insurance actuary
Insurtech

Can InsurTech Rescue Insurance?

Is insurance broken and in need of rescue?

That was the question I recently asked myself whilst hiring a rental car to visit the infamous “White Line” mountain bike trail in beautiful Sedona, Arizona.

When I discovered the full Hertz insurance cover was going to cost me double the price of the actual car hire, I couldn’t help but relay my shock to the salesperson. She proceeded to tell me about their customers’ typical reaction to the accompanying insurance cover purchase and three things, from the conversation, stuck in my mind:

  1. 1
    Many of their customers opt not to take the liability cover even though it leaves them quite exposed.
  2. 2
    A surprisingly high percentage of customers ask for a refund on their insurance payments, at the end of the rental period, if they didn’t need to make a claim!
  3. 3
    Their customers are generally very distrustful of the insurance product they are buying. Customers are often unsure whether it will actually cover their needs if they have to make a claim.

To my mind, this random conversation captured 3 big problems the insurance industry currently faces:

Problem #1: Consumers often don’t value insurance

Insurance is quite an unusual product. Except for maybe a coffin and a fire extinguisher, it’s the only purchase I can think of, that you make but hope to never have to use.

Let’s face it. Buying insurance is usually an uninspiring ‘grudge purchase’ activity. Tedious paperwork, arcane questions, having to think about what can go wrong in your life. Is it any wonder that the experience is up there with a visit to the dentist? Of course, the reality is that should your home be destroyed in a storm or should you be involved in a car accident deemed to be your fault (especially with third-party injury) insurance can be the saving grace preventing potential financial ruin.

Problem #2: Consumers don’t always understand insurance

After going through the pains of considering the potential financial impact of personal tragedy, you are rewarded with the end product…a paper contract.

Not just any old paper contract, but a long-winded, very conditional and often confusing document. How exciting! Again, is it any wonder insurance customers can’t or don’t want to take the time to understand the precise nature of what some deem to be the world’s most boring product?

Problem #3: Consumers generally don’t trust insurance companies

To highlight the trust issue, I turn to the most popular definition of “insurance company” from the crowd-sourced urban dictionary:

An affiliation of pirate-gamblers who accept bets called premiums. The dollar amounts of the premiums are non-negotiable but the amounts of the claim settlements, should the company lose the bet, are rarely delivered without argument.” – Insurance Company (Urban Dictionary)

Whilst the quoted source may be a parody, I believe the underlying inclination signifies the typical level of distrust that consumers have of insurance.

Don’t get me wrong. I believe insurance plays a critical role in our lives and insurance companies can provide a great service as well as a very rewarding career path. But, when it comes to the general consumer view of insurance there seems to be an issue.

Ask 10 random people on the street to describe “insurance” in 3 words and you can be nearly sure at least one person will allude to issues of distrust.

InsurTech to the rescue?

So what is the industry doing to solve these problems? It appears that the nimble insurance technology start-ups (InsurTechs) are playing a large part in leading the way in attempting to overcome these issues. Below, are three InsurTech companies focused on addressing these issues and arguably changing the insurance world for the better:

Solution # 1: Improved Value – METROMILE

Telematics has been around for a few years now. Particularly in Italy, the UK and the US.

Onboard car technology is used to monitor and potentially assess the driving behaviour of each individual driver. Thus moving insurance from a pooled pricing model to a more individual specific model. One where the underlying policyholder risk is more closely monitored.

These telematics technology devices (also known as a “black box”) are able to pick up a number of diverse driving metrics such as:

  • mileage
  • location
  • time of day
  • driving frequency
  • behaviour around hazardous zones
  • speed
  • rates of acceleration
  • braking habits

This information can then be considered in a more accurate and individualised pricing model. One that potentially allows the previously trapped (i.e pooled) policyholder to break free from his or her age or gender (non-EU) status etc and prove their worth as a safe driver that is a good risk and unlikely to have an accident and hence claim.

As well as young male drivers, low-mileage drivers also benefit and this is the market which Metromile have targetted.

The usage-based customisation of insurance certainly seems to be keeping their customers happy with policyholders reporting they feel like they are getting a fairer deal. After all, should a low mileage, safe driver really be subsidising a riskier high mileage driver just because they share common old-school rating factor characteristics?

Metromile have been forging ahead with this lifestyle app-based continuous digital engagement model since 2011. And they show no signs of slowing down. In late 2016 they raised US$192 million in funding through which they acquired a carrier enabling them to now underwrite their own policies.

Solution #2: Better Simplicity & Understanding – TROV

The Trov promise:

As simple as Tinder and as beautiful as Airbnb” – Scott Walchek: CEO of Trov

Trov provide on-demand insurance for personal items that can be toggled on and off via a few simple taps from your phone. They aim to provide the mobile generation with easy protection which they can enjoy “without worrying about rigid policies and confusing fine print”.

In addition, Trov seems to be jumping on the personalised cover bandwagon – treating policyholders as individuals instead of an average risk within a cohort. Their flexible app gives customers the option to tweak their cover towards their own personal circumstances. As one customer put it: “Why pay for an expensive insurance plan designed to cover your worldly belongings when all you really care about is your mountain bike and your laptop”.

Protect just the things you want – exactly when you want – entirely from your phone” – Trov Website

This simplicity and flexibility seems certain to appeal. I personally like the idea of being able to quickly and easily protect my mountain bike by getting temporary insurance for the times when I do actually take it out and use it. And if a claim is required, it’s all handled via an in-app chatbot. Insurance for the smartphone generation indeed!

Whilst I do wonder how they counter fraud (given the ability to so easily turn the cover on and off), as we are living in the age of convenience, it would seem that this model is sure to appeal beyond just tech-savvy millennials.

Solution #3: Enhanced Trust – LEMONADE

The poster child of InsurTech. Or at the very least the king of savvy InsurTech marketing. When they shout about paying a claim in 3 seconds, using AI not actuaries and bots not brokers it certainly makes one stand up and take notice. Lemonade began selling insurance nearly 2 years ago and have now amassed a sizeable level of funding and following. They promised to bring trust back into the insurance world – the way it should be and how it was in the beginning.

The tools of their trade: behavioural economics and artificial intelligence.

Their promise to the end customer: simplicity, convenience and affordability.

All done under the guidance of highly regarded chief behavioural officer, Dan Ariely.

But back to the trust issue. How is Lemonade approaching it? Their business model attempts to disrupt the cycle of distrust between insurer and insured. This is done by separating the pool of risk capital from the company’s own 20% flat fee. Essentially this model aims to remove the incentive for the insurer to minimise claim payouts on the basis that doing so will not affect their bottom line (the remaining 80% claim pot gets paid out to small peer groups under a ‘giveback’ scheme, after some unavoidable expenses such as reinsurance cover).

Basically, the deal is: Trust us to pay out your claim quickly, with minimal fuss and without any sneaky “catching you out in the fine print” shenanigans and we will trust you to only claim if it’s genuine.

Knowing that every dollar denied to you in claims is a dollar more to your insurer, brings out the worst in us all… Since we don’t pocket unclaimed money, we can be trusted to pay claims fast and hassle-free. As for our customers, knowing fraud harms a cause they believe in, rather than an insurance company they don’t, brings out their better nature too. Everyone wins.”

Dan Ariely: Chief Behavioural Officer at Lemonade

The behavioural implication, with the removal of potential conflict, is that the enhanced 2-way trust will drastically reduce fraudulent claims. This, combined with the operational cost efficiency savings from AI and technology will allow the company to have happy customers and still make a sustainable profit.

At least that’s the theory.

Now, whilst I love what they are doing, I’m not entirely convinced their model is altogether different from some of the smaller mutuals. Especially those that still maintain some level of social bonds. Maybe I’m biased because they don’t seem to like actuaries, but I also wonder whether their pricing, underwriting and risk management will allow their loss ratios to stay low enough to not impact on their 20% flat fee over the long term. It takes some time for reality to test the theory, in insurance. So I, for one, will be watching the Lemonade space with interest.

Conclusion

So is insurance really broken and in need of fixing?

Firstly, let’s not forget what insurance is all about. In essence, insurance is about the pooling and sharing of risk. Swapping an uncertain, and potentially large, outgo for a small(er) more certain outgo (the premium). This is unlikely to change and insurance companies obviously already do this.

But, I do believe, there is a need to modernise, especially in relation to the customer experience. I don’t see InsurTech companies causing a complete revolution. But they are likely to play a big part in the ongoing insurance evolution.

What do you think? Does insurance need to evolve? Is InsurTech the answer to the customer experience issues? Are these InsurTechs all marketing talk and lacking substance? Will the asset rich insurance incumbents ultimately lead the way in the unfolding tech world evolution?

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Wearable Technology in Insurance - ProActuary
Insurtech, Technology

Wearables in Insurance: Where Do We Go From Here?

This essay was awarded first place in the Society of Actuaries' Actuarial Innovation and Technology Essay Competition in 2020. It has been republished here with kind permission from the Society of Actuaries. The original essay and other entries can be read in full here.

Introduction

Actuaries, working in the pre-digital era, writing out calculations by hand, would have found it difficult to imagine today’s actuary having such immense data, technology and computing power at their disposal. 

Ubiquitous smartphones, advanced artificial intelligence, autonomous vehicles, the internet of things, drones and blockchain are just some of the new technologies today’s actuary is exposed to. The future holds even more exciting prospects with emerging fields such as quantum computing, 5G, brain-computer interfaces, smart pills and smart dust all coming to the fore.

Naturally, these changes provide immense possibilities, but also challenges and potential repercussions for the data-focused actuarial profession. As a forward-looking profession, it seems imperative that actuaries must change with the times and learn to embrace the challenges and opportunities the new technology-focused digital world is creating.

This essay summarizes the current use of technology within insurance (InsurTech) with a focus on wearable technology. Thoughts are provided on new wearable-derived data sources insurance companies may use in the future and the potential advantages of using data from wearables. A summary of opinions are presented on important questions that must be addressed as the use of wearables in insurance becomes more advanced and widespread.

In the era of tightening data regulations and consumer concerns, a blockchain solution is proposed. The essay concludes with thoughts on the important ethical considerations actuaries and other insurance stakeholders should consider, to ensure we are using wearable data in an ethical and responsible way.

The Emergence of InsurTech

In recent years many high profile insurance thought-leaders have argued that the industry has been lagging behind other industries (e.g., banking) which have increasingly embedded technology throughout their business models. However, this is now beginning to change as we witness the emergence of InsurTech – the use of technology innovations within insurance.1

InsurTech has seen many technologies coming to the fore. For example:

  • Telematics (e.g., Metromile use telematics to offer affordable car insurance for low mileage drivers)
  • Artificial Intelligence (e.g., Lemonade offers ‘zero paperwork and instant everything’ home insurance powered by AI)
  • Blockchain (e.g., Insurwave is a blockchain-enabled insurance platform for marine insurance)
  • Robotics (e.g., Digital Workforce uses robotics to enable insurance companies to automate processes)
  • The Internet of Things (IoT) (e.g., Neos Ventures combines connected home devices and home insurance)
  • Wearable Technology (Wearables) (e.g., John Hancock sells interactive life insurance policies that track fitness and health data through wearable devices and smartphones)

Wearables

One of the key technologies to emerge over the last decade has been the Internet of Things (IoT). Our World is now saturated with a vast array of sensors that capture information across many areas including transport, agriculture, healthcare and property.

IoT sensors have also made their way into wearable technologies that collect data across many aspects of an individual's lifestyle, particularly those relating to health and health-related behaviors. We have also moved beyond wrist-borne devices to now seeing wearable devices in shoes, clothing, accessories and jewelry. Consider, for example, the Oura Ring - a seemingly normal looking ring that incorporates a plethora of sensors measuring various sleep, activity, and recovery metrics with a high degree of accuracy.3

This availability of more bespoke and timely data on biometrics and the ability to understand this data, via machine learning, is having a profound impact, both on the medical profession and on patient care. The ability to detect deterioration in a biometric(s) of choice can lead to a preventative intervention, which can be delivered at lower cost and higher efficiency than a curative response in the absence of the biometric warning.4 Furthermore, research from behavioral psychology and economics confirms that more immediate feedback results in a higher probability of a behavioral adjustment of an individual.5 The early evidence on the use of wearable technology is that it is an effective tool in changing individual attitudes, behavior and ownership of health problems to the net benefit of the subject’s health.6

Wearable data, therefore, provides information that can be conceivably exploited to both improve our understanding of health and mortality related risk factors, and also used as an indirect channel to incentivize and help improve health behavior for society.

Hence, wearables also hold much promise for the health and life insurance industries to incorporate health and behavioral data to aid insurance underwriting, pricing, product innovation and customer engagement. This is evidenced by some pioneering insurance companies such as John Hancock, Vitality, United Healthcare and Oscar that have already incorporated wearables into their product design.

Wearable Data

The insurance companies currently embracing wearables are typically monitoring activity levels (e.g., via step counts) and rewarding policyholders in the form of discounts and other perks. However, as the technology advances and matures it seems conceivable that other health metrics may be used by insurers to underwrite policies with greater accuracy (see Farrell & McCrea, 2018).7 Health metrics that hold particular promise include:

  • Continuous Blood Glucose Monitoring (CGM): CGM is now feasibly monitored by individuals (from both an economic and a practical sense) because of the advancement of sensors such as that offered by The Freestyle Libre System and the Dexcom G6 system. Insurance for diabetics has historically been challenging as insurers’ class these individuals as high risk. CGM may act as a means by which cheaper insurance can be purchased by diabetics that are managing to control their blood sugar levels through means such as exercise and diet.
  • Heart Rate Variability (HRV): HRV measures the variation in the time interval between heartbeats. It has been studied extensively in the medical research field and has been shown to be a predictor of morbidity and mortality. As HRV provides a non-invasive and easy way (e.g., measuring via the previously discussed Oura Ring) to measure autonomic nervous system imbalances, it could be potentially used by insurance companies in the future. Insurers could potentially use HRV as a rating factor and also a means to help inform policyholders of insights into their health and to even facilitate healthy behavior change.

Advantages of Using Wearable Data in Insurance

Incorporation of self-quantified wearable health data into insurance product design provides insurance companies with many potential advantages. I discuss some of these below:

1. Product Innovation

The availability of these new technology-driven data metrics opens potential new avenues for health and life insurers to provide cover for previously difficult to insure or uninsurable risks.8 This is aided by the potential to now provide ongoing feedback data to the insurer in a real-time basis, overcoming the historical underwriting of coverage whereby the insurer typically only captures mortality and morbidity related metrics at a single point in time.

2. Reduced Adverse Selection and Improved Underwriting and Product Pricing

By recording data on an individual’s health behavior, the information asymmetry between the policyholder and the insurer is reduced, thus enabling an enhanced granular risk differentiation based on the true risk levels of the drivers to be achieved. This potentially reduces the problems of adverse selection. Wearable technology may, therefore, lead to the identification of newly available and potentially relevant information and rating factors which are important determinants of health and life related insurance products. This is particularly prevalent in today’s insurance market as insurers engage in a ‘race to simplification’ so that they can offer adequately priced products whilst avoiding having to obtain invasive and time consuming policyholder information.

3. Enhanced Customer Engagement

Insurance company products do not lend themselves well to customer engagement, with most insurance buying viewed as a ‘grudge purchase’. In addition, the industry has suffered from a lack of consumer trust. The traditional insurance model, which typically involves contact at a single (annual) point in time, has arguably held the industry back in today’s customer-centric world. Incorporating wearables into product design may now help to overcome this as customers are engaged with on a more frequent basis with the potential to reward policy-holders for desirable (i.e., risk lowering) activities. In addition, wearables data might give the insurance company an opportunity to provide policyholders with valuable health information and analysis and motivation (through discounts and rewards) to engage in healthier behaviors.

The Challenges Ahead

Although some insurance companies are already embedding wearables into product offerings, the application of wearables within insurance is still nascent and many opportunities remain to be uncovered and challenges remain to be solved. Actuaries, as insurance problem-solvers and historic gatekeepers to policyholder premium calculations and insurance product development, are likely to play a significant role, along with other stakeholders, in addressing the many future issues around utilizing wearable data and embedding the technology into insurance. Some issues and questions actuaries may contribute to answering include:

  • How can the insurance industry use more timely and rich biometric data to refine their underwriting and pricing practices and provide a more personalized product?
  • Can wearable data be used to predict the risk of adverse health outcomes and help incentivize healthy behavior, thus altering the policyholder/insurer relationship?
  • What are the socio-economic implications from potentially reducing adverse selection in insurance markets via pricing using wearable technology data? Does more accurate pricing of health insurance open the possibility of extending coverage to those deemed uninsurable or difficult to insure (e.g., diabetics)? Will certain high-risk individuals be penalized as a result? Will they still be able to get insurance? Should regulatory bodies, therefore, provide greater oversight?
  • How will customers react to insurers introducing new technology into their products? Will they enter a trusting relationship that encourages data disclosure?
  • How can we ensure that we use new novel data sources and artificial intelligence in an ethical manner within insurance?

Furthermore, as the future is likely to move towards more detailed data being captured, on a more frequent and possibly real-time basis, there are various implementation impediments to overcome. Actuaries may also help solve problems in the following areas:

  • Data privacy, security and ethical debates have been a central part of the “big data” landscape since its rise to prominence. What are the demographic, cultural, legal and institutional barriers to the sharing of private information? How have users of private data in other technological spheres overcome these barriers?
  • What are the technological challenges in the collation, storage, processing and communication of this very detailed and real-time data? Can insurers provide guarantees for the validity and source of the data using technical means?

Blockchain: Part of the Solution?

A major hurdle for insurers’ ability to use wearable data relates to effectively managing policyholder concerns regarding privacy and control of data.

actuaries and blockchain

Blockchain, as a distributed ledger technology, holds much potential for the actuarial profession (see Farrell (2018)9). The incorporation of wearable data into insurance may also benefit from blockchain as it potentially allows policyholders to control access to personal records and to know who has accessed them.10 If insurance pricing is to be based on more extensive levels of health and behavioral data, then this data needs to be shared with the insurance company whilst allowing privacy to be maintained as well as adequate policyholder controls (e.g., releasing a certain aggregated level of the data and only for specific purposes) and suitable security mechanisms to be put in place.

Blockchain has already shown promise, within healthcare, in the facilitation of sharing medical data without the need to turn the data over to another party.11 It also, therefore, seems to have potential to be used to help manage wearable data for insurance companies of the future.

Ethical Considerations

With great power (to ‘nudge’) comes great responsibility

Wearable technology has the potential to change the insurer and insured relationship to a more continuous risk-management support role where the insurer helps to prevent adverse conditions taking place by alerting policyholders and also nudging them in the right direction. However, this shift towards ‘predicting and preventing’ and influencing behavior has many potential repercussions that should be considered. To highlight this, consider the following examples:

  • An insurance company rewards policyholders for activity via recording steps. As a result, the policyholder goes for a run rather than doing yoga (which they would enjoy more and would have a better marginal impact on their overall health).
  • A health insurer offers a policyholder a free watch with heart health monitoring capability. The policyholder willingly accepts it as they expect the data, from their rigorous fitness lifestyle, to reduce their premium. The data reveals a heart issue. The insurance company withdraws cover.

An Ethical Example: Adverse Selection - Friend or Foe?

As ‘big data’ continues to increase, the insurance world appears to be moving towards more individualized, granular pricing. With both increasing and more accurate data availability (e.g., via wearables) it is likely that the asymmetry of information between the insurer and the policyholder will decrease, in the absence of regulation. This situation will inevitably lead to a decrease in adverse selection as the pooling of risk involves pooling lives of a more similar nature and hence fewer lives leave the risk pool because of a pricing mismatch between risk and premium.

There are many socio-economic implications from potentially reducing adverse selection in insurance markets. The traditional view is that reduced adverse selection is advantageous and desirable since policyholders are paying a premium closer to a statistically ‘actuarially fair’ price, that truly represents their level of risk. However, this traditional belief provides a good example of a situation where insurance companies and regulators may now need to reconsider traditional views considering the new data rich world we inhabit. For example, British actuary, Guy Thomas (2018), argues that some adverse selection may actually be good for society if we consider the social value created from insurance coverage as a probabilistic ‘loss coverage’.12 I show this situation below (diagram reprinted with kind permission from the author):13

The Potential Impact of Adverse Selection on Insurance Loss Coverage

The Potential Impact of Adverse Selection on Insurance Loss Coverage

This example helps to highlight how some groups of consumers (in this case, the low risk insurance policy holders) may benefit from enhanced personalized pricing and other individuals may be potentially disadvantaged (in this case, the high-risk individuals - who are arguably most in need of insurance - who were previously being subsidized by the lower risk policyholders).

This serves as just one example of how insurance companies, regulators and actuaries must carefully consider the implications of incorporating new data into pricing models to help ensure that we are using data responsibly in an ethical manner.

Concluding Thoughts

In an era where data is growing at an exponential rate and machines are progressively more capable of out-performing humans at many tasks, the actuarial profession (like many professions) is facing unprecedented change. Novel data sources, such as from wearable devices, combined with more sophisticated and powerful analysis, is one example of how technology is altering some areas of traditional actuarial work. As we continue to move into this new digital data-rich paradigm, new opportunities and challenges will emerge. Technology is creating a new world before our very eyes, providing actuaries with an opportunity to capitalize on our strengths of technical expertise, problem-solving ability and professionalism to ensure we remain relevant and trusted business professionals in the future.

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Is Adverse Selection Insurance Good? | Proactuary | Blog
Insurtech

Adverse Selection: Friend or Foe?

As big data continues to increase, the insurance world seems to be moving towards more individualistic, granular pricing.

Consider ZhongAn, in China, for example. As an innovative digital insurer, utilising big data to its full extent, they are focused on micro-pricing premiums in a very personalised way. With more than 460 million customers acquired over the last 3 years, their digital and individual risk assessment approach seems to be working.

But is this move towards more individual risk-pricing a good thing from a societal point of view?

The insurance industry has traditionally claimed that not being able to accurately price insurance products, with regard to individual risk, will lead to the adverse selection spiral as the low-risk individuals in the pool reduce or forgo their insurance.

However, UK actuary, Guy Thomas, challenges this orthodox view by contesting that some adverse selection (and hence some restrictions on risk classification) is beneficial from a public policy perspective.

I have reviewed his, recently published, Loss Coverage book for The Actuary magazine.

Do you agree that some adverse selection (and hence restrictions on risk classification) may be beneficial for society as a whole? Or should insurers always be aiming for an “actuarially fair” premium?

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Insurtech

The Enterprise Risk Management (ERM) Actuary

The Enterprise Risk Management (ERM) Actuary

What is the ERM actuary? Why is Enterprise Risk Management (ERM) important for you as an actuary?

To answer these questions we first need to take a step back and think about what exactly risk is:

Risk & Reward

Defining risk and deciding how to manage it are key considerations for modern corporate management.

Risk is a nebulous concept, with no single accepted view or definition. Different fields may view risk in often seemingly disparate ways. For example, numerically focused professionals, such as actuaries, view risk as an objective phenomenon which is quantifiable.

In the world of finance, risk is often viewed as the chance that the return achieved on an investment will differ from that which is expected. In other words, volatility of return. Social sciences take a contrasting perspective, envisaging risk as a subjective phenomenon which is not always accurately quantifiable. 

Despite these discrepancies in defining risk, it is widely accepted that the pursuit of greater returns requires additional risk exposure by the enterprise.  The greater the risk exposure, the greater the potential reward on offer. Or in layman’s terms, “there is no such thing as a free lunch.”  From a corporate perspective, shareholders invest funds in the organisation and expect to receive a return commensurate with the level of risk they perceive they are undertaking. 

Deciding upon the appropriate level of risk to undertake is therefore a key corporate consideration, which the ERM actuary will need to carefully consider. It is often a delicate balancing act with a fine margin for error.  If the enterprise does not take on enough risk, they may err on the side of over-cautious risk aversion and may not be fully exploiting potential investment projects.  On the opposing side of the continuum, excessive risk-taking can leave the organisation in a precarious position, whereby their level of risk exposure is higher than the absorption capabilities of their provisioned capital (i.e., the amount of liquid cash the organisation needs to hold to safeguard its solvency and economic stability regarding the investment project(s) in question).

The optimal risk-taking position lies between these extremes and is characterised by exposing the organisation to an acceptable level of risk that also enhances the potential investment return.

The Risk/Return Profile

ERM actuary

Source: Chapman (2006)

The above diagram highlights this delicate and important relationship between optimal risk and return by showing how the optimal risk-adjusted return is found by striking an appropriate balance between low-risk exposure and aggressive risk-taking.

From a corporate finance viewpoint, the additional risk can come in the form of systematic risk, which relates to undiversifiable market uncertainties, or from firm-specific idiosyncratic risk.  

From a portfolio perspective, risk that cannot be eliminated, via diversification, requires an enhanced expected return, above the risk-free rate, for an investor to be motivated to undertake it.  

The firm-specific (idiosyncratic) risk and the treatment of it, within an appropriate risk management framework, is a widely debated topic.

Early research by Modigliani and Miller (1958) questions the validity of risk management efforts.  However, more recent risk practitioners and scholars, such as ERM actuary and author of "Financial Enterprise Risk Management," Paul Sweeting, have outlined the benefits and rationale for managing risk, such that nearly all organisations now engage in risk management to some extent.  

With this increased acceptance of risk management as a potentially valuable and even necessary business activity, the discipline itself has naturally evolved.  A prominent development has been the movement towards managing risks in a more integrated enterprise-wide fashion that considers risk in a portfolio context (although Markowitz developed his efficient frontier theory primarily for portfolio asset management, it revolutionised how risk was managed in every industry and also draws parallels to the ERM approach) and inherently aligns risk management with corporate governance and strategy.  

This emerging holistic approach to the aggregation of risk is generally referred to as Enterprise Risk Management (ERM). The actuarial profession has also embraced the idea of the ERM actuary, over the last two decades, with many actuaries taking on positions such as the Chief Risk Officer (CRO), where they are tasked with overseeing the holistic aggregated risk position of the enterprise.

The Emergence of Enterprise Risk Management (ERM)

Enterprise Risk Management (ERM)


Modern businesses have to contend with increasing complexities due to the rapid and dynamic change and ever-growing volume of global interconnections.  Consider, for example, the effect increasing computing power and internet technology has had on how businesses market, sell and operate.  This pace of change shows no sign of slowing down as emerging technologies, such as blockchain and artificial intelligence, now coming to the fore. 

ERM is a multifaceted, ambiguous concept that eludes simple interpretation.  The integration of risk management techniques into a holistic and integrated framework is defined by COSO (2004) who define ERM as:

Enterprise risk management is a process, effected by an entity’s board of directors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risk to be within its risk appetite, to provide reasonable assurance regarding the achievement of entity objectives.

From the firm-specific perspective, it is evident that risk management has seen some catastrophic failures over the last 25 years.  The infamous Barings Bank collapse in 1995 represented the failure of risk management systems to monitor, detect and limit the actions of a rogue trader who had concentrated risks in increasingly larger amounts to conceal trading losses.  The Enron (2001) and Worldcom (2002) debacles had, at their core, a breakdown in corporate reporting systems that masked underlying risk exposures.  The collapse of Lehman Brothers (2008), perhaps the most enduring event of the most recent financial crisis resulted from an explosion in underwriting activity in subprime mortgage related products combined with an arguable lack of understanding of risk exposures at the upper echelons.  In particular, underestimation of underlying asset correlations and the risks posed by these products led to an inherent vulnerability of the institution, which ultimately toppled in the systemic downturn of 2007-2008. More recently, in 2020, we have witnessed worldwide businesses struggling to maintain operations because of the Covid-19 pandemic.

Arguably, many of these failures can be attributed to the piece-meal approach that has arisen from traditional, silo-based risk management processes.  Up until the mid-1990s, a silo approach to corporate risk management was habitually used, (often termed Traditional Risk Management (TRM)).  This approach is characterised by the management of individual risks in separate units often using a highly disaggregated method.

In contrast, the discipline of ERM takes the advanced view that risk management needs to bring together the individual silos of risk management under a more portfolio-based, holistic approach.

The aggregation of significant hazard, financial, operational and strategic risks marks a shift in focus from a defensive endeavour to a more offensive discipline.  In other words, the ERM approach is a result of the maturing, continuing growth and evolution of the risk management division and its application in a more structured and disciplined way (McCarthy and Flynn, 2004).

By breaking down the historical silos, operating within the organisation, and tackling risk on an enterprise-wide scale, in an aggregated enterprise-wide fashion, the risk management process is equipped to deal with the additional threats and opportunities faced in the rapidly evolving business world.

As the world has changed at a rapid rate over the last two decades so has the role that risk management plays within the organisation.  An increasingly complex layer of connected risks has called for the adoption of an integrated, holistic approach to risk management.  Actuarial and corporate risk management strategies have expanded beyond financial and hazard risk mitigation practices, such as using insurance and financial hedging instruments, to now include a multitude of other risk types, such as operational risk, reputational risk and strategic risk.  

Risk management is no longer confined within the traditional silos of operation that existed in the past. Whereas historically, risk management activities were compartmentalised and uncoordinated with a focus on using insurance and derivative instruments to protect the firm against hazard and financial risks, a holistic approach has emerged to coordinate management of all significant risk exposures the organisation faces (McShane et al., 2011). 

D’Arcy and Brogan (2001) put forward the following alternative ERM definition, adopted from the Casualty Actuarial Society (CAS):

ERM is the process by which organisations in all industries assess, control, exploit, finance and monitor risks from all sources for the purpose of increasing the organisation’s short and long-term value to its stakeholders.

This definition is particularly revealing as it highlights some key ERM principles and important differentiators from more traditional risk management practices:

  • ERM is a discipline and should therefore have support from the top of the organisation to be carried out in an orderly, prescribed manner.
  • ERM applies to all industries, not just the financial industry.
  • ERM focuses on all risk types, not just those that are insurable or financial in nature.
  • ERM accounts for all stakeholders, not just shareholders.  Hence regulators, customers, employees and suppliers may all be considered in the ERM process.
  • ERM is focused on the long-term and should ultimately create tangible value for the organisation.

Embracing ERM from a management perspective may seem intuitively obvious and enticing, especially in turbulent times, when one considers the potential ERM benefits, such as:

  • Helping choose the optimal level of risk for the organisation (Meulbroek, 2002).
  • Improving internal project decision making (Nocco and Stulz, 2006)
  • Enhancing capital efficiency (Myers and Read, 2001).
  • Reducing hedging and insurance risk management expenditures through recognition of diversification effects (KPMG, 2009).
  • Improving board transparency (Beasley et al, 2005).
  • Reducing capital costs (Samanta et al, 2004).
  • Reducing the volatility of returns (Sweeting, 2011).

However, the ERM actuary must consider whether the potential paybacks from ERM when weighed against the absorption of finance and human resources (which may be material for such an enterprise-wide undertaking) are worthwhile.  

Despite the theoretical rationales listed above, if and to what extent ERM adds value has yet to be established with a high degree of certainty.  

Researchers, such as Beasley et al. (2008) and Hoyt and Liebenberg (2011), provided some initial evidence for ERM value creation, but a major validity impediment of these studies has been the development of a reliable measure of the ERM construct (McShane et al., 2011).

Beasley et al. (2008), Hoyt and Liebenberg (2011) and Lin et al. (2012) utilise Chief Risk Officer (CRO) appointments as a binary proxy for ERM implementation and base their findings on the supposition that CRO appointment is indicative of ERM implementation.  The rationale being that the CRO is the executive accountable for enabling the efficient and effective governance of significant risks, and related opportunities, to a business and its various segments.  In more complex organisations, the CRO is generally responsible for coordinating the organisation’s ERM efforts.

Clearly, the literature has fallen short on using an all-encompassing ERM measure that addresses and explores the actual processes and factors (Kraus, 2012).  I, therefore, argue that much of the empirical evidence presented to date only provides early indication of a relationship between ERM and firm value. There is a need to empirically examine the ERM value relationship with a much more valid and revealing ERM construct.  Additionally, researchers (Beasley et al., 2007; Lin et al., 2012) have also found early evidence to suggest that ERM does not in fact create value and may potentially destroy it. 

In my widely cited 2015 paper, “The Valuation Implications of ERM Maturity” I was able to use a newly available, and previously under-utilised, data-rich source from the Risk and Insurance Society that provides in-depth ERM maturity model survey responses from a sample of public listed organisations.  I used this data to empirically investigate the relationship between the extent of ERM implementation and firm performance to provide a unique contribution to the relationship between ERM maturity and firm value

From Traditional Risk Management to Enterprise Risk Management

ERM actuary


Risk management is often referred to as the process of identifying, assessing and prioritising risk exposures followed by a co-ordinated application of resources to effectively minimise, monitor and control the likelihood and/or severity of negative events.  Over the last 70 years, businesses have increasingly taken risk management into consideration as part of operating a successful long-term company.  

Risk management particularly came into effect in the 1970s and 1980s as organisations realised that firm-specific risks (also known as idiosyncratic or unsystematic risk) were important to be managed, making it a high-priority item for investors.  

Prior to this time period, risk management focused on managing the downside of risk, which was typically resolved through insurance, which simply pooled the risk with other similar risks, thus allowing the insurer to accept the transfer of risk in a profitable and mutually beneficial setting.  By pooling risks together, an insurance company can utilise actuarial science theory and loss distributions to predict with a high degree of accuracy the potential losses (claims) from year to year.

However, the transfer of risks via insurance only took into consideration hazard type risk exposures, which, although important, only pertain to a sub-section of risks the organisation may face. Insurable hazard risks are typically risks that are independent, measurable and do not allow the organisation to benefit (i.e. no potential upside in contrast to (for example) financial risks).  Hence it became increasingly evident that some risks that were previously transferred to an insurer could instead be prevented, or their severity reduced, through efficient loss-prevention and control systems.  Furthermore, it often made sense to instead retain some of these risks within the company.  This led to a broader risk management approach to insurable hazard risks.

As the use of financial derivative products gained momentum in the early 1970s, risk management moved away from being a reactive process to focus more on proactive procedural practices.  

Most ERM actuaries will be familiar with the work of Black and Scholes who published the ‘Option Pricing Model’ in 1973, ushering in more modern aspects of risk management where risks outside the aforementioned insurable hazard risks (e.g., financial risks) could be effectively priced and also mitigated. They found that the use of their pricing model provided a mechanism whereby organisations could effectively hedge their financial risks by openly trading derivative products on an exchange, at a price that accurately reflected their risk. These developments have led to a much more fluid and active transfer of risk between parties and have formed much of today’s corporate risk mitigation strategies.

It seems reasonable to assert that an optimal strategy for achieving success is to maximise strengths and minimise weaknesses.  Bernstein (1998) applied this same line of thought to risk management by conveying: “The essence of risk management lies in maximizing the areas where we have some control over the outcome while minimizing the areas where we have absolutely no control over the outcome and linkage between effect and cause is hidden from us”.  It is therefore clear that risk management plays an integral role in successfully achieving business objectives and has become a part of every organisation.

There is no one way to practise risk management, as it should be scaled according to not only the size of the organisation, but also based on the nature and complexity of the risks it faces.  In other words risk management should be practised in accordance with the organisation’s risk tolerance. Risk tolerance is a measure of the amount of uncertainty that an organisation is prepared to accept in respect of negative changes to its business or assets.  This differs slightly from ‘risk appetite’, which can be defined as ‘the amount and type of risk that an organisation is willing to take in order to meet their strategic objectives. Risk management should also be comprehensive and dynamic enough to react to changes as necessary.

ERM

ERM is considered to be an advanced framework for risk management, and it first appeared in 1995 in the Joint Australia/New Zealand Standard for Risk Management (AS/NZs, 2004). However, it was James Lam who, in 1993, became the first person to use the title of “Chief Risk Officer” even before ERM became mainstream (Lam, 2014). The appointment of a CRO is often regarded as a signal of holistic risk management implementation and has therefore frequently been used as a proxy for ERM in many academic studies.

ERM is often viewed as a difficult to define discipline, but most ERM literature seems to agree that it relates to interchangeable concepts, such as integrated risk management”, “strategic risk management” and “holistic risk management”.  For instance, Beasley et al. (2006) introduce ERM as a holistic approach across an entire organisation, and McShane et al. (2011) argue that ERM is “a construct that ostensibly overcomes limitations of silo-based traditional risk management”.

Although scholars and organisations have taken differing slants on their views of ERM, we can draw some clear parallels from the various definitions.  Namely, that ERM is an integrated and holistic evaluation of all the risks facing an organisation with a focus on how those risks affect the organisation in aggregate. Integration is therefore a key component of ERM and stems from:

  1. 1
    An integrated risk organisation that encourages a centralised risk management process.
  2. 2
    The integration of risk-transfer strategies.
  3. 3
    The integration of risk management into the firm’s culture and corporate decision making processes.

Scholarly research, such as that carried out by Banham (1999), Doherty (2000) and Meulbroek (2002) support the view that ERM is an integrated risk management framework and allows managers to benefit from new insights with regard to risk correlations and connections, which are generally missed without an all-encompassing and comprehensive approach.

This movement away from an exclusive focus on financial and insurable risks, towards encompassing the full spectrum of risks, is a key differentiator from traditional risk management approaches.  A further differentiator between TRM and ERM practices is the fact that ERM does not simply attempt to minimise an organisation’s risk threat, as TRM practices may have done, but instead focuses on risk opportunities and even how risk can be actively sought for competitive advantage.  This vantage point is very important for the ERM actuary, since from this new perspective, many ERM definitions stress value creation and how the implementation of the ERM discipline can help a business improve decision making, thus increasing the likelihood of achieving business objectives.

Although ERM has been recognised as a discipline for less than three decades, the debate for a holistic risk management approach has been on-going perhaps since Kloman’s (1976) publication of “The Risk Management Revolution”.  Kloman (1976) advocated for a more coordinated, or “holistic”, approach to risk management, and other researchers, such as Crockford (1980), Bannister and Bawcutt (1981) and Stulz (1996), all called for a move away from the silo-based practice of TRM, towards a more optimised risk management system that integrated activities under a single framework.

With the range of risks that companies feel they need to manage continually expanding there has been an increasing recognition that most guidelines, methods and best practises focus on only a specific part of the business and do not take a systematic approach to the problems most organisations face.  

ERM builds upon TRM procedures by taking a holistic approach to the measurement and management of all significant risks, hence providing an improved framework to deal with an increasing array of inter-connected risk exposures.

Kraus and Lehner (2012) discussed how two early facets of TRM practices have been incorporated into ERM.  Firstly, they contest that since company risk management practices have become more sophisticated over time, managers recognise that both financial risks (such as movements in stock prices, commodity prices, exchange rates and interest rates) and non-financial risks (such as reputational, operational and strategic risks) should be managed together.  This acknowledgement has led to the development of new risk-transfer products that combine more than one type of risk, such as weather derivatives and catastrophe bonds, as well as the application of copula functions to help assess risk correlations.  Again, according to Kraus and Lehner (2012), the second TRM component that has contributed to the rise of ERM relates to general management thinking.  Contingency planning has always been an important part of corporate policy with the purpose of identifying activities that may be threatened by adverse events to ensure systems are in place if such events do occur.  Business continuation management has extended the practice of contingency planning by requiring comprehensive internal control systems.  Thus, there is evidence to suggest that TRM’s silo-based approach has been deemed inefficient as both the adverse and possibly beneficial effects of risk correlations are not adequately considered, potentially producing inefficiencies and risk oversight.

To summarise, in today’s changing business world, TRM practices are no longer viable in terms of ensuring that organisations manage risks in an enterprise-wide fashion.  This has led to an advanced framework that can manage risk in a more integrated holistic fashion, such as ERM.  

In the process of managing all risks, ERM must embrace every significant risk regardless of the source–whether it is strategic, financial, operational or hazard-based–to ensure that every significant risk exposure is managed in the context of the organisation as a single comprehensive entity.

Drivers of ERM

Whilst the growth of ERM has varied by organisation and industry, the transition away from the more silo-based and less aggregated traditional risk management practices can be attributed to a number of fundamental drivers, many of which are described in detail by the Casualty Actuarial Society (CAS) ERM Committee (2003). These drivers, from the CAS, Overview of ERM paper, are summarised and discussed in turn, below.

Increasingly Complex Risks

Modern businesses are increasingly recognising the growth in both the number and nature of risks to which they are exposed. As the business landscape has altered, new vulnerabilities have grown in importance. Globalisation, for example, has led to more firms facing regulatory obstacles, geo-political exposures, supply chain risk and foreign exchange rate risk.

Furthermore, recent high-profile losses and failures, such as the 2010 oil spill in the Gulf of Mexico, which has since seen BP set aside $42 billion to deal with the repercussions (Reuters, 2015), have increased focus on operational and strategic risk.

Heightened financial sophistication, advancing technology, emerging geo-political risks and accelerating business activity have also contributed to the number and the growing complexity of risks organisations face.  Beasley et al. (2015a) carried out a study of more than 1,000 members of the America Institute of Certified Public Accountants (AICPA) business and industry group and found that 59% of their respondents believed that the volume and complexity of risks had changed “extensively” or “mostly” in the previous five years.

Along with increased risk levels, and increased recognition of them, ERM has also been driven by a greater awareness of the interconnected nature of risks.  A study conducted by the professional services firm, Deloitte (2013), explored the extent by which risks are correlated.  The study, consisting of 1,000 of the world’s largest global public companies, between 2003 and 2012, reported that 38% of companies suffered a one-month share price decline of more than 20% relative to the MSCI Global 1000 index.  The study report concluded that almost 75% of these major losses occurred due to correlated and interdependent risks.

Stakeholder Pressures

Miccolis and Shah (2000) reported that both direct and indirect external pressures have driven the migration towards this integrated and strategically focused risk methodology.  The 2007–2008 global financial crisis and on-going corporate risk management failures have led to a greater insistence from regulators, institutional investors and corporate governance oversight bodies that board members and senior management of organisations take more responsibility for managing risk on an enterprise-wide scale and that risk practices become much more stringent.  

As an example, the Sarbanes-Oxley Act (2002) stipulates that corporations must scrutinise their risk profiles using a holistic, enterprise-wide approach as opposed to the more traditional silo-based approach.  A further example highlighted by Hannoun (2010), relates to the introduction of Basel III by the Basel Committee on Banking Supervision in order to help correct the failings of prior accords by improving an organisation’s risk awareness and loss absorbing ability.  Supporting this further, a 2008 study by Deloitte, reported that the major force behind ERM was an organisational need to respond effectively to regulation, with ERM seen as the appropriate mechanism to manage increasingly complex compliance requirements.

Rating agencies, and in particular S&P, have also begun to incorporate the presence of an ERM framework into their rating factors, and thus it can be presumed these policies serve as an additional driving factor behind ERM.  Finally, it would be remiss not to mention shareholders, as the owners of public traded companies, who are exerting influence via a desire for more predictable and stable earnings if they are to invest capital.  Shareholders are also increasingly seeking tangible proof of effective and value-creating risk management practices.

Portfolio Theory

A driving influence behind ERM is the management of all the significant risks facing the organisation within a portfolio context.  Modern Portfolio Theory (MPT), developed by Markowitz in 1952, highlighted how risk-averse investors can construct investment portfolios that optimise expected investment return (based on a given level of market risk) by considering the correlation levels between the assets included in the investment portfolio.  By diversifying a portfolio of financial investments (with varying levels of financial volatility risk) that were not 100% correlated, Markowitz showed that the variability in returns could be reduced.

Similarly, business entities will generally invest in a range, or portfolio, of different projects.  These businesses also consist of a multitude of different departments, potentially operating from separate and often international locations.  The 21st century business is increasingly exposed to a vast array of interconnected risks with varying degrees of correlation between exposures.  ERM, therefore, parallels MPT by viewing the organisation’s risk exposures in a portfolio context, with inter-dependent and connected risk exposures, which can therefore be optimised by taking advantage of the “portfolio effect”. 

The portfolio approach to risk management (to both financial and non-financial risks) therefore encourages a greater understanding of the total risk facing an organisation and allows senior management to diversify risks and exploit natural risk hedges (Lam, 2014).  As well as the possible beneficial diversification effects of correlated risks, it should be noted that there is potential for risks to compound and lead to significant adverse effects that may not have occurred if the risks were isolated.

CAS (2003) highlights this danger by arguing: “even seemingly insignificant risks on their own have the potential, as they interact with other events and conditions, to cause great damage” (CAS, 2003).

Enhanced Risk Quantification Abilities

A further driving force in ERM adoption has been the increased ability and tendency to measure and analyse risks as a result of advances in risk-modelling expertise and technology.

Organisations are increasingly able to quantify risks, which were traditionally viewed as unpredictable or infrequent. Catastrophe modelling, for example, has been widely utilised by actuaries in the insurance world since the early 1990s. Catastrophe modelling (or cat modelling) is the process of using computer-assisted calculations to estimate the losses that could be sustained due to a catastrophic event such as an earthquake or flood. These products have proven to be very popular such that in 2014, a record $8 billion worth of catastrophe bonds were issued (The Economist, 2015a).

Value-at-Risk (VaR), as a probabilistic measure of market risk, is another risk-quantification methodology that has also been widely adopted since the 1990s and now forms a large part of modern regulatory requirements, such as the Basel Accords in the banking industry.  The rapidly increasing speed and ease by which technology has allowed us to measure modern financial risks has facilitated the emergence of such risk measures.  This progress in risk quantification has provided regulators and organisations a level of confidence to ensure that they operate within both regulatory parameters and corporate risk-tolerance levels.  The European Union (EU) Solvency II Directive for instance, prescribes Solvency Capital Requirement for EU insurers, by specifying that they: “shall correspond to the Value-at-Risk of the basic own funds of an insurance or reinsurance undertaking subject to a confidence level of 99.5% over a one-year period” (Floreani, 2012). 

The vast increase in collated data in recent years, combined with the ability for data to be instantaneously transferred, has also led to huge developments in analytical prowess. Increasingly, organisations are moving from an intuitive, ‘gut-feeling’ approach to more data-driven predictive modelling. Indeed, this movement has been witnessed across the insurance, marketing and even human resource industries.

Finally, with organisations now taking a portfolio view of risk, as described above, there is a growing effort to quantify risk correlations and the overall portfolio risk of the organisation.  Whilst such quantification still remains challenging, especially in risk related areas, such as operational and strategic risk, immense value can be added to the decision making process from insights that may simply provide a direction of the risk exposure.

Benchmarking & Sharing

CAS (2003) state that: “Organisations have become quite willing to share practises and efficiency gains with others with whom they are not direct competitors” (CAS, 2003).  Hence it is clear that the sharing of common tools, processes and ERM practices across industries and globally has also played a part in helping to drive and embed the ERM discipline. The internet and related technology, such as social media, has aided information sharing as well as an increased willingness among organisations to share risk practices via forums, conferences and professional bodies.  This has resulted in increased transparency in terms of effective risk practices that create value and are thus worthwhile.

Focusing on the Upside of Risk

Finally, ERM adoption has been influenced by an attitude change towards risk-taking amongst business leaders of the 21st century. CAS (2003) has also recognised this by highlighting that “there is a realisation that risk is not completely avoidable and, in fact, informed risk-taking is a means to competitive advantage” (CAS, 2003).  Hence the ERM actuary will seek to consider risk optimisation and not simply risk minimisation. 

The world may arguably have become more uncertain, but there is evidence of this new posture towards risk taking. In the past, firms often took a defensive risk stance, simply focusing on the reduction, or even elimination, of risk via practices such as insurance. Whilst defensive risk mitigation strategies certainly play an important role in modern risk management strategies, organisations have begun to focus more on the opportunities that risk may present and how value can be created from it, by taking on risks where the organisation has a competitive advantage. A number of reasons have brought this change in attitude to the fore.

Firstly, as organisations have become more familiar with the risks to which they are exposed and have enhanced their capabilities in managing those risks over time, they have recognised their competitive advantage, such that those risk exposures have become a viable route to profit.

It is also now easier for organisations to actively seek out target risk exposures due to a more fluid market place and access to financial risk management products, such as the derivative products of forwards, futures, options and swaps. New financial products and markets also allow firms to effectively evaluate risk-return trade-offs and ensure that the benefits of certain risk strategies outweigh the costs.

Furthermore, risk may be sought out for diversification and hedging purposes in line with the desire to now view risks in a more holistic portfolio perspective. PWC (2015) surveyed over 1,000 business executives and found that the perspective of risk is changing from operational to strategic. Their study found that 31% of risk leaders are willing to accept financial risk, and 35% are willing to accept diversification and concentration of risk, both of which highlight the movement towards embracing appropriate risk-taking behaviour.

ERM & Value Creation

The theoretical value proposition of corporate risk management may seem intuitively obvious, but is however ambiguous and has historically been contested. For example, the Modigliani and Miller (1958) seminal contribution on the irrelevance of an organisation’s capital structure implies that in perfect capital markets, risk management activities also do not create value. Building on the work of Markowitz (1952), Sharpe (1964) created the Capital Asset Pricing Model (CAPM), which provides the theoretically appropriate required rate of return of an asset based on the additional systematic risk it contributed to the portfolio.

When pricing the risk of adding a new asset to the portfolio, Sharpe (1964) claimed that only systematic risk should be factored in, as idiosyncratic risk can be diversified away. To this extent, an important metric used in CAPM is ‘beta’. An organisation’s beta dictates the magnitude of asset volatility in relation to market movements. In Sharpe’s world of well-diversified portfolios, asset returns are fully determined by market fluctuations. The organisation can control their level of beta and thus manage the potency of market movements similar to the principal behind leverage. Hence, the CAPM asserts that well-diversified investors are able to hold portfolios that will have already eliminated the idiosyncratic specific risks of the firm, thus rendering risk management efforts irrelevant in terms of value creation.

However, of critical importance to the ERM actuary, there are various theoretical counter arguments that suggest risk management can and does indeed add value to the firm.

Firstly, as Grace et al. (2015) argue, the commercial environment has many market imperfections in terms of taxes (Modigliani and Miller, 1963), bankruptcy costs (Kraus and Litzenberger, 1973), external capital costs (Froot et al., 1993) and agency costs (Jensen and Meckling, 1976), which can be exploited allowing risk management to add value within the organisation. Pagach and Warr (2011) echoed this perspective by highlighting that attempts to reduce idiosyncratic risk is not a negative net present value project, due to the numerous market frictions and imperfections that exist within the corporate world.

Other arguments include recognition of the fact that well-diversified investors do not exist (Shimko, 2001) and that risk management enhances firm value by improving the value of expected cash flows (Shapiro and Titman, 1998; Nocco and Stulz, 2006). Various studies have also statistically shown that risk management appears to be adding value in the presence of these market imperfections (e.g., Smith and Stulz, 1985; MacKay and Moeller, 2007).

I now discuss the various rationales for value creation from ERM engagement, in turn below.

Optimising Risk & Return

As previously emphasised, risk management is no longer solely concerned with minimising downside risk and the ERM actuary's focus will shift as a result.

Organisations are now challenged to view risk as an opportunity by ensuring they only take on risks where they have a competitive advantage and also by actively seeking risk exposures that may lead to valuable upsides. Reverting to the basic premise that it is not possible to yield a return without bearing some degree of uncertainty, it is clear that risk is, quite simply, an unavoidable part of doing business. Risk management practises, therefore, do not simply attempt to mitigate risk exposures, but rather, they should strive to exploit opportunities and thus optimise the risk-adjusted return through managing a degree of risk that is within a pre-determined risk tolerance.

Knight and Petty (2000) highlight this point by contesting that the development of a risk policy should be a dynamic process, which handles risks innovatively and exposes opportunities for value growth. Best practice ERM dictates that risk management processes become ingrained in a firm’s strategic planning, and therefore the ERM decision making process starts with the identification of current risk exposures as well as potential risks that could be taken, rather than acknowledging them as an afterthought or dealing with them as they arise. This approach creates a more efficient planning process that leads to a more optimal distribution of the limited capital for investment.

It is, therefore, generally recognised that ERM attempts to create shareholder value by allowing firms to achieve a more optimised risk-return trade-off.  Meulbroek (2002) shares this view and argues, “The goal of risk management is not to minimize the total risk faced by a firm per se, but to choose the optimal level of risk to maximize shareholder value”.  Adopting an integrated framework approach to managing risk aids in achieving this goal.

Risk Aggregation: A Holistic Approach to Risk Management

From previous discussions, it is clear that many consider fragmented risk management no longer acceptable, considering the increasingly strong intertwining connections between risks and the growing complexities of the business world.  To achieve a comprehensive appraisal of all these interdependencies and manage risk in an efficient and effective manner, a holistic approach is required. The problems and frailties that surround the silo-based approach have served as a significant driving force in the expansion and development of ERM.

Hence a key aspect of ERM (and difference from the TRM approach) relevant to the ERM actuary, is that the firm’s major risks, from all sources, are aggregated together in a ‘portfolio’ of risks. Rosenberg and Schuermann (2006), for example, use a copula-based method to show that a firm’s total amount of risk differs from the sum of the enterprise’s individual risks. Nocco and Stulz (2006) contend that an evaluation of risk and return at the project level does not allow for optimisation at the corporate level, as risk diversification and correlations are ignored, thus leading to sub-optimal decision making. As a key component of ERM is the examination of the risk interactions and their aggregation, it is therefore posited that ERM improves internal decision making and hence ultimately contributes to firm value through more efficient capital allocation (Myers and Read, 2001). Furthermore Nocco and Stulz (2006) argue that ERM can lead to a reduction in the probability of large detrimental cash flow shortfalls (which are economically burdensome to the firm in terms of future growth implications), costly capital acquisition and relinquishing of profitable investments. In support of the argument for a holistic risk management approach, McShane et al. (2011) emphasised the benefits of ERM, attesting that hedging residual risk (rather than independent risks) maximises value by allowing the organisation to benefit from a risk diversification effect or recognition of natural risk hedges. Thus, only the remaining risk needs to be addressed, which should be less onerous than mitigating each risk independently. Markowitz (1952) recognised that an investor can reduce portfolio risk simply by holding combinations of instruments, which are not perfectly positively correlated. As such, ERM assumes that risks are not 100% correlated. Hoyt and Liebenberg (2011) also recognise this key benefit in their discussion of how the integration of risks helps firms avoid duplication of risk management outlay.

Improved Board Decision Making

In addition, viewing the company’s risks as a portfolio should be beneficial to the firm, as it should improve both the senior management and the board’s ability to understand and oversee the enterprise’s overall level of risk exposure (Beasley et al., 2005).

This increased need for the board to truly understand the organisation’s risk position has been particularly prevalent since the 2007-2008 global financial crisis, when many commentators blamed the over-use of complex financial models and derivative products for an unhealthy gap between risks undertaken and the board’s understanding of those risks. For example, in 2008, the American International Group (AIG) received a bailout of US$85 billion primarily as a result of its misuse of financial tools known as collateralized debt obligations (CDOs). It is clear that the board of AIG did not have a full comprehension of the true AIG risk exposure resulting from their CDO endeavours.

Stakeholders, in the pursuit of maximising their wealth for a given level of risk, have strong incentives to ensure that the board provides effective risk oversight by practising risk management in a value-additive and transparent manner.  Accurately plotting the organisation’s position on the risk/return curve requires knowledge of risk exposures on an enterprise-wide scale.  An improvement in the understanding and transparency of the firm’s aggregate level of risk, right up to the board level, should allow for an efficient level of strategic decision making in line with an optimal risk-taking strategy (Chapman, 2011). Hoyt and Liebenberg (2011) posit that this improved understanding, at board level, enhances resource allocation, capital efficiency and equity return.

The ERM Actuary: Focused on Creating a Competitive Advantage

It should also be noted that ERM goes beyond focusing on just risk avoidance activities to also recognise the value of embracing risks that provide a strategic competitive advantage. This is partly in recognition of the fact that the desire for risk avoidance may actually increase the volatility and fragility of financial markets as a whole via certain investment products (Jacobs, 2004).

Key considerations and imperatives under the ERM framework include a focus on the organisation’s ability to respond appropriately, via redeployment of resources, in the face of changing business environments. This more offensive approach towards agility, pro-active risk seeking and attempting to optimise risks, rather than simply reducing or mitigating them, enables a more favourable risk profile to be achieved; such that new business opportunities can be effectively developed and executed as the competitive landscape alters (e.g., from technological innovations).

Other Noted Benefits

Other value additive benefits of ERM include reduced cost of capital via improved ratings from credit rating agencies (Samanta et al., 2004; Hoyt and Liebenberg, 2011), improved insights into different types of risk (Meulbroek, 2002), enhanced capacity to inform outsiders such as regulators and investors of the firm’s risk profile (Hoyt and Liebenberg (2011), better capital structure decision making (Graham and Rogers, 2002) and the avoidance of large swings in the staff required (thus limiting recruitment and redundancy costs), which helps reduce the amount of necessary risk capital (Sweeting, 2011).

Finally, various ERM consulting practices have also reported that ERM has led to more accurate financial reporting, an improved perception of the organisation from a plethora of stakeholders, a better marketplace presence and, in the case of public service organisations, enhanced political and community support.

The ERM Actuary: Summary

In summary, it is clear that the practice of risk management is in the midst of a paradigm shift, as the global commercial business landscape continues to rapidly evolve. ERM is a maturing discipline that aims to help organisations proactively and effectively deal with ever-changing risk exposures and resulting strategic planning requirements. The evidence is compelling that the implementation of ERM has the potential to create tangible value amongst organisations in general, but particularly amongst those that are more complex in nature or operate in a strong knowledge-based stakeholder focused environment.

The manner in which organisations manage risk has evolved significantly over the last two decades and the holistic integrated approach, known as Enterprise Risk Management, has gained significant traction throughout the corporate world.

Firms that advance ERM from a value-based perspective and focus on embedding risk culture across the organisation, encourage employees to take a more risk aware approach and align ERM with their strategic goals are realising significant value, particularly in the long-term.

As the world increases in complexity and inter-related systems require greater levels of understanding and clear communication, the ERM actuary is likely to be in strong demand.

References

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Beasley, M., Branson, B. & Pagach, D., 2015. An Analysis of the Maturity and Strategic Impact of Investments in ERM. Journal of Accounting and Public Policy, 34(3), pp.219–243.

Beasley, M., Branson, B., & Hancock, B., 2015a. 2015 Report on the Current State of Enterprise Risk Oversight: Update of Trend and Opportunities. ERM Initiative at North Carolina State University.

Beasley, M., Branson, B., & Hancock, B., 2015c. Global State of Enterprise Risk Management Oversight: Analysis of the Challanges and Opportunities for Improvement. ERM Initiative at North Carolina State University.

Beasley, M., Branson, B. & Hancock, B., 2010. Report on the Current State of Enterprise Risk Oversight. The ERM Initiative at North Carolina State University. Available at: http://riskwide.com/wp-content/uploads/2014/06/ERM-Research-Study-2014.pdf.

Beasley, M. et al., 2006. Working Hand in Hand: Balanced Scorecards and Enterprise Risk Management. Strategic Finance, 87(9), p.49.

Beasley, M., Pagach, D. & Warr, R., 2008. Information Conveyed in Hiring Announcements of Senior Executives Overseeing Enterprise-Wide Risk Management Processes. Journal of Accounting, Auditing & Finance, 23(3), pp.311–332.

Beasley, M.S., Clune, R. & Hermanson, D.R., 2005. Enterprise Risk Management: An Empirical Analysis of Factors Associated with the Extent of Implementation. Journal of Accounting and Public Policy, 24(6), pp.521–531.

Bernstein, P.L., 1998. Against the Gods: The Remarkable Story of Risk. John Wiley & Sons Inc, United States of America.


Black, F. & Scholes, M., 1973. The Pricing of Options and Corporate Liabilities. The Journal of Political Economy, 81(3), pp.637–654.

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D’Arcy, S.P. & Brogan, J.C., 2001. Enterprise Risk Management. Journal of Risk Management of Korea, 12(1), pp.207–228.

Deloitte, 2013. The Value Killers Revisited - A Risk Management Study.

Doherty, N., 2000. Integrated Risk Management: Techniques and Strategies for Managing Corporate Risk, McGraw Hill Professional.


Farrell, M. & Gallagher, R., 2015. The Valuation Implications of Enterprise Risk Management Maturity. The Journal of Risk and Insurance, 82(3), pp.625–657.

Floreani, A., 2012. Risk Measures and Capital Requirements: A Critique of the Solvency II Approach. The Geneva Papers on Risk and Insurance - Issues and Practice, 38(2), pp.189–212.

Froot, K.A., Scharfstein, D.S. & Stein, J.C., 1993. Risk Management: Coordinating Corporate Investment and Financing Policies. The Journal of Finance, 48(5), pp.1629–1658.

Grace, M.F. et al., 2015. The Value of Investing in Enterprise Risk Management. The Journal of Risk and Insurance, 82(2), pp.289–316.

Graham, J.R. & Rogers, D.A., 2002. Do Firms Hedge in Response to Tax Incentives? The Journal of Finance, 57(2), pp.815–839.

Hannoun, H., 2010. The Basel III Capital Framework: A Decisive Breakthrough. BIS, Hong Kong. Available at: https://www.bis.org/speeches/sp101125a.pdf.

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insurance actuary
Future of The Profession, Insurtech

6 Reasons Why An Actuary Should Choose A Career In Insurance

“Should I become an insurance actuary?”

“Isn’t insurance boring?”
“Is insurance a good industry to work in longer term?”
Source: Occasional Aspiring Actuaries.

Every year I give a number of talks to students interested in a career in Actuarial Science.

At times I’ve been asked questions, similar to the above, regarding the insurance industry.

Contrary to popular belief, I happen to think that insurance is a great industry for people to work in.

Insurance is not perfect, but it does provide a valuable societal value and insurance is continuing to embed exciting technology solutions and improve as a service offering. And the insurance actuary is likely to play a key role in the insurance world for the foreseeable future. 

I’ve summarised most of the points I usually touch on, in the infographic below.

insurance actuary

Would you agree? Do you have anything else to add?

Help me to sell a career in insurance to the next generation of actuaries!

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data science - future of actuarial profession
Data Science, Insurtech, Learning, Misc

6 Thoughts on Future Strategies for the Actuarial Profession

I was recently contacted by another actuary – an IFoA council member – asking for my thoughts on strategies the IFoA should think about for the future.

I thought I’d share my response on here, and would love to hear what other actuaries think:

“…. Like many other professions, I truly believe that our profession is facing a critical time given the pace of change.

So what can the actuarial profession do to remain relevant well into the future? Here are a few of my personal thoughts:

1. Perpetual Learning

Going forward, I think, there needs to be a greater focus on “on demand learning/upskilling” and accessibility to resources as and when needed for learning on the job. Eg understanding and applying artificial intelligence, machine learning, blockchain, IoT, wearables, dealing with new emerging risks. The list goes on and is constantly evolving. I think the profession can and should continue to play a role in continuous ongoing learning after qualification. It increasingly seems that qualification is only the beginning and we need to be constantly learning and evolving as actuaries, to avoid getting left behind. Learning to learn and being flexible and having an ability to reinvent oneself are critical skills for the future. I believe the profession can help us stay nimble as well as fostering a culture of continuous ongoing lifelong learning. Otherwise, I believe, others (eg “data scientists”) that often have the more flexible mindset may continue to make inroads into traditional actuarial areas (eg pricing).

2. Innovation & Creativity

I would like to see a greater focus on innovation and creativity as well as more training in these areas. These skills are becoming increasingly important. The insurance world is now beginning to change and “catch up” with other sectors, in terms of technology adoption. We should be aiming to claim a slice of the InsurTech pie and not just seen as the regulator checkbox guys or technicians. Let’s learn to bring more of an agile mindset to our work. I think it will be increasingly important to be able to think like an entrepreneur. Building, testing, iterating. Let’s continually learn to take initiative and find unique solutions to the new emerging business problems.

3. Data Science

Data science, especially machine learning, is becoming more and more important as a tool for actuarial work. It’s great to see the profession doing a lot in this space. Can the actuarial qualification act as a more general route into a career as a data scientist? I think it possibly can. We have a unique position in this space due to our code of ethics and highly regarded professional qualification/recognised credentials. Hence, we have a unique advantage over many others claiming to be data scientists (given anyone can now say they are a data scientist!). The problem though is the opportunity cost of learning irrelevant material (for much of data science) to get the actuarial credential.

4. Professional Actuarial Judgement & Business Acumen

Related to the above – there’s a lot of talk about automation and people losing their jobs to robots. Whilst there is a certain amount of hype around this, I do believe automation will change the nature of many jobs in the future. Digital and automation is the future and we need to be part of that. Let’s, therefore, ensure that we continue to add value beyond the number crunching by having the skills to exercise professional judgment and business acumen whilst staying on top of developing trends.

5. Supply & Demand

I think the profession has a role to play here to help ensure this is managed carefully in different parts of the world. India, in particular, seems to be currently feeling the effects of an over-supply of new “aspiring actuaries” having difficulty getting on to the actuarial career ladder.

I believe we can collaborate more with other actuarial bodies to effectively build brand “actuary” (trusted advisors of risk). There will always be risk and especially today risk is everywhere and changing all the time. I would like to continue to see brand “actuary” as the trusted advisors in financial risk, but with more creativity and innovation. I believe one of the key positives of our profession is that it attracts really bright people. We should focus on continuing to make the profession attractive to the brightest and best.

Our new IFoA President, John Taylor, has talked about “growing the membership,” so I think it will be interesting to see what direction this takes.

6. Innovative Research

A greater focus on truly innovative research. We live in exponentially changing times. Let’s be at the forefront of change and bring a creative, innovative mindset to our work underpinned by relevant cutting-edge research.”

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actuaries and blockchain
Insurtech

Actuaries & Blockchain

You’ve heard of blockchain, right?

Of course you have! Blockchain appears to be everywhere these days and is receiving an increasing amount of attention in various media channels.

Thanks, partly, to the meteoric rise and partial fall of the volatile bitcoin crypto currency, which utilises blockchain as its underlying technology, blockchain has risen in prominence over the last couple of years. In many circles, it is now being heralded as another new technology that promises to change the world as we know it.

But promises are one thing, and reality is another. Will the current hype of blockchain really significantly change the financial world as we know it? Or is it another example of hype that will be forgotten about as we move on to the next big thing? I don’t believe so. In my humble opinion, blockchain is here to stay and actuaries should be paying very close attention.

This article, directed at actuaries, will explain the basics of blockchain in very simple terms and we will then examine some UK/European-based use cases where blockchain is already being used or developed.

WHAT IS BLOCKCHAIN?

Blockchain is essentially a peer-to-peer data storage technology that aims to remove the need for intermediaries. The need for trusted third parties in transactions, often results in significant expense and time delays. But what exactly is this technology?

First the long-winded definition. Blockchain is described as:

a transparent replicated, secure, decentralised, incorruptible, immutable (still debatable), irrefutable, distributed ledger of economic transactions in a database utilising “blocks” that are time-stamped using cryptographic encryption.

Wow – lots of big words! Let’s take a big step back and try to keep things simple.

First, I want you to imagine the favourite tool of the junior actuary. Yes, the humble spreadsheet that we all know and love (or hate if you are a data scientist!). Well, it turns out that blockchain is kind of like an Excel spreadsheet. They share a lot in common. For example:

  1. 1
    Spreadsheet rows are analogous to blockchain blocks. A block is essentially a collection of data. In a similar fashion to a ledger spreadsheet having rows added, a blockchain has blocks of information added. It views each block as a legally valid record of a transaction and together they form a chain of blocks (i.e. a blockchain).
  2. 2
    Shared access (but with no central owner). In the same way a single Google spreadsheet can be shared and seen amongst all users, a blockchain is transparently distributed across a diffuse network of personal computers or servers (known as nodes) in a decentralised fashion. Any changes made will occur instantaneously within the entire network. Furthermore, this decentralised sharing also results in the blockchain being immutable thanks largely to consensus driven collaboration. The decentralised aspect of blockchain technology also means that transactions cannot be lost or manipulated.
  3. 3
    Locked spreadsheet cells = Secure blockchain. In a similar fashion to spreadsheet cells or rows being locked to avoid changes, the blockchain does not allow the editing of any information that is already there. Any changes must be made via the addition of a new block of information. This is important since it means that all historic changes are transparently recorded providing an audit trail that is available to the blockchain members.
  4. 4
    Password protection = blockchain hashing. Spreadsheets can be somewhat protected via a password system. In contrast, blockchains utilise cryptography and hashing to enhance security. Hashing involves taking an input value and then applying a mathematical algorithm to produce a cryptographic output of a fixed length. This hashing process enhances the security of the data as individuals attempting to reverse engineer cannot deduce the original input value.

So what does this all mean? Well, the advocates (of which there are many) of blockchain technology point to its ability to solve the issue of ‘trust’ across networks. Complete strangers are supposedly able to complete transactions with minimal ‘middle-man’ interaction (and hence friction payments) and without the risk of counterparty default.

BLOCKCHAIN INDUSTRY IMPACT

Blockchain has been touted as having the potential to change many industries. The promised lands of change range from banking to finance to security to healthcare to marketing and even entertainment. As I said, there are some big promises being made with blockchain!

For actuaries, the main industry of interest is insurance. On the face of it, blockchain would appear to make enormous sense to use within the insurance world. Operational inefficiencies abound in insurance as manual claims handling and other frictions permeate throughout the chain. Insurance is built on a foundation of trust and given this foundation seems to have been somewhat shaken over the last few decades, many now view blockchain (also known as “the internet of trust”) potentially coming to the partial rescue.

SMART CONTRACTS

Perhaps the main use of blockchain within insurance is the enabling of event-triggered smart contracts. Under such a contract, claims processing could be automated such that the policyholder does not have to make a claim and the insurer does not have to administer the claim. Verified inputs that are clear, objective and unambiguous (such as that from death registries, or official weather reports for example) would be recorded on the blockchain and if the conditions for paying out on the smart contract are met then the smart contract automatically pays out. Plain, simple, automated, cost-reducing and with the potential to largely counteract fraud and enhance customer satisfaction – what’s not to like about this grandiose blockchain theory?

To provide a tangible feel to the blockchain smart contract let’s now examine some UK/European-based insurance blockchain use cases that are currently in existence. Firstly, we will look at a marine blockchain insurance solution that has been developed by Ernst & Young (EY) in the UK along with Guardtime, A.P. Møller-Maersk, Microsoft, Willis Towers Watson, XL Catlin, MS Amlin and ACORD, and is now in commercial use. Secondly, we will discuss French multinational insurer, AXA’s recently launched flight delay insurance that runs off a blockchain platform. Thirdly, we examine a product being developed and built by the European-based Etherisc community.

Marine Insurance

Marine insurance covers a ship’s vessel, its container boxes and cargo as well as the various liabilities (e.g. pollution) that ship owners may incur. Marine insurance is notoriously lacking in transparency and expediency due to numerous intermediaries that are typically involved in the inefficient and costly purchase of cover. EY, Guardtime and several other insurance industry leaders recently launched “Insurwave”, described as the world’s first blockchain solution for marine insurance. The blockchain solution was designed to remove much of the inefficiencies the industry has historically experienced. The proof of concept was deemed to be a success and in May 2018 the product was commercially released.

The Insurwave platform uses distributed ledgers to store additional data points allowing for more sophisticated underwriting as well as smart technology contracts to reduce costs throughout the chain. According to the EY website the “technology will support more than half a million automated ledger transactions and help manage risk for more than 1,000 commercial vessels in the first year.” London-based EY global insurance leader, Shaun Crawford, is leading the project and had the following to say:

The platform allows multinational companies to share vital data sets relating to the assets that are being shipping around the world with brokers, insurers and reinsurers in a secure, private network. InsurWave brings much needed technology to the industry and removes the need to maintain a paper trail while giving everyone in the value chain ‘a single version of the truth’ on a near real-time basis. If data on the ships changes, for example, or there are losses, everyone in the chain is notified.

When I recently spoke with Shaun he mentioned that they are now planning to build out their offering in both China and Singapore. More proof indeed that blockchain is here to stay.

Flight Delay Insurance

In 2017, French insurer, AXA, released a blockchain-based insurance product called ‘Fizzy’ that utilises smart contracts to pay out on flights that are delayed for a period of more than 2 hours. Flight delays are tracked in real time through global air databases and get recorded as fact on the blockchain eventually resulting in an automated payout for the policyholders, without the need for a claim filing or additional paperwork.

Whilst the scale of this project is admittedly small, when one considers the number of daily delayed flights across the globe and the policyholder hassle factor involved in claiming for a flight delay, it isn’t difficult to imagine why this type of insurance will increasingly appeal to many travellers who value simplicity and convenience. I know from my own experience that claiming for a risk on something like this is typically cumbersome, time-consuming and frustrating and I can certainly see the appeal from a customer point of view. Interestingly, whilst the insurance company may save on administrative costs, they will also need to consider the additional costs they bear from paying out on 100% of eligible claims, as many previous non-claiming policyholders are given automated payouts.

Hurricane Protection

Etherisc is described as a decentralized platform built for the insurance industry and since 2016 they have been building and developing various decentralized insurance apps on the Ethereum blockchain.

An example product developed by the Etherisc community is their hurricane protection solution which aims to protect low-income individuals and small business owners from the damage caused by hurricanes. According to their website automatic claims are paid out if wind speeds are recorded within 30 miles of the individual’s home or business. Again one can see how the input which clearly and objectively defines the payout (in this case wind speed) can be recorded on a public blockchain resulting in automation, reduced overheads and quick service. In fact Hurricane Guard’s website compares the 9-12 month regular insurance payout period to their envisaged (the product is not yet licensed) payout period of 24 hours as well as pointing to a much reduced premium, complete transparency and zero deductible.

SUMMARY

Whilst blockchain is still very much in a developing stage, clearly it is already having an impact and could well be a technology that will rival the internet in terms of influence on business. Insurance companies seem particularly well-placed to benefit and it will be interesting to watch how things unfold over the next few years. Of course there are still many hurdles to overcome, including scaling the technology, regulation and obtaining consumer confidence.

Whatever your view on blockchain, I think it is safe to say that insurance is rapidly changing as we continue to enter the digital age where technology-based solutions increasingly permeate throughout businesses.

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