Managing assets and liabilities: Methodology vs. Mythology

Like druids, witches and warlocks of ancient folklore, financial risk evaluators such as actuaries are generally treated by management of financial institutions with a degree of awe and suspicion. The mathematical risk recipes presented by these modern day wizards may as well be potions of batwings and toads in comparison with historical and standard business management philosophies. However, with the increasing volatility and sophistication of financial markets globally, insurers of the future will have little choice but to embrace scientific risk modeling in coordinating the management of their assets and liabilities, a recently released industry report states.

By coordinating the management of assets and liabilities, financial institutions can operate more soundly and profitably. This coordination is known as asset-liability management (ALM), the authors of a recently released Swiss Reinsurance Company report “Sigma” note. And, the authors observe, “despite its [ALM] significant potential benefits, few insurers have fully exploited what ALM can offer”.

The Sigma report points out that ALM as a concept has been in practice in the financial services industries since the 1970s – primarily in response to increased interest rate risk volatility. With the growing complexities of financial markets, a host of alternative mathematical risk models also evolved from the different financial sectors – thereby creating an added hindrance against broad acceptance of ALM by company managers. Not only has the abstract nature of ALM been difficult to grasp by operational management, but the lack of market standardization in its interpretation and application has further clouded the potential value on offer.

Indeed, most of the insurance spokespeople consulted in this article agree that ALM processes have not been widely accepted by company management. Some remain skeptical of the true benefits, while others believe that the growing cost-pressures being exerted on property and casualty insurers will necessitate a more efficient and scientific management approach to optimize the value of capital and assets.

The authors of the Sigma report also predict broader use of ALM in the future, primarily due to the global consolidation trend which through mergers and acquisitions has resulted in larger and more complex companies. The heightened value and stress on the long-term strategic value of these deals has placed greater emphasis on the due diligence processes and risk management tools employed. Furthermore, the Sigma report expects the shift by insurance regulators toward risk-based evaluation will add pressure on companies to implement ALM models. “Regulators and rating agencies are increasingly focusing on the ALM practices of the insurers they follow.”

Development of ALM

As previously noted, ALM was first applied by banks and life insurers in the 1970s as a result of increased interest rate risks (see chart, pg. 20). As the Sigma report notes, “from the Great Depression through the mid-1960s, the yield on long-term U.S. government securities stayed in a narrow range between 2% and 4.5%. So stable was this environment that bankers could follow an informal “3-6-3 rule: borrow from depositors at 3%, lend to others at 6%, and be on the golf course by three o’clock.” This abruptly changed in the 1970s when inflationary pressure drove interest rates upward.

The subsequent “high interest rate volatility period” of the 1970s saw several major insurers fail as a result of underwriting interest-sensitive products, the report notes. This prompted regulators to institute annual financial security tests on the industries they had been charged with – leading to the New York State Insurance Supervisor introducing in 1986 formal regulations for “basic asset/liability analysis”, or cashflow testing (CFT) on companies underwriting annuity or guaranteed investment certificate (GIC) business. In 1993, the National Association of Insurance Commissioners adopted a “Standard Evaluation Law” requiring all insurers to perform CFTs. Although CFTs provided a basic platform for ALM, the limited evaluation criteria applied then, and even today in minimum asset testing requirements of the insurance regulators, is far from “failsafe” in ensuring long-term financial soundness of companies’ market practices.

The Sigma report highlights two fairly recent company failures of inadequate matching of assets to liabilities.

In April 1997 Japan’s Nissan Mutual Life – with 1.2 million policyholders and assets of JPY2 trillion (US$17 billion) – was ordered to suspend business. The company sold individual annuities paying guaranteed rates of 5% to 5.5% without hedging these liabilities. A plunge in government bond yields to record low levels created a large gap between the interest rates Nissan Mutual had committed to pay and the returns earned from investments. Nissan Mutual was the first Japanese insurer to go bankrupt in five decades – with losses amounting to JPY300 billion.

Two years after the Nissan Mutual fiasco, U.S. General American Life ran into financial difficulties and was eventually sold to MetLife. The 66 year-old independent insurer, with US$14 billion in assets, had been downgraded in security rating by Moody’s Investors by one point from A2 to A3. This triggered an initial “bank run” by fund managers against General American totaling US$500 million. The insurer was able to meet these pay-outs as it held around US$2.5 billion in liquid assets. However, in a matter of days, investors sought to redeem a further US$4 billion in short-term debt instruments issued by the company. General American was unable to liquidate assets quickly enough to stem the outflow and was forced to be placed under state supervision. General American appears to have suffered from a mismatch between assets and liabilities, the Sigma report notes. “The proceeds from the [short-term debt] funding agreements were invested in less liquid, longer-term assets. In retrospect, the mismatch might seem obvious. Yet, at the time, regulators, independent actuaries and professional employees were either unaware of the redemption feature [of the debt instruments issued] or saw no need to change it.”

Defining the benefits of ALM

Asset and liability values are influenced by risk factors other than interest rates, the Sigma report notes. “To understand an organization’s risk profile, one must understand how these myriad risk factors relate to one another. An integrated risk model describes risks, their evolution, and their interconnections.”

In essence, the report points out, the value of ALM lies in allowing management to make better strategic choices, thereby enhancing competitiveness and financial security. The report suggests the following advantages:

Can the company reallocate its investments to boost returns, reduce risk – or both?

How much reinsurance should the company purchase? What type?

Are the company’s rates high enough to permit a satisfactory return on capital? Are they too high to be competitive?

How fast should the company aim to grow?

Should the company exit certain lines of business and enter others?

Will the acquisition it is considering add value to the firm?

Does the firm have enough capital to assure its continued solvency? Should its capital be financed differently?

Does the firm have excess capital it might re-deploy or distribute to shareholders?

In addition to the above internal company considerations, the Sigma report suggests at other “market related” factors that application of ALM would reduce the risk of. Firstly, the report observes, “the risk environment is constantly changing. Even if a firm holds its portfolio of assets and liabilities fixed, the risks to which it is exposed change due to industry competition, financial market fluctuations, and regulatory developments.” And, secondly, the report points to increasing “shareholder activism” whereby senior management of companies have been made more accountable for mistakes. This has lead to an overly cautious approach by management in decision-making and their desir e to accept risks in growing the business. “A careful ALM analysis certifies to regulators, rating agencies, investors, and the board of directors that a controversial action was appropriate in light of the best available information,” the report states.

P&C insurers and ALM

Although p&c insurers were the first to introduce a broader and more advanced ALM risk model known as “Dynamic Financial Analysis” (DFA) – which incorporates a larger scale risk simulation of a company’s operations – insurers have begun to fall behind the advancements made by the banking industry, says one of the Sigma report authors, Eric Thorlacius.

It is not really an issue of “who has the more advanced process” Thorlacius comments, “but the banks are ahead in applying common methodologies.” During the mid-1990s, the banking industry adopted “Value at Risk” (VAR) as a common ALM platform, which has since grown as the report describes “explosively”. The lack of communication and common understanding of ALM in insurer circles is the biggest setback facing the industry, he surmises. In fact, the Sigma report charges, “the greatest obstacle to ALM [in the p&c insurance industry] is the ‘silo mentality’ that prevails at many insurers, whereby investment and underwriting decisions are handled separately. Internal politics and clashes between ‘old school’ and ‘new school’ approaches to risk management help maintain these barriers.” Thorlacius concedes, however, that the “silo mentality” of the p&c industry is not an easy challenge to overcome. “This has been a hurdle in the industry’s path for sometime…it’s not a simple issue, it relates to the very nature of the industry’s structuring.”

Jim Falle, chief financial officer at Zurich Canada, concurs that insurers in Canada have not been overly enthusiastic in embracing ALM. “Actuaries have had the abilities [to apply scientific risk modeling] for years…but the procedures and processes have not been in place.”

However, Falle is hopeful that application and conformity of ALM will begin to take hold in the p&c industry. “The pressure on earnings is tremendous, and with the customer driving the price, it’s going to come down to efficient use of the balance sheet and capital to generate a profit.”

And, Falle believes there is growing support in the management ranks of insurers for a common scientific and integrated risk management approach. “There is a change of mentality evolving with regard to bringing together the underwriting and investment components of the business into a single risk-evaluated strategy. However, it’s really important to get everyone around the table, from claims and underwriting managers, to understand the philosophy.” In addition, he expects the risk-based approach adopted by the Office of the Superintendent of Financial Institutions (OSFI) will promote a more formal approach to ALM among insurers. “In this respect, the regulators are driving the industry in the right direction, however, their [regulators] ‘consumer bias’ toward requiring excessively strong surpluses can counter the true effectiveness of ALM.”

While the Sigma report hints at the fact that there are too many ALM type risk models floating around the industry – hence the lack of standardization – Falle has found the situation to be the contrary, “what really surprised me when I came into the insurance industry was the lack of ALM models available”. However, regardless of the number and sophistication of models on the market – which modern technology developments have inspired – Falle points out, “if you don’t understand your business, then even the most sophisticated model won’t help”.

ALM – another “love potion”?

Although ALM does provide some operational advantages, “it’s not Utopia,” comments Philip Wilson, vice president of finance at Royal & SunAlliance Canada. Though he agrees with the consensus that there is very little commonality in the application and language of ALM as practiced by insurers, “enterprise-wide risk evaluation is being developed and researched within the insurance industry. To say that we are in the ‘dark ages’ is not true.”

Wilson does not believe that the “silo mentality” criticism leveled by Swiss Re against insurers is justified in this context. While he admits that some barriers do exist between the underwriting and investment management in day-to-day operations, any drawback is overcome at the higher management level. “[The silo approach] is breaking down, I don’t think it is a big factor…most companies are doing a decent job of managing the various areas of the business.”

Wilson’s biggest concern with ALM models is that they tend to be rigid and rely on historical market data, and the expected repetition thereof, to produce meaningful results. “These mathematical models depend on historical patterns which means that they’re only effective if the same patterns repeat. Any risk model that is so rigorous that it can only point to one answer is usually far from the truth.”

Wawanesa Mutual Insurance Company president Gregg Hanson points out that the short-term nature of the p&c industry’s liabilities also negates much of the benefit offered by ALM models. “On the life side of business, where the liabilities are long-tail in nature, ALM is a big thing.” CGU Group Canada senior vice president of finance, Norman McIntyre, agrees with this perspective. ALM is not as advanced in use within the p&c sector as compared with the life industry, he observes, “but there is good reason for this in that there’s no strong correlation between insurers’ liabilities and interest rates”. In a broader risk picture, McIntyre confirms that CGU runs computer risk modeling, primarily on the investment side, but this is not coordinated with underwriting risk evaluation. At the end of the day, he notes, “we generally have enough new money coming in through premiums to meet claim costs”.

Graham Cudlipp of insurance management consultants GSC & Associates also believes there are greater benefits in having the various areas of the business managed separately. “I’m somewhat controversial in this regard, but I think there is more value in running the business components apart – of course, there has to be some matching of the assets and liabilities.”

Thorlacius counters the above arguments in pointing out that ALM risk modeling is not intended to replace the “human factor” in risk management decisions, but rather as a tool complementing the strategic management making process. “You can’t incorporate perceptions into forward planning models. We’re not suggesting that every management decision should come down to an algorithmic calculation – there has to be some human interpretation.”

Furthermore, ALM techniques combined with current technology data processing allows companies to run numerous risk-based simulations of their operations, the objective being to identify the most beneficial route of action, Thorlacius contends. “The real issue we’re trying to make is that there are greater benefits to be derived from ALM by establishing common standards.” This Cudlipp supports, “this has been a debate for over 10 years, it would be great to get some standardization in the application of ALM”. Overall, Thorlacius believes the Sigma report achieved its objective, that being to stimulate interest in standardization of ALM. “We have been really pleased with the level of positive feedback since the release of the report.”