A Property/Casualty Perspective: The Birth, Death and Resurrection of Dynamic Financial Analysis

A PROPERTY/CASUALTY PERSPECTIVE: The Birth, Death and Resurrection of Dynamic Financial Analysis

The second article of a six–part series on The Evolution of Risk Management

By Robert Wolf

It seems only yesterday, but it was 1991. It was the early days of my consulting career. I had to tell my client, an officer of a small multiline property/casualty insurance company, that he was on the verge of financial collapse. I had to tell him that loss reserves were materially deficient, his rates charged on policies in force were materially inadequate, and that he should be concerned with liquidity to meet policyholder obligations as they became due per their huge agents' balances and reinsurance receivables. Bottom–line, this company was in trouble and they did not have a clue that they were. I recommended they speak to the insurance department to convey this situation to them, thinking this to be a better approach than if the insurance department discovered all of this themselves.

My client looked up at me and asked, "Can you help me with a workout plan? How do I get out of this?" After deliberating with colleagues at my consulting firm, we came up with a process of modeling (deterministically at the time) a scenario of future balance sheets and income statements, one to five years out into the future, reflecting realizations contingent on various strategies. Assumptions included the following:

• To what extent rates needed to be increased—all at once or every six months?
• How many policyholders would flee to other carriers (a liquidity problem) given the rate increases?
• How many lines of business should we grow in or leave?
• How does the company's reinsurance structure need to be revised and restructured and how does that play out in the financials?
• How do we re–strategize the asset side of the balance sheet to improve cash flow?
• Can we get some additional capital? How much do we need and at what cost?

Based on these assumptions, and everything going according to plan (a key assumption), they could have worked it all out in five years. This was something that the company could approach the insurance department with, before the department came in and figured it out for themselves. In essence, it was a mathematical spreadsheet exercise, determining how long it would take for this company to get back to where it needed to be given the realization of assumptions and strategies we had discussed.

But what if everything didn't go according to the plan? I started including multiple scenarios, which created multiple Lotus (yes, Lotus) spreadsheet files. Bear in mind that the computer capacity in the early 90s did not stack up to how fast I was conjuring up alternate scenarios. I had to build in more and more assumptions, scenarios and considerations. Let's see. If you increase rates 40 percent, how many policyholders will flee? Where will they go and what are the current competitive rates? How are rating agencies going to rate the company? If the regulator gets there before the company implements this workout plan, they will probably put the company into rehabilitation, furthering the liquidity problem as all current and potential policyholders will duck for cover. Not only that, but virtually all the reinsurers will flee. And down and down into the spiral we go, further exacerbating the liquidity problem. This exercise started me wondering why we are so concerned with the probability of ruin so common in actuarial literature at the time. I could not point to one event or situation that caused all of this.

Little did I know at the time, I was actually producing and applying dynamic financial analysis (at its early stage). With all of the scenarios of Lotus spreadsheets I was creating, I finally got to a point of using @Risk for DOS (don't laugh), pushed a button and waited for 1,000 realizations to run. I literally pushed the button at 5 p.m., came back the next morning and just hoped and prayed that it finished with no errors and the results were reasonable. If not, I may have to use up the next day as well to rerun the model.

As the 90s continued, regulators and rating agencies, previously relying on rules of thumb leverage ratios and ratio tests (e.g., IRIS tests), moved into more complex regulatory requirements of capitalization of companies with the risk–based–capital requirements. In Canada, Dynamic Capital Adequacy Testing (DCAT) was born. The New York state regulators introduced seven interest rate scenarios that life insurers needed to apply in testing their reserve adequacy. Companies were beginning to model their own risks internally, or at least dabble in it. Hence the birth of Dynamic Financial Analysis in the property/casualty insurance industry.

Dynamic Financial Analysis: Ahead of Its Time

The computer capacity increased unfathomably. We were able to model thousands of future balance sheets, income statements, cash flows and external economic scenarios based on multiple and unlimited numbers of strategic assumptions within minutes. They were fun.

Graphing these exercises produced spider–looking graphs with thousands of scenario paths. While intimidating, it became the tool of the day. Hey, we can produce thousands of realizations of business plans by putting variability around loss outcomes, interest rate outcomes, stock market outcomes and law changes. We can load for the once–in–a–lifetime catastrophe to really make things more interesting, as if we knew what the event was. The Casualty Actuarial Society (CAS) created Dynamic Financial Analysis (DFA) committees, DFA tracks at its annual meetings, DFA seminars, DFA publications, publicly available DFA models, etc. It became the Holy Grail.

But what was the Holy Grail for? While the actuarial profession used it, embraced it, invested in it, our audiences—employers, clients and society at large—were not yet there. Although DFA gained significant traction as a tool and revolutionized the actuary, the resultant solutions didn't gain corresponding momentum in the industry. Yet, some may say that we didn't sell it correctly. I disagree. I believe that, like anything else, any new idea or concept takes some time.

The actuarial profession continued to tout its uses:

• We can use DFA to assess if a merger is effective.
• We can use DFA to devise the most effective reinsurance structure or hedging strategy for the risks we are underwriting.
• We can use DFA to analyze the risk and return trade–off.
• We can use DFA to make strategic decisions on what product lines to grow/decline or where we should be in business at all.

Add to our above touting, a lot of patience (ours), and several servings of dot–com bursts, man–made catastrophes, hurricanes and corporate fraud cases later, our publics caught up. Demand for better transparency and accountability led into the current demand and, hence, evolution of enterprise risk management (ERM).Although DFA lost its initial traction, it was resurrected into an effective modeling tool for ERM. It remains an opportunity for our profession to make a difference in the property/casualty space.

The Resurgence

While DFA was trying to gain traction, it was generally agreed in the casualty industry that it was a solution looking for a problem. In the ERM evolution, I believe it found a solution in the casualty insurance industry. This is not to say that DFA is necessary or an ultimate solution for ERM. ERM stands for enterprise risk management, not just modeling. As it looked for the problems to model, it helped create an ERM opportunity for the actuarial community. Arguably, the holistic modeling of a myriad of risks within the context of diversifications and domino–effect correlations helped to produce the organizing concept of ERM in the property/casualty insurance industry today.

The embryo of the successful ERM symposium was, in fact, the special interest annual DFA seminars that were put out by the CAS in the late '90s. The SOA, in its production of a one–time ERM special interest seminar, became an informal partner eight years ago by following one of the CAS DFA seminars. The collaboration of those beginning adjoining seminars produced the impetus of the now incredibly successful symposium and the Joint Risk Management Section. The CAS DFA tracks, committees, task forces and papers, etc., have been transformed into ERM tracks, committees and task forces. Today, virtually every actuarial association in the world is embracing and recognizing the opportunity for our profession. Consortiums of actuarial associations are looking at the feasibility of a global actuarial designation focused on the ERM discipline, led by the SOA in its development of the now familiar Chartered Enterprise Risk Analyst (CERA) designation. A clear, endless chain of DFA savvy actuaries easily migrated into the ERM era.

DFA: The Middle Phase of a Three–Phase Enterprise Risk Management Evolution

Not long ago, project analysis and ratemaking in general was based on a deterministic approach. The National Counsel of Compensation Insurers' internal rate of return models and the Myers Cohn net present value models used in Massachusetts auto rate regulation, were prominent examples of the many mainstream approaches to dealing with fair prices in property/casualty insurance products. This type of risk analysis represented a single deterministic forecast of the future. The actuary would take the present value of the future or gauge the internal rate of return of the future. Uncertainty would be handled via the discount rate. Risk, in essence, was arguably measured subjectively and was buried in a discount rate. One could call this the beginning phase of the ERM evolution.

DFA arguably brought the actuary's work into the second phase of ERM evolution, namely the risk analysis phase. Instead of projecting an expected outcome and using risk adjusted rates to reflect risk, we began modeling the risks around probability distributions of outcomes and in considerations and interactions across risks via either simulation or scenario modeling. Although judgment of a company's risk profile still discerned the strategy, it was the modeling results that served as a tool. I believe the casualty insurance industry is clearly in the risk analysis phase.

Phase three in the ERM evolution can be termed the Corporate Risk Tolerance phase of its evolution. ERM in the property/casualty industry is clearly in its rip current between phases two and three of the three–step ERM process. We are seeing the wave and we are looking over it. Why the rip currents? As I stated in the first installment of this article series (The Actuary, June/July 2008), some experts remain fixated on the classic views of portfolio management in that diversified investors are only concerned with non–diversifiable risk and hence, only require returns commensurate with those risks that cannot be diversified away. This theory implies that the managers of the company shouldn't worry about firm specific risk as the shareholders are supposedly neutral on it (they can diversify it away). Therefore, firm managers should only be focused on maximizing shareholder value. Applying these traditional analogues does not project into practical business management. The questions that arise are:

• Do firm managers really know which risks are systematic and which are firm specific?
• Do shareholders really know if they have truly diversified away so–called diversifiable risk?

Given these two questions, I believe that, in a practical sense, neither the market nor company management appear sufficient on their own to divide risks between those that are diversifiable and those that are not within goals of enterprise risk management. Classical portfolio theory concepts may not be enough here. There appears to be a common denominator that naturally complements the markets and the firm managers. I believe this common denominator is the goal of maximizing the market value of the enterprise (i.e., managing the returns with the risks sought—diversifiable or not). As a result, as enterprise risk management aims to facilitate future earnings growth to protect franchise value, it is to the advantage of both camps (the market and firm managers) to support a company wide ERM program that is objective and transparent to both parties.

How ERM Differs on the Property–Casualty Side

On the surface, ERM is similar in all insurance sectors. Where it differentiates in essence, especially in the property/casualty and health sectors, is how one follows the cash. Unlike life contingent products, in the property/casualty sector there are no capital pools by product line. There are no homeowners insurance pools, general liability pools, mega risk pools, workers compensation pools, etc. There are no separate ALM strategies by product line. Investments are not segregated by product nor by line of business, nor are they differentiated by what portion of an insurer's asset portfolio is backed by equity and by what is policyholder liability. Lines of business are not segregated into separate investments. Only the stated liabilities (loss reserves) play a direct role in byline profitability analysis. Investment benefits are shared across the products.

ERM in a property/casualty insurance company, with the goal of maximizing shareholder value, falls in the category of managing towards an equilibrium in the interaction of policyholder supplied funds (PHSF) and shareholder supplied funds (SHSF). The balance sheet plus franchise value components dictated by this interaction resembles, in essence, a tax disadvantaged trust (double taxation of corporate profits and shareholder dividends). Because of the non one–to–one alignment between asset pools and liabilities corresponding to the product lines, an extensive exercise in gauging returns and risk has been in the appropriation of investment returns, and the cost of capital to business segments. Effective ERM in the property casualty industry translates into managing the so–called float of investing PHSFs until needed to pay claims to the satisfaction (through returns) of the owners.

Strides have been made from the rules of thumb methods of the past to the current mainstream position of marginal methods such as the Mango Marginal Consumption Method which considers policyholder calls on the entire assets of the company. This method in essence sets profit targets of a business unit to value its right to call upon the capital of the entire firm, not just the allocated capital to the line. In like manner, the company carries the risk of the business unit's right to access the insurer's capital—the value of accessing the capital is an implicit cost of carrying the business unit (Merton/Perold). When I started my career, the industry was allocating capital to its product line by its respective share of the premium—what an evolutionary change from not that long ago.

The largest hurdles in applying ERM in the property/casualty industry are in the magnitude of uncertainty. Surveys show that the primary reasons for property/casualty insurance company failures are in reserve deficiencies. The industry now believes that this reasoning is not enough, but is rather a symptom of other failures. Reserve deficiencies happen because the business was not, in hindsight, adequately priced, for one reason or another. Rarely does an insurance company failure occur because of the mega–risk event, such as a man–made or natural catastrophe. They occur because of unexpected or unplanned outcomes (in comparison to business plans which may result from erroneous strategic planning), unexpected changes in tort laws, unexpected changes in claim litigiousness, mismanagement or just plain dumb luck. That said, ERM has, is and will continue to change the way the property/casualty sector is being managed.

The Value of ERM in the Property/Casualty Insurance Industry

Many of our publics, including ourselves, continue to expect a numerical value in an ERM success story. For example, can we point to a Company XYZ in its implementation of a robust and comprehensive ERM infrastructure and subsequently value its success? This has proved to be a daunting assignment, perhaps as daunting an assignment as trying to categorize risk as either diversifiable or non–diversifiable. As with anything in life, there are gray areas of both sides. Perhaps our measurement of the value ERM brings is not in any one number, but in the changes in the way the business is managed in the sectors in which our profession works. Perhaps the numerical value of success can be measured later. In the property/casualty sector, a change in the manner the business is managed is self–evident in the following aspects:

• Asset/Liability Management: Not long ago, asset/liability management meant asset/liability cash flow and/or duration matching. Today, ALM considers whether the company is getting returns from the mismatch before deeming such a decision as being optimal. Clearly this is a migration from risk management to risk and return management.


• Reinsurance Risk Transfer Plus: Reinsurance that didn't transfer a lot of risk (finite risk programs) was deemed a shoddy reinsurance scam. Eliott Spitzer sought to prove that. Now, finite risk deals are assessed on the additional rewards of having available cash when needed from unexpected contingent events (a form of contingent borrowing). Although I agree some of these shoddy deals have gamed accounting conventions in reinsurance transactions, most of them did, however, provide value to the cedants. Valuing the benefits of reinsurance is now seen as bifurcated into the benefits of both risk transfer and contingent borrowing, despite its slow evolvement in accounting conventions.


• Economic Capital: A company used to manage its capital needs based on external mandates by regulators and rating agencies of how much capital is deemed to be enough. Today companies are considering their own economic capital needs based on their risk profile and risk tolerance. Although clearly not there yet, companies are providing the research and initiatives today for developing these internal models (dare I say DFA models) to comply when Solvency II will most likely be the regulatory standard of the global industry. A growing trend is companies managing capital as a process of not only gauging financial strength, but also as having sufficient capital to attract business and having healthy returns on the capital supplied. This is being done so that capital can effectively and efficiently be deployed. Therein lies the ongoing evolutionary theme of managing the returns within the risks (capital efficiency) and the risks within the returns (capital adequacy).


• Pricing the Business: Not long ago, rating/pricing plans were based on two–way classification ratings (location and experience of the driver, for example). Although techniques for minimizing bias in correlated variables existed, we were nowhere near using the tools prevalent today. Today, rates are analyzed holistically using advanced predictive modeling techniques in gauging the credence a virtually infinite set of correlated variables have on the potential future results of loss experience. In addition to, say, location and experience of the driver, credit scoring is now reflected in auto rates. The industry is now beginning to price its products looking at the risk variables holistically as opposed to two or three dimensional cells.


• Managing to a Closer Cliff—Liquidity: The ERM evolution provided realization that the industry should base its management of risk assuming the cliff to be closer. Whereas focus in the past was rooted in assessing failure at the one–in–a–lot event, there is a realization that loss does not have to be extreme to be uncomfortable and to impair the company's ability to thrive on a going concern basis. My aforementioned work with that small multiline company served as my first realization of that. A key aspect of ERM is the management of liquidity risk. Once a consumer, regulator or rating agent loses confidence and ratings are downgraded, the domino effects that occur are very difficult to stop for a national multiline property/casualty carrier and form an infinite death loop:

1. New business and renewals slow up and or stop, thereby slowing/stopping PHSFs.
2. Reinsurers start delaying or further delay payments and/or duck for cover, further slowing PHSFs.
3. The resultant cash flows that you thought you had available to pay benefits and claims as they are due are not there, increasing the need to liquidate some assets earlier than planned in the company's investment strategy, which may reduce investment returns and negate strategies put in place to manage constraints.
4. Subsequent Ratings Drop from A– to B+ to B to C to D to Death Spiral.
5. Go Back to Step 1, repeat until insolvency occurs.

The risk metric cliff should really be where this starts to happen. Companies today are managing closer to this type of framework. More and more casualty companies are treating their profile as how much capital they can afford to lose and, more importantly, how they can get it back before the spiral happens. More and more companies are managing their business on the basis of having sufficient capital to continue serving renewals and hence thriving, despite fortuitous, contingent, unexpected outcomes. More and more companies are looking at the time they can lose and time they can recover in their strategic risk management processes. This evolution emphasizes a clear trend to recovery management as well as survival management, consistent within an ERM framework.

Pushing for Phase Three

Enterprise risk management in the property/casualty insurance industry is clearly going beyond phase two risk analysis in the ERM evolution, and in fact, is climbing to phase three—corporate risk tolerance. Managing liquidity, little more than a passing thought in the past, may be the single most important risk aspect in the property/ casualty industry to manage. In the property/casualty arena, ERM is the solution DFA was searching to solve. The industry is at the cusp of rip currents of slowing resistance by the nay–sayers. Although assigning numerical values to the benefits of ERM continues to be elusive, empirical evidence of change in the way risk, return and value creation are managed in strategic planning shows clear signs of what ERM is bringing to the industry and provides self–evidence proving its stage in its evolution. As a profession, we need to continue to lead in the ERM arena. Our research and initiatives a decade ago in the DFA era provide dividends today, just as our research today will bring dividends to the industry a decade from now. I look forward to our profession leading this charge through phase three in the ERM evolution. We are almost there. Let's keep talking. Our employers, clients and society at large are listening.

Robert Wolf, FCAS, MAAA, is a staff actuary for the Society of Actuaries. He can be reached at rwolf@soa.org.

Sidebar: Learn More about ERM!

Several sessions on Enterprise Risk Management (ERM) are planned for the SOA 08 Annual Meeting & Exhibit, October 19–22 at the Orlando World Center Marriott Resort in Orlando, Fla. Here's a listing of a few. For more information, visit the Annual Meeting page on the SOA Web site at SOAAnnualMeeting.org.

ERM: Opportunities for Actuaries to Make a Difference

Learn about the fundamental concepts of ERM and how it differs from traditional risk management practices.

Integrating Economic Capital and Enterprise Risk Management

Gain insight into how companies are integrating economic capital and ERM frameworks.

Enterprise Risk Management for Smaller Companies

Learn how a smaller insurance company has implemented an ERM process and how it has helped it to manage its business.

The Implications of ERM

Get an inside look at how ERM is changing the insurance industry.