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Actuaries Beware: Pricing Cyber Risk Is a Different Ballgame

Growth in the cyber insurance market has recently occurred at warp speed, with more than 60 companies writing in the U.S. alone and with market premiums amounting to approximately $2.5 billion annually. The impressive year-over-year growth is expected to continue into the foreseeable future, with a variety of estimates placing market premium between $7.5 billion and $20 billion by the end of 2020.

This impressive premium growth is because of several factors — perhaps most notably, reporting of the various types of cyber attacks in the news on a regular basis, driving both awareness and fear. Not surprisingly, cyber risk has become a board-level concern in today’s increasingly connected world. Additionally, recent growth of the Internet of Things has given rise to the seemingly infinite number of attack vectors affecting every industry. Individuals and entities of any size, spanning all regions of the world, are potential victims.

The apparent need for new apps and devices that link to one another without focus toward security of those apps or devices gives reason to worry. It also creates an immediate need for a suite of security analytics products that helps insurance companies write cyber insurance more confidently.

State of Data

Actuaries are creative and intelligent problem solvers, but this creativity and intelligence is tested thoroughly when pricing cyber insurance. Actuaries still need the same suite of products used within any other catastrophe-exposed lines of business, but there are many challenges and complications with respect to cyber insurance that make this a particularly difficult task. That is, we still need an underwriting tool, an individual risk-pricing tool and a catastrophe-aggregation model, but certain aspects of these tools vary significantly from what we’ve seen in the past or have grown accustomed to as actuaries.

Data lies at the center of any actuarial project, but data in this space is very limited for a number of reasons. To consider why this is the case, let’s take a step back and consider the wider context. We first want to think about both how to define the cyber peril and what types of attacks are possible.

Risks could lie anywhere between smaller attacks on individuals involving brute-force attempts to steal credentials and conduct identity theft; and state-sponsored attacks on another government entity involving both physical damage and theft of critically sensitive intelligence. We may see malware deployed on a commonly used piece of software or hardware at a massive scale; infrastructures or processes taken down using denial of service; or a breach of a popular database or platform that affects many entities simultaneously.

Many of the attack variants in this hypothetical list have never happened, and some may never happen. Even within those that have happened, information pertaining to the breach — both in terms of the attack specifics used or the actual dollar impact of the attack — is hard to come by.

Several third-party data sources are currently available, but they tend to concentrate primarily on those pieces of data or attack types that are most accessible — particularly data breach and privacy violation claims. This, naturally, is a very small subset of what we need to price for as actuaries.

Unfortunately, there is fairly loose regulation around the reporting of different types of attacks. Even within the data breach family, there exists tremendous lack of standardization across states with respect to reporting. Criteria for whether a report is required may include whether the data is encrypted, how many people were actually affected by the breach and the type of data stolen (PHI, PII, PCI, etc.).

See also: How Actuaries Can Be Faster, More Efficient  

External research can be done on public sources to find the aggregate amount of loss in some cases, but there is little to no incentive for the breached entity to provide more information than is absolutely required. Thus, while we want to price data breach events at a very granular level, it’s often difficult to obtain dollar figures at this level. For instance, a data breach will lead to several costs, both first party and third party. A breached entity, at minimum, will likely have to:

  • Notify affected customers;
  • Offer credit monitoring or identity-theft protection to those affected;
  • Work with credit card companies to issue new credit cards;
  • Foot bills associated with legal liability and regulatory fines; and
  • Endure reputational damage.

It’s impractical to assume that a breached entity would find it attractive to publicize the amount lost to each of these individual buckets.

Worse, other events that either don’t require reporting or have never happened clearly give us even less to work with. In these cases, it’s absolutely critical that we creatively use the best resources available. This approach requires a blend of insurance expertise, industry-specific knowledge and cyber security competence. While regulation will continue to grow and evolve — we may even see standardization across both insurance coverages offered and reporting requirements by state or country — we must assume that in the near future, our data will be imperfect.

Actuarial Challenges

Though many companies have entered the cyber insurance space, very few are backed by comprehensive analytics. Insurers eager to grab market share are placing too much emphasis on the possibility of recent line profitability continuing into the future.

The problem here is obvious: Cyber insurance needs to be priced at a low loss ratio because of catastrophic or aggregation risk. Once the wave of profitability ends, it could do so in dramatic fashion that proves devastating for many market participants. The risk is simply not well understood across the entirety of the market, and big data analytics is not being leveraged enough. In addition to the glaring data and standardization issues already discussed, actuaries face the following eight key challenges:

1. No Geographical Limitation

On the surface, the cyber realm poses threats vastly different from what we’ve seen in other lines of business. Take geography. We are used to thinking about the impact of geography as it pertains to policyholder concentration within a specific region. It’s well understood that, within commercial property insurance, writers should be careful with respect to how much premium they write along the coast of Florida, because a single large hurricane or tropical storm can otherwise have an absolutely devastating effect on a book of business. Within the cyber world, this relationship is a bit more blurry.

We can no longer just look at a map. We may insure an entity whose server in South Africa is linked to an office in Ireland, which, in turn, is linked to an office in San Francisco. As existing threat actors are able to both infiltrate a system and move within that system, the lines drawn on the map have less meaning. Not to say they’re not important — we could have regulatory requirements or data storage requirements that differ by geography in some meaningful way — but “concentration” takes a different meaning, and we need to pay close attention to the networks within a company.

2. Network Risk From an External Perspective

In the cyber insurance line, we need to pay attention to the networks external to an insured company. It’s well documented that Target’s data breach was conducted through an HVAC system. By examining Target’s internal systems alone, no one would have noticed the vulnerability that was exploited.

As underwriters and actuaries, we need to be well aware of the links from one company to another. Which companies does an insured do business with or contract work from? Just as we mentioned above with apps and devices that are linked, the network we are worried about is only as strong as the weakest link. Another example of this is the recent attacks on a Bangladeshi bank. Attackers were able to navigate through the SWIFT system by breaching a weaker-than-average security perimeter and carrying out attacks spanning multiple banks sharing the same financial network.

3. Significance of the Human Element

Another consideration and difference from the way we traditionally price is the addition of the human element. While human error has long been a part of other lines of business, we have rarely considered the impact of an active adversary on insurance prices. The one exception to this would be terrorism insurance, but mitigation of that risk has been largely assisted by TRIA/TRIPRA.

However, whenever we fix a problem simply by imposing limits, we aren’t really solving the larger problem. We are just shifting liability from one group to another; in this case, the liability is being shifted to the government. While we can take a similar approach with cyber insurance, that would mean ultimately shifting the responsibility from the insurers to the reinsurers or just back to the insureds themselves. The value of this, to society, is debatable.

See also: Cyber Insurance: Coming of Age in ’17?  

A predictive model becomes quite complex when you consider the different types of potential attackers, their capabilities and their motivations. It’s a constant game of cat and mouse, where black hat and white hat hackers are racing against each other. The problem here is that insurers and actuaries are typically neither white hat nor black hat hackers and don’t have the necessary cyber expertise to confidently predict loss propensity.

4. Correlation of Attacks

In attempting to model the “randomness” of attacks, it is important to think about how cyber attacks are publicized or reported in the news, about the reactions to those attacks and the implications on future attacks. In other words, we now have the issue of correlation across a number of factors. If Company A is breached by Person B, we have to ask ourselves a few questions. Will Company A be breached by Person C? Will Person B breach another company similar to or different from Company A? Will Person D steal Person B’s algorithm and use it on entirely different entity (after all, we’ve seen similar surge attacks within families such as ransomware)? If you as the reader know the answers to these questions, please email me after reading this paper.

5. Actuarial Paradox

We also have to consider the implications on the security posture of the affected entity itself. Does the attack make the perimeter of the affected company weaker, therefore creating additional vulnerability to future attacks? Or, alternatively, does the affected company enact a very strong counterpunch that makes it less prone to being breached or attacked in the future? If so, this poses an interesting actuarial dilemma.

Specifically, if a company gets breached, and that company has a very strong counterpunch, can we potentially say that a breached company is a better risk going forward? Then, the even-more-direct question, which will surely face resistance, is: Can we charge a lower actuarial premium for companies that have been breached in the past, knowing that their response to past events has actually made them safer risks? This flies directly in the face of everything we’ve done within other lines of business, but it could make intuitive sense depending on incident response efforts put forth by the company in the event of breach or attack.

6. Definition of a Cyber Catastrophe

Even something as simple as the definition of a catastrophe is in play. Within some other lines of insurance business, we’re used to thinking about an aggregate industry dollar threshold that helps determine whether an incident is categorized as a catastrophe. Within cyber, that may not work well. For instance, consider an attack on a single entity that provides a service for many other entities. It’s possible that, in the event of a breach, all of the liability falls on that single affected entity. The global economic impact as it pertains to dollars could be astronomical, but it’s not truly an aggregation event that we need to concern ourselves with from a catastrophe modeling perspective, particularly because policy limits will come into play in this scenario.

We need to focus on those events that affect multiple companies at the same time and, therefore, provide potential aggregation risk across the set of insureds in a given insurance company’s portfolio. This is, ultimately, the most complicated issue we’re trying to solve. Tying together a few of the related challenges: How are the risks in our portfolio connected with each other, now that we can’t purely rely on geography? Having analytical tools available to help diagnose these correlations and the potential impacts of different types of cyber attacks will dramatically help insurers write cyber insurance effectively and confidently, while capturing the human element aspect of the threats posed.

7. Dynamic Technology Evolution

If we can be certain of one thing, it’s that technology will not stop changing. How will modelers keep up with such a dynamic line of business? The specific threats posed change each year, forcing us to ask ourselves whether annual policies even work or how frequently we can update model estimates without annoying insurers. Just as we would write an endorsement in personal auto insurance for a new driver, should we modify premium mid-term to reflect a newly discovered specific risk to an insured? Or should we have shorter policy terms? The dynamic nature of this line forces us to rethink some of the most basic elements that we’ve gotten used to over the years.

8. Silent Coverage

Still, all of the above considerations only help answer the question of what the overall economic impact will be. We also need to consider how insurance terms and conditions, as well as exclusions, apply to inform the total insurable cost by different lines of insurance. Certain types of events are more insurable, some less. We have to consider how waivers of liability will be interpreted judicially, as well as the interplay of multiple lines of business.

It’s safe to assume that insurance policy language written decades ago did not place much emphasis on cyber exposure arising from a given product. In many cases, silent coverage of these types of perils was potentially entirely accidental. Still, insurers are coming to grips with the fact that this is an ever-increasing peril that needs to be specifically addressed and that there exists significant overlap across multiple lines of business. Exclusions or specific policy language can, in some cases, be a bit sloppy, leading to confusion regarding which product a given attack may actually be covered within. This becomes the last, but not least, problem we have to answer.

Conclusion

The emerging trends in cyber insurance raise a number of unique challenges and have forced us to reconsider how we think about underwriting, pricing and aggregation risk. No longer we can pinpoint our insureds on a map and know how an incident will affect the book of business. We need to think about both internal and external connections to an insured entity and about the correlations that exist between event types, threat actors and attack victims. In cases when an entity is attacked, we need to pay particular attention to the response and counterpunch.

As the cyber insurance market continues to grow, we will be better able to determine whether loss dollars tend to fall neatly within an increasing number of standalone cyber offerings or whether insurers will push these cyber coverages into existing lines of business such as general liability, directors and officers, workers’ compensation or other lines.

Actuaries and underwriters will need to overcome the lack of quality historical data by pairing the claims data that does exist with predictive product telemetry data and expert insight spanning insurance, cyber security and industry. Over time, this effort may be assisted as legislation or widely accepted model schema move us toward a world with standardized language and coverage options. Nonetheless, the dynamic nature of the risk with new adversaries, technologies and attack vectors emerging on a regular basis will require monitored approaches.

See also: Another Reason to Consider Cyber Insurance  

In addition, those that create new technology need to realize the importance of security in the rush to get new products to market. White hat hackers will have to work diligently to outpace black hat hackers, while actuaries will use this insight to maintain up-to-date threat actor models with a need for speed unlike any seen before by the traditional insurance market.

Some of these challenges may prove easier than they appear on paper, while some may prove far more complicated. We know actuaries are good problem solvers, but this test will be a serious and very important one that needs to be solved in partnership with individuals from cyber security and insurance industries.

Where is Real Home for Analytics?

One of the fascinating aspects of technology consulting is having the opportunity to see how different organizations address the same issues. These days, analytics is a superb example. Even though every organization needs analytics, they are not all coming to the same conclusions about where “Analytics Central” lies within the company’s structure. In some carriers, marketing picked up the baton first. In others, actuaries have naturally been involved and still are. In a few cases, data science started in IT, with data managers and analytical types offering their services to the company as an internal partner, modeled after most other IT services.

In several situations that we’ve seen, there is no Analytics Central at all. A decentralized view of analytics has grown up in the void – so that every area needing analytics fends for itself. There are a host of reasons this becomes impractical, so often we find these organizations seeking assistance in developing an enterprise plan for data and analytics. This plan accounts for more than just technology modernization and nearly always requires some fresh sketches on the org chart.

Whichever situation may represent the analytics picture in your company, it’s important to note that no matter where analytics begins or where it currently resides, that location isn’t always where it is going to end up.

Ten years ago, if you had asked any senior executive where data analytics would reside within the organization, he or she would likely have said, “actuarial.” Actuaries are, after all, the original insurance analytics experts and providers. Operational reporting, statistical modeling, mortality on the life side and pricing and loss development on the P&C side – all of these functions are the lifeblood that keep insurers profitable with the proper level of risk and the correct assumptions for new business. Why wouldn’t actuaries also be the ones to carry the new data analytics forward with the right assumptions and the proper use of data?

Yet, when I was invited to speak at a big data and analytics conference with more than 100 insurance executives and interested parties recently, there was not one actuary in attendance. I don’t know why — maybe because it was quarter-end — but I can only assume that, even though actuaries may want to be involved, their day jobs get in the way. Quarterly reserve reviews, important loss development analysis and price adequacy studies can already consume more time than actuaries have. In many organizations, the actuarial teams are stretched so thin they simply don’t have the bandwidth to participate in modeling efforts with unclear benefits.

Then there is marketing. One could argue that marketing has the most to gain from housing the new corps of data scientists. If one looks at analytics from an organizational/financial perspective, marketing ROI could be the fuel for funding the new tools and resources that will grow top-line premium. Marketing also makes sense from a cultural perspective. It is the one area of the insurance organization that is already used to blending the creative with the analytical, understanding the value of testing methods and messages and even the ancillary need to provide feedback visually.

The list of possibilities can go on and on. One could make a case for placing analytics in the business, keeping it under IT, employing an out-of-house partner solution, etc. There are many good reasons for all of these, but I suspect that most analytics functions will end up in a structure all their own. That’s where we’ll begin “Where is the Real Home for Analytics, Part II” in two weeks.

How Risk Management Drives up Profits

Diane Meyers, director of corporate insurance for YRC Worldwide, manages the insurance and associated risks of one of the most hazard-prone industries in the world – trucking. YRC is the largest long-haul trucking company in U.S., operating in all 50 states and Canada. It has 14,500 tractors and 46,500 trailers and ships 70% of all transported cargo throughout the U.S. each year. YRC’s origins trace back to 1924 to the Akron, Ohio-based company Yellow Cab Transit before the independent trucking companies of Yellow, Roadway, Reimer and others were combined in 2009 into the YRC banner.

I asked Diane about her biggest challenges in managing the risks associated with the YRC fleet, including 32,000-plus employees (a number that has grown in busy times to more than 50,000) and 400 physical locations. She said her top three hot buttons are: collateral, collateral and collateral.

For anyone familiar with high-deductible or self-insured workers’ comp programs, insurers and state governments rely on a company’s posted collateral (aka security deposit) as the financial backstop should the company go bankrupt or default in its obligations. Companies with high-risk jobs can experience workers’ comp costs that can easily be 400% to 500% greater than white collar jobs. Posted collateral needs to cover the costs expected to be associated with the life of each claim and can be a huge drain for any company, including YRC.

Diane, who reports to the treasurer, says YRC negotiates collateral requirements with one excess workers’ comp insurer for its high-deductible program in 24 states. Collateral is typically posted using LOCs (letters of credit) or surety bonds. YRC’s self-insured program in the remaining 26 states means meeting the collateral demands of their 26 separate governing entities.

Meeting with the YRC’s carrier’s actuary along with her own actuary every three months, Diane also has to deal with each state at least annually. “Working with multiple sets of actuaries is a whole other challenge, since I have to educate them on the realities of our own workers’ comp program and its achievements, like return-to-work,” she says. “Besides that, in working with actuaries, I have to speak their language and understand how they work their crystal ball.”

Diane added: “These are monies that are tied up for decades to come that cannot otherwise be used for our company’s operations. I have to find ways to save the company from the ever-changing collateralization demands through ongoing, complex negotiations with insurers and regulators. Safety and loss control programs have to demonstrate traction and real savings to our workers’ comp and liability exposures.” Diane noted that safety is so important that each YRC operating division has its own safety department.

As with most large companies, YRC is self-insured for most of its liability risks. To assist Diane with vehicle and general liability claims, YRC uses its own, as well as outsourced, legal counsel to manage risks up to its retention level. There are also a myriad of state and federal rules and regulations regarding long-haul trucking that require strict adherence and attention to changes.

When asked about her unique challenges at YRC, Diane said, “I have to understand the legal demands and expectations of all 50 states, Canada, and D.C.”

She also faces the complexity of working with a corporation that has grown through acquisitions of older companies. To find key claim-related data, she says, “I have had to go through various insurance policies and records of the companies we acquired going back as far as the ’60s!”

With the ever-changing demands for long-haul transportation by various industries, YRC experiences significant fluctuations in its workforce. There have been times when the workforce has expanded more than 50%, and, during recessions, there have been significant reductions. A swing either way can create huge risk management challenges, especially when there are continuing workers’ comp claims to deal with. This is made even tougher because most of YRC’s employees are in the Teamsters union, and some issues could require collective bargaining or at least close communication and cooperation between labor and management.

Modernization: Actuaries Must, Too

To effectively produce a variety of new financial reporting, reserving and risk metrics, actuarial departments will need to modernize with new tools, hardware, processes and skills. This will be a significant undertaking, especially considering how most organizations and regulatory environments are constantly changing. Re-engineering projects will require careful planning and will affect people, processes and technology. Developing a modernization strategy that provides a path to real change includes visualizing a compelling future state, articulating and communicating expectations, defining a roadmap with achievable goals and avoiding overreach during the implementation.

Case for change

The insurance market has changed significantly in recent years, which has had a particularly pronounced effect on how companies operate, meet internal and external demands, report externally and comply with regulations. However, many insurers have not modernized their actuarial functions to keep pace with these changes and are struggling to effectively meet not just existing demands but also impending ones.

Specifically, drivers of actuarial modernization include:

  • Internal drivers – The audit committee seeks assurance that reserves and risk-based capital are sufficient and being determined in a well-controlled environment. Senior management wants actuarial departments that work toward the same strategic goals as the rest of the company. Business units are looking for trusted actuarial advisers who can collaborate effectively with them, as well as develop practical solutions to complex problems to help them meet their business objectives. Lastly, the finance department needs timely insight into how the reserve movements affect earnings and equity.
  • External drivers – The need to issue financial reports under multiple accounting bases necessitates the adoption of new processes as well as the collection of additional data. Similarly, regulatory requirements have mandated additional analyses, various views of the book of business and a push toward more forward-looking information. Other external parties, including investors and rating agencies, demand more information with a greater degree of transparency than ever before.

The modernized actuarial function

In a modernized company, the actuarial, finance, risk and IT functions have clearly defined, collective expectations and utilize common, efficient processes. More specifically, the following characterizes a modernized actuarial function:

  • Data – The organization, with significant actuarial input, clearly defines its data strategy via integrated information from commonly recognized sources. The goal of this strategy is information that users can extract and manipulate with minimal manual intervention at a sufficient level of detail to allow for on-demand analysis.
  • Tools and technology – Tools and technology enhance the effectiveness of the actuarial department by delivering information faster, more accurately and more transparently vs. the traditional, ad hoc computing done by end users. Specifically, tools that use data visualization can more effectively convey trends and results to management. Algorithms can be programmed to automate first-cut reserving and other actuarial analyses each reporting period based on rules that can help point staff to business segments that may require deeper analysis in the quarter.
  • Methods and analysis – Modernized actuarial organizations enhance traditional actuarial methodologies with additional cutting-edge methods that yield superior insights (e.g., predictive analytics, which have transformed personal lines pricing and are being adopted in the commercial arena). Another example is stochastic analysis, which enhances deterministic approaches with statistical rigor, helps actuaries prepare transparent reserve range indications and enables management to better understand uncertainties.
  • Processes – Operations are reviewed from the top down and well-defined in terms of controls, responsibilities, timing,and outputs, particularly in the quarter-close procedures for reserves. Automation of key processes is a primary organizational objective. Modernized actuarial organizations have streamlined processes that eliminate unnecessary or excessive evaluation.
  • Organizational structure – The ability to deliver superior business intelligence to management often depends on how an organization uses its actuarial resources. Many companies are debating the merits of centralized, decentralized or hybrid organizational structures. While each structure has its own set of advantages and disadvantages, organizational structure is not the most vital factor in a function’s success. Rather, it is much more important that actuaries serve as trusted advisers to company stakeholders while fostering a culture of innovative thinking that identifies new information and opportunities to test, learn and scale.
  • Reporting and governance – Strong governance, particularly around data, analysis review, challenge, issue escalation and resolution and reporting are cornerstones of a modernized actuarial function. Actuarial functions solicit stakeholder input on information demands and provides consistent, quarterly reporting packs that satisfy these stakeholders’ reporting demands. Additionally, modernized actuarial functions have formal policies and procedures that clarify the roles and responsibilities of management, reserve committees and the audit committee.
  • Business intelligence – Modernized actuarial functions focus on providing operational metrics that meet individual stakeholder needs and objectively relate business performance. For example, senior managers often desire corporate dashboards that provide them access to real-time information on business performance to help them make strategic decisions.

Benefits of insurance modernization

A modernized actuarial function produces insightful, strategic information and allows the actuarial function to deliver the value management desires while meeting external stakeholders’ regulations and demands. Modernized actuarial functions have robust feedback loops within pricing, reserving and capital management.  Additionally, the modernized actuarial function understands the business’ fundamental performance and takes an active role in helping management define the company’s future direction.

Modernization represents a fundamental shift in the actuarial function priorities. Traditionally, the actuarial function has provided a retrospective look at business performance despite various data, technology, process and personnel limitations. However, modernization seeks to address these limitations and allow the actuarial function the freedom to innovate, dig deeper into the business, provide forward-looking insights and have a strategic partnership with management.

At modernized insurers, tailored reports direct actuaries’ attention to portfolios with unusual characteristics. Automated programs quickly populate various templates for additional ad hoc analyses and drill-down investigation. Data visualization tools provide management comfort with findings and remediation recommendations. Cross- functional reporting and implementation teams fluidly improve on-the-ground results. Research features exploratory environments (“sandboxes”) and widespread data access that helps innovators discover emerging trends early, leading to potential differentiators. As an added benefit, actuarially modernized functions operate at a much higher level of efficiency, with greatly reduced levels of time needed for manual processing and data manipulation.

Factors for successful modernization/ key considerations

The thought of overhauling entire systems, processes and functional areas may feel overwhelming for company executives. This is understandable, as comprehensive modernization is a long journey that likely will have a significant price tag. As a result, many companies address modernization in steps. Although, in an ideal world with limitless resources, modernization could occur in a “big bang,” there is significant value in first addressing the areas in most need of modernization (while maintaining an overarching focus on holistic modernization). As one area becomes more streamlined and efficient, other areas will start to reap the benefits.

Regardless of the breadth of modernization initiatives, modernization strategies will require a holistic consideration of data, methods and analyses, tools and technology, actuarial processes and human capital requirements.  These strategies will also need to address the business and operational changes necessary to deliver new business intelligence metrics. Any weak links between these closely connected components will limit the realization of actuarial modernization.

Although a modernization strategy should be holistic to avoid “digging up the road multiple times,” it is possible to tackle modernization issues in logical, progressive ways.

Achieving the vision

The first step is a comprehensive assessment of current processes and identifying the areas in greatest need of modernization. If we consider each modernization dimension (e.g., data, processes, technology, etc.) as a gear in motion, the first step to modernization  involves identifying which gear in the function does not work in concert with the others. Stakeholders should collaborate on creating a comprehensive plan of action with an objective view of the dimensions that require immediate attention, while keeping in mind how each gear affects the organization as a whole.

Captives: Cutting Through the Obfuscation

If you are not a practicing member of the captive community, either as a professional service provider or a captive owner, and are interested in learning about captives, you will most likely turn to the Internet.  Unfortunately, the vast majority of Internet sources are designed to sell you something, or at the very least, tempt you to contact them with some sort of “teaser.”

Additional sources of captive information are periodic industry-focused magazine articles and occasional pieces that appear in the likes of Forbes and Fortune magazines, along with the odd newspaper article. These are often interesting to read, but they are almost always written from a particular point of view, and because of time and space limitations, rarely present a truly balanced perspective.

You may recall a few years ago, when a financial reporter for the New York Times wrote what was intended to be an expose of captives’ presumed nefarious financial and tax doings.  The piece was ultimately discredited, its author clearly had an agenda. (For good measure, the Times, turned out to own a captive).

Given the general lack of information about captives, let’s begin with some basics.  Regardless of what you may have read, a captive is first and foremost, an insurance company.  The term “captive” denotes insurance company status.  Insurance company status means that the captive employs insurance accounting.  If the structure cannot qualify for insurance accounting, it must use deposit accounting, which renders it something other than a captive insurance company.

Insurance accounting allows the captive to deduct its loss reserves from its federal income taxes; taxes are paid on earnings, and earnings are recognized once losses for a particular period (usually a year) are no longer expected to occur or become reported.

Moreover, the captive’s contracts (insurance policies) must conform to Financial Accounting Standard (FAS) 113.  FAS 113 requires that the insurance contract provide coverage for a reasonable chance of a significant loss.

Contrary to what you may read, a captive is not a tax shelter, nor is it a bank.  It can be used, however, as an estate-planning tool (more on this later).  To qualify to use insurance accounting every captive must:

  • Establish and document non-tax business objectives and purpose
  • Experience insurance losses
  • No parental guarantees to bail out the captive
  • Have adequate capitalization
  • Avoid substantial loan-backs
  • Engage professional captive management
  • Comply with local insurance regulations and formalities
  • Follow conventional investment strategies
  • Use risk-transferring insurance contracts per FAS 113
  • Make sure risk sharing is sufficient based on IRS safe harbors
  • Transact business at “arms length” using actuarial-based pricing
  • Maintain the business, books, and records separate from the parent company and comparable to other insurers
  • Not have premiums match the maximum limit of liability

The majority of the companies selling captives – not feasibility studies, just captives – sell what is known as the 831(b) captive.  Caompnies will also assist in the creation of standard captives, but their primary stock-in-trade is the 831(b).

This captive’s name is derived from the section of the Internal Revenue Code that enables their use.  Many of these 831(b) companies make little pretense of providing objective risk management advice; their advice centers on estate planning, which is the primary purpose of the 831(b) captive.  The primary benefits of the 831(B) captive are that (1) only investment income is subject to U.S. federal income taxation (income from premiums is tax-free)  and that (2) 831(b) captives are off-balance sheet.

Unfortunately, many firms have a less-than-comprehensive grasp on the rules to which all captives must adhere, to be considered bona fide insures.  Others conflate certain aspects of the 831(b) captive with captives in general, which of course causes confusion and adds to the amount of misinformation available to prospective captive owners.

Because there is so much blatant misinformation on the Internet, it was hard to pick out the best examples for this article, but I think you’ll find the following examples entertaining, if not disconcerting.

Example 1

An article appearing in a respected technical journal on taxation and accounting lists the following as three benefits of captives:

  • “Asset protection from the claims of business and personal creditors” 
  • “Opportunity to accumulate wealth in a tax-favored vehicle”
  • “Distributions to captive owners at favorable income tax rates”

The problem is that none of the three so-called benefits apply to the vast majority of captive insurers.  They apply ONLY to the 831(b) captive, which, as noted above, is used as an estate-planning vehicle.

The vast majority of captives (non-831 (b) captives) are on-balance-sheet, risk-financing vehicles.  Their tax filings are consolidated with their parents’ filings, so they provide no asset protection from creditors.  Likewise, the vast majority of captives are not “tax-favored,” thanks to the 1986 tax law changes.

The fact that the article is actually devoted to only 831(b) captives is never revealed; the term 831(b) is not even mentioned until page three of the six-page article.

Example 2

A promoter advertises itself as offering a “new service” to help clients “take advantage of Captive structures and domiciles to meet their individual risk management needs.”

It is clear that this company has almost no institutional knowledge of captives.  Its litany of captive benefits is a recitation of the generic, non-specific “benefits” cited hundreds of times across the Internet and elsewhere.  It is obvious that this firm is, like many others, describing the 831(b) captive, but it doesn't even use the term.

This firm’s captive “sin” is tax-related.  This is ironic as according to the firm’s marketing literature, it is the leading tax services firm in North America!  Its sales material on captives states that annual insurance premiums (paid to a captive from its parent) are tax-deductible as ordinary and reasonable expenses pursuant to IRC Section 162(a).  This statement is untrue on its face.

IRC Section 162(a) does indeed provide guidance as to tax-deductible business expenses.  However, given the specialized rules (for captives) promulgated by the IRS over the last couple of decades, this firm’s lack of understanding of captives is not only annoying; it’s potentially dangerous.  The IRS has issued a raft of revenue rulings that address the tax status of captives and their parents, in a wide variety of circumstances.

The central theme of many is the notion of what constitutes risk distribution (risk sharing).  These rules are applicable to every captive, including the 831(b) variety.  Briefly, a single-parent captive (such as an 831(b) captive), must have at least 50% unrelated business to qualify as a bona fide insurer.  This means that only about half of the captive’s total annual premiums can come from the captive parent.

To add insult to injury, in the same marketing piece, this firm says that safe harbor revenue rulings provide the tax benefits.  They do indeed, but only if the prospective captive owner can qualify under them!  This firm’s message is that any company that pays taxes is automatically qualified to form a captive.  Bait and switch?

This firm’s marketing literature also says that a captive’s funds can be immediately invested in just about anything the owner wants – real estate, stocks, bonds, mutual funds, etc.  Nothing could be further from the truth.  Some captive domiciles, such as Bermuda, have specific investment guidelines designed to require the captive to hold primarily liquid investments.  In Bermuda, 75% of investments must be considered “relevant,” another way to say liquid.

Some onshore domiciles such as Vermont have no specific investment guidelines for single-parent captives, but I guarantee that the regulator (and your actuaries) will seriously discourage illiquid investments such as real estate and equities.  Bonds are the preferred captive investments.

Example 3

Another firm proclaiming captive expertise provides an exhibit that ostensibly shows captive tax benefits over ten years.  If you’ll recall, the first principle – Establish and document non-tax business objectives and purpose  doesn’t appear to be a priority with this firm.  The exhibit compares after-tax income with and without an 831(b) captive.

On its face, the exhibit shows that with a captive, if the parent company pays about $10 million into its little captive over 10 years, it earns about $5 million over the no-captive scenario.  Unfortunately, the exhibit fails to include a rather important element – captive losses.  Without losses, captives are nothing more than tax-advantaged pools of funds, upon which the IRS frowns.  This omission effectively renders the exhibit worthless.

Conclusion

Unfortunately the snake oil trade is alive and well on the Internet.  How does one guard against such shenanigans?  The only effective way to do so is to talk to qualified professionals (consultants, attorneys, etc.) who have nothing to sell but advice.  My next article will include a few more egregious examples of professional malpractice or prevarication, along with a detailed, unbiased, discussion of the 831(b) captive and its uses.  Stay tuned.