Businesses worldwide are facing new and significant risks due to the pandemic and its many ripple effects. At the same time, work-life has undergone drastic changes — many have had to shift to remote working overnight or find other inventive ways of getting the job done despite the current situation. In these distressing times, business leaders are dealing not only with significant change but also attempting to navigate an evolving risk landscape.
Reacting effectively to these changes and risks is absolutely essential, but it is difficult to know what the right reaction is, and many are reacting differently. Some have stayed calm, acting quickly and decisively, while others have failed to act, mishandled things or aggravated the situation by making bad choices. Why do some experienced leaders have this problem or react differently under stress, especially now?
There are multiple reasons for these differences, and, I’m happy to say, there are also ways to shift to more effectively handle risk and change — now and into the future.
Why leaders aren’t all on the same page
Decision-making is always somewhat difficult in that it inherently involves uncertainty. But the number of unknowns related to the pandemic means that leaders are experiencing uncertainty more than ever before. They have fewer details and evidence at their disposal to make decisions, and so leaders have to lean heavily on their individual experiences, knowledge and intuition.
Secondly, there’s the matter of time. Leaders are used to being able to evaluate options objectively in a step-based manner, selecting a final choice after good, organized analysis and feedback. Now, the pandemic is forcing leaders to make decisions quickly. They do not necessarily have time to check all the parameters beforehand.
Choices also are more complex for leaders, regardless of whether they have to happen at the local, regional or global levels. Choices can have consequences that are quite significant compared with normal circumstances. And although crisis leadership has always been a valuable skill, most business leaders simply are not prepared for the level of risk-taking and change management capability necessary to respond to the pandemic at a worldwide level, because the COVID-19 crisis is unlike anything most leaders have experienced.
Lastly, current risk management culture is largely defensive rather than opportunistic — that is to say, most business leaders don’t have the risk management function to drive a culture of resilience and agility. That generally means that leaders react more slowly and in a more limited way to crises.
Making more effective decisions during COVID-19 and beyond will require leaders to rethink their mental and logistical approach to operations. The first step is to surround yourself with others who have the skills necessary to help you make your choices. Because traditional hierarchical structures will not be self-assured, you must reach out to experts and informed, qualified professionals at every level. Well-rounded insights from a variety of sources will put you in a position to consider options from a broad perspective and to feel confident that you have considered many points of view or potential ramifications.
Leaders also need to commit to maintaining a long-term perspective, even if it means fixing decisions later when new information emerges or the situation changes. This is because the ultimate goal of crisis management isn’t just to get through the crisis — it’s to recover and thrive well into the future. Leaders have to understand how their choices influence the future path of the company and try to make decisions that offer the right balance of stability and flexibility.
Additionally, situations arising due to the pandemic can naturally present leaders with agonizing moral choices. Companies might have to choose between cutting wages for everyone or paying full salaries and keeping just a portion of their team, for instance. Sometimes crises mean that legislators relax regulations that would keep less scrupulous behaviors at bay — for example, dumping chemicals, skipping oversight hearings or approving a vaccine without sufficient testing. There are also good examples of leaders supporting the people during this difficult time to draw from, such as CEOs and executives giving up their salaries to redirect funds to their workers. But all leaders should strive to make ethical decisions that are data-driven, address the wellbeing of people and consider those who are most affected by the virus.
Finally, leaders need to embrace the digital future with a focus on building resilience and adjusting to change as quickly as possible. This might look quite different depending on what your company’s mission and industry is. But good examples can include setting up secure remote networks, focusing on business continuity, and even learning to interact virtually with clients for conducting business. As you figure out how technology can serve you to improve both general operations and crisis management, remember that it’s crucial for employees to be able to disconnect for their happiness and health.
Leaders can approach business in a wide variety of ways, which is part of what makes business so exciting. Even so, few leaders are well-positioned to make decisions during and after the pandemic smoothly, as challenges like lack of experience and the sheer complexity of choices create unstable ground.
The bulk of us will need to take deliberate steps to improve the odds that our decision-making will be better. By reaching out to skilled people, maintaining a long-term perspective, dedicating yourself to ethical action, and using technology in innovative ways, you can make judgments to be proud of through this crisis and for years to come.
Back in 2001, famed technologist and futurist Ray Kurzweil boldly proclaimed that the human rate of progress was doubling. He added that, by the time the 21st century ends, the progress would feel like 20,000 years’ worth of transition instead of 100.
At the time, Kurzweil’s statement sounded a bit dubious. But with how rapidly technology has transformed over the last two decades, it now seems that the world’s ability to change quickly was drastically underestimated.
We live in an age defined by acceleration, and this incredible pace of change has exceeded many industries’ capacity to handle it. Changes that once took an entire generation for people to adapt to now takes 10 years. The possibilities of this rapidly changing landscape are endless, and so is the risk that comes with it.
The Far Reaches of Risk
It should come as no surprise that risk evolves alongside technology transformation. Advancement is a double-edged sword. It can simultaneously create a greater level of safety for the status quo and change the very nature of risk, forcing insurers to build new coverage solutions to address previously unforeseen concerns.
For instance, autonomous vehicles might be safer drivers than humans, but they’re also vulnerable to cyberattacks and malware. In many cases, driverless cars are blurring the lines of established risk categories. For proof, just take a look at the sharing economy. It’s less than a decade old, yet it’s raised major questions in terms of how coverage works. Are Uber or Lyft vehicles classified as work or personal? And does the coverage shift throughout the day as drivers turn their ride-sharing service on and off? Insurance companies have to find answers for these types of problems on a daily basis.
It’s an understandably complex and intimidating concept for many insurance leaders. However, while progress may be rapid, it’s not entirely unpredictable. The future can be bright for those who remain engaged with the changing landscape of risk. Here’s what those leaders can expect:
1. Humans will gain a deeper understanding of risk.
While technology’s race toward the future provides ample opportunity for confusion, it also provides the tools to parse that confusion and come to a better understanding of risk. Telematics, machine learning, data analytics and more all give insurers much greater insight into how risk touches every aspect of life.
Commercial auto insurers are testing the waters of telematics to explore how they can be applied to evaluate individual driving behaviors. Companies can examine individual driving habits to see how those routines inform the kinds of services and discounts they can offer customers. Instances like these are only going to become more common. This type of granular data sharing will have a direct impact on how coverage is constructed and provided in the future.
2. The way humans and technology relate to risk will change.
As automation continues to be integrated into daily life, coverage will have to properly account for and balance the effect computers and humans each have on rates.
Amazon has more than 100,000 automated and robotic systems integrated into its operations working with human employees to maintain efficiency. The online retailer has almost certainly had to consider how to provide coverage for its employees while they work in tandem with heavy machinery, something companies in similar situations will also have to consider.
Regulation for this is still being crafted. Insurers will need to make sure they continue to stay up-to-date on how and when machines can take over from humans and how that will affect risk.
3. Customer service will look a little different.
Thanks to the Internet of Things, insurers will be able to learn about incidents in real time and process claims before a policyholder even gets involved. These instantaneous notifications are clearly useful for insurance companies, but, used correctly, they can also be a major selling point for consumers.
Machine learning could have a similar impact on customer service. It can be used to pinpoint a highly customized plan for every individual without the customer having to do most of the groundwork.
This age of acceleration is intimidating, and it certainly shows no signs of slowing down. Leadership, however, should look at all this innovation as an opportunity, not a threat. Insurers can leverage tech to improve the customer experience from quote to claim, and, as technology advances, so will the tools that help insurers understand risk.
There’s no denying that infrastructure, demographics and risk are all changing at breakneck speed. To keep up, insurers must not just follow change — they need to grab it by its horns and embrace the new before it becomes old hat.
If you’re like me, you can readily define those terms—or at least give examples. A Treasury note indexed to inflation? Conservative. Stock in a small company in an emerging market? Aggressive.
But what makes an insurance company’s overall portfolio conservative or aggressive? And however you describe your or your organization’s risk tolerance, how do you know your portfolio is in line with your perception of risk?
If those questions are harder to answer, they also merit more thought than the relative riskiness of any single security. Exploring portfolio-level risk and risk tolerance in ways that go well beyond labels should help your investment team come to a shared view about how much risk you are—and should be—taking in your portfolio.
Define investment risk
While it is imperative for you to understand and adhere to regulatory risk definitions and constraints, it is equally important for you to clearly define investment risks and your own risk tolerance. To explore conservatism and aggressiveness through the lens of an insurance CIO, let’s consider a hypothetical insurance company—call it Insure-a-Co.
Insure-a-Co is a small/mid-sized property and casualty insurer that invests core portfolio and surplus assets in search of income and a stated return target. Like most of Vanguard’s insurance clients, the company’s chief investment officer describes her approach as conservative.
Naturally, Insure-a-Co faces liquidity needs dictated by claims and operational expenses. Risk-based capital regulations also come into play. Liquidity and regulatory concerns help to explain why Insure-a-Co historically has favored individual U.S. government bonds for safety, as well as individual municipal and investment-grade industrial and financial corporate bonds. That said, because of historically low yields and its fairly high return target, the insurer is considering owning more equities.
Risk is situational, not absolute
A central fact about risk is that it isn’t absolute. Rather it’s relative, or situational. A suitable level of risk for Insure-a-Co, given its operational needs, underwriting and investment objectives, and state regulatory influences, may be irresponsibly excessive, or inadequate, for another insurer.
Important business-line differences might include the extent to which a P&C insurer’s book of business concentrates on lower-risk policies, such as homeowners’ coverage in regions where natural disasters are rare, or higher-risk policies, such as auto coverage for operators with poor driving records. The extent of any reinsurance may also affect judgments about investment risk.
Volatility is an incomplete risk measure
Certainly, Insure-a-Co executives go beyond labeling themselves and their portfolios as “conservative” or “aggressive.” They often distill investment risk as volatility—specifically, as the standard deviations of the total returns of their individual holdings and overall portfolio.
But even as the standard deviation of returns tries to neatly summarize volatility, it may obscure crucial factors that contribute to performance swings. These include market risk, concentration risk, manager risk and interest-rate risk—which is especially important for Insure-a-Co, given its large fixed-income exposure. Other significant risks may be only loosely related to volatility. Inflation risk and shortfall risk are examples.
Complicating life for Insure-a-Co is the fact that seeking to minimize one type of risk may raise other risks. For example, market risk and shortfall risk are more or less inversely related, so taking less of one necessarily means taking more of the other. For Insure-a-Co, holding more equities raises market risk and boosts risk-based capital requirements, but holding fewer equities raises the risk of not meeting its return target.
All other factors being equal, we believe a better-diversified portfolio is a more conservative portfolio. As such, we’d likely suggest that a real-world Insure-a-Co consider venturing beyond a collection of individual U.S. government, municipal and corporate bonds. While such a portfolio may be perceived as conservative, it may leave an insurer exposed to substantial inflation or shortfall risk—hazards that may be limited by more diversified exposure to bonds of various maturities, sectors and credit qualities, as well as professionally managed, diversified equity exposures. International holdings may also be appropriate.
What to do?
At this point, you may be wondering how Insure-a-Co can possibly calibrate its portfolio for risk. The multi-dimensional and changing nature of risk obviously renders inadequate a decision to seek “conservative” or “aggressive” investments and means it is a mistake to rely on volatility as a standalone risk proxy.
However, there are steps an insurer can and should take:
Create clear, measurable, appropriate goals. To zero in on goals, start with a keen focus on your investment policy statement.
Develop a suitable asset allocation. We believe in balance across asset classes, within the parameters of insurance regulation, and diversification within asset classes.
Minimize the cost of investing. In our experience, cost is one of the biggest drivers of portfolio performance.
Maintain a disciplined investment approach. Even sophisticated institutional investors can change course at the wrong times, allowing market or economic changes to spur misguided investment changes.
Labeling an investment or your risk tolerance as conservative, aggressive or something in between means little to nothing if your risk tolerance and the risks of your portfolio are misaligned.
All investing is subject to risk, including the possible loss of the money you invest.
Investments in bond funds are subject to the risk that an issuer will fail to make payments on time and that bond prices will decline because of rising interest rates or negative perceptions of an issuer’s ability to make payments.
International investing is subject to additional risks, including the possibility that returns will be hurt by a decline in the value of foreign currencies or by unfavorable developments in a particular country or region. Diversification does not ensure a profit or protect against a loss.
Model risk management (MRM) continues its rapid growth in the insurance sector. More insurers are adopting MRM programs and are looking to increase the efficiency and effectiveness of existing programs.
Developing and using an effective MRM system will promote better MRM performance. A basic MRM system should provide a platform for managing MRM activities, in particular tracking and managing validations. As insurers accumulate information about their models through scoring and validation processes, we believe that they can enhance their systems to gain beneficial insight across their model inventory, especially commonality of components and interactions between models.
Based on recent client work and recent industry surveys, we share below some thoughts on the key characteristics of an effective base platform, cross-inventory opportunities, and how risk managers can enhance MRM processes and systems to take advantage of these opportunities.
Basic characteristics of an MRM system
An essential starting point for insurers initiating an MRM program is to develop an inventory of their models. Because MRM programs typically encompass all of an insurer’s models (not just actuarial or risk or financial ones), the inventory can be quite large. A survey we conducted early last year indicated that more than half of respondents had more than 150 models in their inventory; a quarter had more than 450. Another survey we conducted later in the year found that MRM systems’ primary task at all insurers is to catalogue all these models.
Once catalogued, an obvious next step is to populate the system with information that helps manage the MRM process. Typically, we see the following functionality in effective systems:
1. Model documentation repository.
Model documentation is the starting point to conducting a validation. Providing access to that documentation is important for validation and continuing risk management of the model. Sometimes (typically for older models undergoing their first validation), comprehensive documentation is not available and needs to be developed. Sometimes validations point out the need for documentation to improve. Keeping track of the need to update validation either because it is inadequate or because the model has changed also should be a part of the systems’ functionality (see item 4 below).
2. Model validation document repository.
This is the most self-evident functionality. Ninety percent of respondents in our survey who had a multifunction system (i.e., systems that do more than just catalogue models) reported that it was a repository for validation or model documentation. Also of importance, as programs mature, the system needs an appropriate mechanism to update the repository with documentation from subsequent validations (presumably without losing earlier versions).
Though not as universal as documentation storage, storing model risk scores and the details about the model that were used to develop its score is a feature present at about two-thirds of surveyed respondent companies. Model risk scores are often used to prioritize and sequence validations, so the first score is likely developed before the model is validated. Not surprisingly, validations often shed new light on a model and can often lead to a change in score. Also, we have found some insurers have begun to revisit their earlier scores and scoring algorithms, often placing greater emphasis on models that permanently affect cash flow. The system should be capable of tracking the development of the model’s risk score because it may change over time.
4. Tracking findings needing attention and due dates for that attention.
Managing hundreds of models is likely to lead to an extensive list of findings needing attention. Keeping track of these, the party responsible for addressing them and their expected completion dates seems a natural choice for an MRM system feature. As models are being built or undergoing significant modifications, the system can be used to keep track of their progress and validation needs.
5. Emailing notification to model owners and others of coming or missed tasks.
It seems a short step from tracking as we describe above to emailing notifications and follow-ups, as required. Our survey showed that only slightly more than half of the multifunction systems have this functionality.
As with any process, reporting on MRM activity, particularly the progress of validations and issue resolution, is a necessary antecedent to managing the process. About three-quarters of the respondents have this functionality built into their system. Though only a few have developed this as a real-time reporting dashboard, the rest are working on this or planning to do so.
Cross-inventory commonalities and connections
Recognizing that MRM is still a relatively new program at many insurers, early emphasis has been on developing a system that supports initial validation efforts. However, as programs mature and systems’ basic functionality has been established, insurers should consider enhancements that could increase the overall value of their MRM program. We believe these enhancement opportunities come from better using the information in the system. In particular, they come from working across the inventory rather than one model at a time.
Different models are likely to have many assumptions in common. The system could compare assumptions across models in the inventory. If two models use different values for the same assumption, for example different values for future interest rates, it would be instructive to investigate the sources and implications of these differences. Potentially, differences are not appropriate and, if not corrected, could cause increased risk across the model inventory. A single-source model for this assumption could apply to all cases, thus reducing overall modeling costs.
Different models frequently use common parts. For example, both stress testing and ALM models may use common cash flow projection engines. Although both models should undergo their own validations, some elements of the work can be reused. In particular, with proper safeguards, multiple replication of the same calculation algorithms would be unnecessary. Often, the replication element of a validation is one of the most resource-intensive and costly aspects of the work, so avoiding duplication here could meaningfully improve efficiency.
Few if any models exist completely on their own, isolated from others in the inventory. Typically, models are fed some input from upstream models and often send some output downstream to other models. This web of connectivity can be hard to visualize, but the raw material for doing so could be available from the MRM system. Typically, systems will need some enhancement to allow insurers to mine this material, however.
Enhancing the system to enable cross-inventory gains
The next significant step in MRM’s development can come from a holistic look at the whole model inventory. Some process and system enhancements that can enable cross-inventory perspective include:
1. Model documentations standards.
Most insurers have developed a playbook or template that they expect validators to follow in conducting validations and completing validation documentation. It is not often though that we find the same attention to standards in documenting models. Standardization can benefit both the model documenters and MRM cross-inventory analysis.
2. Terminology standards.
Because many different model owners and users have developed models independent of each other over several years, it’s not surprising to encounter inconsistent terminology. Different terms often describe the same thing, and sometimes the same term describes something else. As the MRM system becomes more densely populated, a thorough review can identify inconsistencies and enable greater standardization.
3. Upstream and downstream precision.
Many validation report guidelines (and presumably good model documentation guidelines) require identification in input and output of upstream and downstream models.
It would seem a modest step to require that these identified models are cross-referenced to their place in the inventory, presumably using the same model number identification tag.
Insurers should bring their MRM systems up to baseline capabilities by enabling the functionalities we describe above.
As validations and model risk management activities populate the MRM system, insurers should use that information to standardize model documentation formats and develop consistent terminology. Model and validation documentation should reference upstream and downstream models using the system’s identifiers.
Insurers can then mine information contained in their MRM system to:
Ensure consistency where required,
Eliminate duplicative validation tasks and,
Map their model web, eliminating unused models, improving models that need updating and carefully nurturing and managing the models that are of greatest value to the organization’s success.
In the opening segment of this series on complexity, I discussed the three network graphs that have emerged in the risk markets and which business models embody them. For quick reference:
In the second segment, I discussed the emergence of peer-to-peer insurance, which will accomplish the three core functions of the risk markets that currently exist in a “black market” unformalized state by using distributed managerial methods, which are:
Escrow of funds for a defined purpose; and
Management of reallocation of escrowed funds.
In the third segment, on distributed ledger technology, I looked at how it can be configured as a cohesive platform that would embody all three network graphs. I discussed how the roles of individual peers, along with carriers and agents, can work together to formalize the P2P methods in the risk markets. For a quick reference:
In this final segment, I will look at the current balance of the market share of each graph type in the risk markets, how the balance may change and what the new equilibrium state might look like in the risk markets.
Before doing that, I would like discuss an important idea that emanates from the blockchain and cryptocurrency communities: the idea that there could be “one ledger to rule them all,” or, asked another way, “Could a single ledger be an all-encompassing ledger, accounting for all value?” The simple answer here is “no.”
No single ledger, technology or network will ever be all-encompassing. That would be silly, as it would reintroduce the systemic weakness inherent in centralized system structures, namely the risk that by taking out a single central node (or ledger, in this case), the whole system could collapse.
Just as was realized in the blockchain and cryptocurrency communities, the idea of a “risk ledger to rule them all” is not a desired structure; in the risk markets, a single distributed risk ledger to account for all funds escrowed against all risk types is not a desired structure. Because of the nature of risk and the diverse set of risk exposures in the world, there will need to be a diverse set of risk ledgers. We may see something materialize that looks like the following as an example of four distributed risk ledgers, each for a specific category of risk exposure.
Hold on to that thought for now….
I would like to again reference some of the work done by the Ripple team and their thought leadership toward a solution to address the concern of “one risk ledger to rule them all.” The Ripple team has introduced a protocol that will enable value to move in a cryptographically secure way between two or more distributed ledgers. It is called the Interledger Protocol, and more information can be found on their site here.
Using the Interledger Protocol, the Ripple team has articulated how various types of distributed ledgers, each engineered for a specific strength, can be networked together to create a term they have coined the “Internet of Value.” Without a single shred of doubt, it is a true statement that “finance is getting its internet,” and it is already here, albeit in a state of maturity similar to the internet circa the late 1990s. Unlike the slow pace of the internet’s growth, however, finance’s internet will not take as long to mature — mainly because it received an advantage from the preexistence of the internet itself and all that has been learned. Insurance and the risk markets of all the various financial services are the lowest-hanging fruit.
This might seem like a stretch in today’s environment, but it is not hard to imagine that by connecting many risk ledgers (each escrowing funds against a specific risk type) and using the methods outlined with Interledger protocol, that we will see the emergence of an internet of risk. Just like with the internet of value we see emerging today, the internet of risk will be made of many different distributed risk ledgers networked together.
I would define the internet of risk as a network of distributed risk ledger networks. The technical name for a “network of networks” in complexity science is a “multiplex.” Risk markets have been operating with an informal and non-digital multiplex structure for some time. Because each insurance company manages a risk ledger and because reinsurance companies function to connect insurance companies’ risk ledgers together, the reinsurance industry effectively embodies a decentralized network of insurance companies — and both graphs combine to embody a multiplex of risk ledgers.
In all likelihood, over the coming years we will observe the digitization of the existing multiplex of risk ledgers that is the risk market into a network of digitally connected distributed risk ledgers, with each individual risk ledger serving the specific needs of a specific risk exposure.
KarmaCoverage is intended to be this “multiplex of risk,” organizing the connections between the risk ledgers of all types of P2P risk sharing. And it aims toward the goal of insuring that, as the P2P segment of the risk market grows, it maintains a high degree of resilience, enabling society to transfer risk efficiently among individual peers, successfully addressing the various risk exposures of those peers. You would expect to ultimately see this play out and create an internet of P2P risk ledgers that looks something like this:
To be fair, it is not possible to know the ultimate structure (or graph) of this multiplex of risk. It will emerge by a process of self-assembly. It must employ distributed managerial methods to avoid reintroducing the fragility inherent with its centralized structure. That said, many portions of it can (and should) be centralized for efficiency purposes. Distributed systems have weaknesses, as well, one of which is the introduction of some degree of inefficiency. We would not want to act out that behavior where “if all you have is a hammer, everything looks like a nail.” The functions that should be centralized combine a make the business case for something like KarmaCoverage.
Now, let’s take a look at how this may have an impact on the existing balance of market share where each graph serves as a percentage of total risk. Using data on the currently formalized methods of total risk and by assigning a percentage to each graph in the risk markets, you find that the graphs settled at roughly these percentages:
P2P coverage: 0% (This does not account for all the risk transfer activity that occurs informally in the black market of P2P risk transfer.)
There are two factors to consider when thinking about how the equilibrium state of the risk markets will balance out in the information age. To answer this, first we need to consider market growth and look at how the size of the risk markets will grow as a result of formalizing the P2P black market activity. Second, we need to consider the market share split among the three graphs, given that P2P will no longer continue to be 0% of the formalized market.
Let’s look at Uber and the taxi market for a benchmark.
Uber CEO Travis Kalanick, speaking at the 2015 DLD conference in Munich, said the taxi market in San Francisco was about $140 million per year, while Uber’s revenues in San Francisco were running at $500 million per year and still growing at 200% per year. Ignoring the continued growth, these numbers indicate roughly a 350% growth in market size.
Approaching this question about the growth in market size from another angle, and after reviewing various sources, the global formalized taxi market size is roughly $20 billion in revenue per year, while Uber’s annual revenue is only about $5.5 billion. These numbers would indicate roughly a 25% growth in market size.
While this is a simple and quickly obtained benchmark, it would be easy to conclude that the process of formalizing the P2P segment of the risk markets will drive somewhere between 25% and 350% growth to the size of the risk markets. This would take the roughly $5 trillion in global annual premiums of the combined insurance and reinsurance industries and, after adding the P2P industry segment, bring the size of the risk markets to somewhere between $6.35 trillion (on the low side) and $17.5 trillion (on the high side).
Reality check: There is a big difference between risk and taxi rides! Taxi rides are more prone to growth in market demand because of economic activity and population growth than the risk markets are.
Risk, on the other hand, is more prone to shrinking demand because of improved mitigation of actual risk because of safer technology and other factors driving the reduction of risk. As one example, let’s look at auto risk as we make the transition into driverless cars, which stand to make a very significant dent in auto risk exposure. We are already seeing a 40% decrease in accident rates from mere “accident-less” cars equipped with accident-avoidance technologies.
Using these benchmarks (and my crystal ball), the fact that the frequency of small loss events is much higher than large and catastrophic loss events leads me to predict that the formalizing of P2P methods in the risk markets will result in the doubling of the size of the formalized risk market at some ambiguous point in the future. I will also assume that the ratio between insurance and reinsurance shown above does not change. This would end up with risk markets growing to nearly $10 trillion, with the market share being split among the three segments like this:
P2P coverage: 50%
Surely these assumptions and predictions are wrong, but this is more of an exercise in trend observation, not an attempt to actually predict the state of the risk markets at some specific future point.
There will be other drivers that will have an impact on the shifting balance. One easy-to-understand but powerful and potentially market-driven force would be consumers voluntarily choosing significantly higher deductibles. This trend is already in motion. One indication of this trend on home insurance policies is that in California, on policies covering more than a million dollars, the lowest deductible that is compliant with regulatory rules is for $10,000. While that example is imposed on the industry, here in Florida, we saw the industry self-impose an increase in deductibles from hurricane losses after the 2004-05 seasons — while, at the same time, many large carriers simply pulled out of the state, leaving a vacuum to be filled by newer, smaller Florida domestic carriers.
Using formalized P2P “networked self-insurance” methods, it is possible for consumers to achieve an average of $10,000 in coverage on an annual basis for less than $100 per month and to simultaneously fill the deductible gap all the way down to the first dollar of loss, fully addressing total risk exposure. That could easily lead to enabling consumers to request $10,000 deductibles on all their insurance policies, which would have a material impact on gross premiums.
On home and auto insurance losses, more than 90% of claims are less than $10,000. If the consumer behavior of requesting ever-higher deductibles on their traditional insurance policies occurs, it becomes easy to consider that premiums on traditional insurance may currently be at or near their historical high.
Obviously, this process of formalizing the P2P segment of the risk markets will face headwinds, but since I entered the industry with an eye on the intersection of risk markets and crowdfunding methods back in 2013, we have seen the number of P2P insurance companies grow from one to dozens all over the world. It seems like the moment for the formalization of P2P methods in the risk markets is here.
Because of the convergence of factors discussed in this series (and a few others), I believe we will see a Napster-, an Uber- or an AirBnB-type of service emerge for the risk markets in the coming years.
I have started a LinkedIn group for discussion on blockchain, complexity and P2P insurance. Feel free to join here.
The whole mini-series is available for download at KarmaCoverage.com.