Less Talk, More Action NeededTo Improve Capital Management

Over the past few years, there has been considerable discussion over the issue of capital management.

For several years leading up to 2001, the industry was concerned about overcapitalization: too much capital chasing too little risk made for soft pricing and poor returns to shareholders. In the wake of recent catastrophes, discussions have turned to possible undercapitalization.

This points out the fact that capital management is not a static issue. Both risk exposures and available capital differ from firm to firm, and can change quickly over time.

The problem is that there is more talk than action over the issue of capital adequacy. What the industry needs is a more dynamic approach to capital management.

Effective capital management involves measuring required capital based on risk, and comparing it to available capital. Dynamic capital management involves updating calculations of required capital and measures of available capital routinely, and especially in the event of significant changes in the market.

An overcapitalized firm will earn sub-par returns for shareholders because the excess capital earns a risk-free rate of return–hardly what an equity investor expects. An undercapitalized firm runs too high a risk of bankruptcy in the event of a large risk event.

Stock companies need to worry about overcapitalization because share prices have suffered as returns-on-equity languished in mid single-digits during the period of overcapitalization in the late 90s. Mutual insurers may seem less affected, but they should worry about it because their mutual policyholders will figure out, over time, that the they are getting sub-par returns from the risks they are taking.

Insurers that are potentially undercapitalized in the wake of a large catastrophe need capital measurement models just as much. They need to know, on an economic basis, just how much capital they need to raise, reflecting both new information about risk exposures, and their diminished amount of available capital.

This article recommends an approach to dynamic capital management that is based on a simple three-step process:

Assess the capital required to cover a firms risks.

Compare actual capital to required capital.

Choose among a set of alternatives to align actual with required capital.

There is general agreement on the basic rationale by which capital requirements should be determined. Insurance companies hold capital to provide debt-holders and/or policyholders with a financial cushion against potential losses. The bigger the risk, the bigger the capital cushion that the firm requires if it is to maintain its financial strength. Conversely, the higher the firm's desired financial strength, the more capital the firm needs for a given level of risk.

There are three basic types of capital measurement models: rating agency models, custom-built models, and vendor models. Let's consider these in turn.

Rating agency models and industry rules of thumb are insufficient for capital management.

In the past, many insurers relied on the National Association of Insurance Commissioners or rating agencies' models when determining their capital requirements. Since the NAIC sets only minimum standards for capital adequacy, insurers began to use multiples of the NAIC requirement as a target for capital adequacy. For example, an insurer looking for an A-rating might target 2.5 times the NAIC risk-based capital.

Other firms relied on rating agency capital models for setting capital levels in line with their target debt ratings. These models would use capital-to-premium ratios to calculate required capital.

And some firms relied on simple industry rules-of-thumb, such as requiring a premium to surplus ratio of 2:1.

Over time, however, firms began to realize the drawbacks of these approaches:

Rating agency models are too general. These models incorporate industry-wide data and their results therefore address a hypothetical average firm. These models are necessarily “top-down” models because of their data limitations and so each firm is evaluated against the average risk of the industry, rather than according to its own risk profile.

Rating agency models are not granular enough. Because these models are designed to function in the aggregate, they cannot be used to determine the capital requirements needed for profitability measurements at the business line, product or customer levels.

Models that use a uniform premium-to-surplus ratio across all lines assume that all risks are priced appropriately. Unfortunately, this is never the case in the real world. Use of a constant ratio also ignores the fact that the volatility and payout patterns of losses vary significantly across different lines of business. Differences in reinsurance programs and structures also make it difficult to apply a standardized premium-to-surplus ratio.

Custom models are better, but can be difficult to implement in-house. A number of insurers have tried to build capital allocation models from scratch, but many have found the development process to be longer and more costly than they imagined. The reason is that it is difficult to assemble the right resources to get the job done, such as:

A multi-disciplinary team.

Building a good enterprise-wide capital model requires financial engineers, actuaries, modelers/programmers and business managers–all costly, scarce resources. There aren't many ways to cut corners, either: a team that lacks a financial engineer will likely get the asset risks wrong; a team that lacks an actuary will get the liability risks wrong.

Benchmark information.

In practice, every company finds that it is missing some of the internal data needed to perform an accurate risk assessment. The pragmatic solution is to use a benchmark/placeholder based on industry data, and then refine the parameters in the future as data are gathered.

Validation.

There are so many moving parts in a good capital model that it is difficult to know when you've got it right. To trust the results, it is important to test the model against an external benchmark. For example, some modelers run their models on the industry as a whole to verify that they come up with reasonable estimates.

Corporate buy-in.

As the name implies, an enterprise-wide capital model impacts all facets of the business. Thus it is essential that commitment to the model be received from the chief executive officer, chief financial officer, chief underwriter and chief actuary in order for the model to be implemented successfully.

Vendor models are on the rise. In response to the challenges of developing a custom model, several firms are offering models that allow insurers to calculate capital requirements. These models are collectively known as “dynamic financial analysis” models, and they come in two broad types: accounting-based simulation models and economic-based analytical models.

The bottom line is that the accounting-based simulation models are more flexible in generating output–the user can choose to look at many different views of the financial statements. However, this power brings responsibility: the user must know both which views are meaningful and how they can be produced. This means simulation-based models can be difficult to implement and use.

Economic-based analytical models are designed to calculate “economic capital.” They provide support for capital-related decision-making, such as return-on-equity targets, reinsurance optimization and risk-based pricing. (See related story.)

Because these models are designed to calculate capital requirements, they are generally easier to implement. ERisk, Risk Management Solutions and Oliver, Wyman & Company together have developed one such “risk-adjusted return on capital” model, P&C RAROC, in which the methodology for assessing the capital required to cover a firm's risks can be described by the four steps outlined below:

Define risk as the distribution of changes in value over a one-year time period.

Identify and characterize risk distributions.

Using proprietary data (or industry benchmarks, if data is insufficient), model the risk distribution at the desired level of granularity (say, lines of business). Each distribution is modeled using the best available techniques from the banking and insurance industries (credit risk analytics from banking, catastrophe risk analytics from insurance, for example)

Combine stand-alone risks using correlations.

Underwriting uncorrelated or partially correlated risks provides significant diversification benefit. Thus the risk distributions must take into account the correlations of the individual risks.

Using this combined risk distribution, and a company's solvency target (A, AA or AAA), quantify the total capital required to support all risks assumed by the firm.

Calculate contributory risk by activity.

The total economic capital required to support the firm is then allocated back to the individual activities (in this case, lines of business) based on each activity's relative contribution to the overall risk.

Having determined the economic capital required to support all of a firm's risks, the next step is to compare this figure with its available capital, as well as the capital needed to satisfy rating agencies or regulators (say, 2.5 times the NAIC risk-based capital number).

Note that adjustments to GAAP equity are needed to get a meaningful comparison of economic and available capital (such as discounting reserves and marking the investment portfolio to market). Note also that the rating agency capital requirement may be quite different from the economic capital requirement (for reasons cited earlier).

Comparisons of economic capital with capital levels required by rating agencies or regulators, and comparisons of economic capital with available capital, will bring a p-c insurer to the next and critical step of the capital management process–deciding what to do with the excess. (See related story.)

The concept outlined in this article is simple: measure capital required as a function of risk. Compare this to available capital. That's the first part of the process.

The next part of the process seems simple also: If you have too much, either give it back to shareholders or invest it productively. The payoff is dramatically better returns on equity than the competition.

While the entire process may be simple, putting it into practice has hitherto been more of a challenge. But now that both software-based and consulting- based solutions for measuring risk-based economic capital are becoming widely accepted, insurers have only their own inertia to blame for the industry's capital management problems.

Peter Nakada is Executive Vice President and head of consulting at ERisk in New York. Peter Ulrich is Managing Director of the Capital Management Group at Risk Management Solutions, in Newark, California. Ugur Koyluoglu is a Director in the Risk Management Practice at Oliver, Wyman & Company in New York.

Reproduced from National Underwriter Property & Casualty/Risk & Benefits Management Edition, November 5, 2001. Copyright 2001 by The National Underwriter Company in the serial publication. All rights reserved.Copyright in this article as an independent work may be held by the author.

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Less Talk, More Action Needed To Improve Capital Management

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