Divergent Approaches
Like many first-order labels, "financial services sector" suggests a degree of homogeneity that quickly departs from reality. It gets you to a general region, where the neighborhoods and even streets can vastly differ. And so it is with the management of inflation by different businesses and institutions across financial services. While participants in the “region” of capital markets have been obsessed with inflation and all its dimensions for time and eternity, in the insurance markets it has historically been a secondary consideration for many companies. This distinction had nothing to do with relative importance and more to do with (1) actuarial science dominating one culture and applied economics dominating the other, (2) until recently, an extended period of low to moderate inflation, and (3) analytical challenges.
Insurers often assume and transfer inflation risk related to claims and policy benefits. Strategies vary by line of business, including the ways (if at all) institutions isolate, model, and price this risk through the different stages of transfer, starting with initial coverage (unless explicitly excluded) to ultimate factor payment or policy expiration. Certain products having fixed benefits, primarily in the life segment, will attach purchasing power protection through various optional riders. In contrast, many P&C, healthcare, and other life products embed inflation cover, then increase premiums and/or charge indirectly by holding or reducing policy limits when inflation increases claims. Lines especially hard hit by inflation include long-term care, worker's compensation, and residential property exposed to supply change problems.
As with other risks, different players in the insurance ecosystem have different roles:
- The insured's risk profile impacts the probability of claims, which bundle inflation costs with losses.
- The primary insurer's inferred or explicit coverage initiates the risk transfer process.
- The reinsurer offers excess-of-loss (XoL) treaty cover to the ceding company for catastrophic events.
There is nothing unique here in the broader context of the insurance business. However, unlike many other risks, the treatment of inflation is less granular regarding the specific profile, tail vs. non-tail risk, and often lacks asset-liability rigor including specialized portfolio strategies and effective hedges. Blunt premium loads are introduced annually. Claims and benefits are paid. On the asset side of the balance sheet, portfolio construction for inflation is largely independent of payout expectations for liabilities, with some exceptions (life riders, etc.). Real assets are added to portfolios ("just buy gold"). Hedge accounting treatment is often out of the question. In summary, many companies don’t manage the risk with informed intensity despite the significant financial implications, including capital efficiency.
The Opportunity -- Risk Management
These conditions create a significant opportunity for insurers and reinsurers. As much as we would like to say so, the risk-management framework that exploits this opportunity is not innovative. However, the framework's application to inflation, and the expertise required to do so, is different.
Step 1: Know and express, quantitatively, the specific inflation profile of your book as well as you know its other risk attributes. This has always been the heavier lifting on the inflation challenge. But more data and new models are lightening the load. An effective metric would be a Customized (and risk-adjusted) Inflation Factor Index (CIFI) that best approximates the inflation sources and tenors assumed by the primary company. The ability to generate/update CIFI will depend on the data quality, structure, and availability needed to "weight and rate" index components. While there are challenges, all the relevant internal and external data exists. With new technologies, management can overcome these challenges. We outline one such process below. There are many variations.
CIFI's starting point is ERM's dollar expression for the line of business (LOB) exposure to a tail event. The team would modify this forward-looking picture in two ways: (1) through simulation or deterministic methods, adjust the exposure to near-term expectations rather than a tail event, and (2) using specific claims patterns and reserve data, allocate the total exposure to various coverages within the policy, effectively setting raw CIFI factor weights. For example, the process would disaggregate the current dollar exposures in the property LOB to building materials (replacement costs), labor availability (construction costs), and temporary living expense reimbursement coverage (displacement costs).
An inflation underwriter would then risk-rate each coverage exposure to adjust raw CIFI weights for their relative inflation risk. Models deployed by claims professionals can help them identify price indices having the closest linkage to the different coverages. There is a mind-boggling array of public and corporate pricing data available. But beware of spurious correlations such as oil imports from Saudi Arabia and the price of bananas (https://tylervigen.com)! Historic and near-term expectations for the coverage-relevant price series, or a group, represent a proxy for the inflation risk in each component. While building material costs may have a smaller weight than the associated labor costs, the former may have a risk score twice as sensitive to inflation as the latter. Similarly, the potential cost of living expense reimbursement may have a smaller weight (many people stay in their homes despite damage) but could be the factor with the highest sensitivity to inflation because of a housing shortage. The underwriter could refine the rating with modifiers such as the location tied to weather (Polk vs. Miami-Dade, etc.) or probability of litigation (plaintiff-friendly jurisdictions) for social inflation. Specific methodologies can be used to eliminate consideration of coverage exposures having small weights and low sensitivity ratings to focus on statistically significant sources of inflation risk.
Step 2: Bifurcate the inflation loss distribution and own the frequency or the severity, but not both. This separation aligns with traditional insurance enterprise roles and newer risk transfer mechanisms (examples below). It also enables significant efficiencies in portfolio management, as described in Step 3.
In the following bifurcation examples, participants define Inflation CATs (ICs) as an economic parameter that exceeds a CIFI acceleration threshold—a minimum increase within a maximum/brief time window (similar to an out-of-the-money option). This bifurcation enables several implementation alternatives, each with a unique set of tradeoffs but all with an IC-dependent trigger for a cost. The following are only a few examples.
- An IC-triggered drop-down attachment point in excess-of-loss (XoL) treaties. In the event of an IC taking place while a treaty is in force, the policy will drop the attachment point. By inclusion in an indemnification contract, this coverage avoids the likely derivative treatment that would be associated with a standalone policy. Economically, the lower limit effectively preserves capacity for non-inflation indemnification. The conventional loss occurrence clause in the treaty remains intact in this option (and those below.)
- An IC-triggered higher limit feature in XoL treaties. In this permutation, the insurance company could purchase an IC-dependent rider to raise the treaty limit in case of an IC. With this rider, the cedent retains a smaller layer of inflation risk while transferring escalating inflation costs to a reinsurer as an integral part of claims.
- An XoL treaty structure that separates insurance exposure by (1) setting a limit based on insured values at policy inception and (2) offering supplemental first-dollar coverage with a limit tied to the increase in values approximated by the change in CIFI.
- A parametric transaction with protection triggered exclusively by an IC.
One of the appeals to transferring the IC loss cost to a certified reinsurer (or directly to investors), who often has a business model and operations designed to complement a primary company, is that the insurer reduces the overall scale of the economic risk and the related hedging/accounting challenges. Another benefit is that the retained liability pattern has less amplitude, which makes ALM management less difficult. While not assured, “hedge-effective” accounting treatment may be possible.
What about pricing? We don’t know, but the much smaller inflation load on the narrow layer of retained risk and the out-of-the-money option premium for IC cover may, in combination, have a lower cost to pass on than the larger premium loads on the front end now in use. Improved results become even more likely with the differing portfolio strategies, customized for both types of enterprise, covered in Step 3. Superior risk strategies have a long history of improving financial benefits.
Step 3: Build specialized investment portfolios, introducing a more engineered ALM approach. A CIFI enables more tailored contributions to inflation risk management. The index represents a benchmark and set of constraints against which a specialized manager should construct a portfolio, and senior management can evaluate performance.
The portfolio manager needs expertise in the availability and pricing of CIFI’s inflation factors (benchmark constraints) in various instruments, including derivatives. For example, while pharma equities have healthcare inflation beta, it is the second or third largest signal in these securities, usually subsumed by general equity beta and associated valuation noise. While not perfect, stripping dividends for the CIFI portfolio purifies the inflation beta in these securities. Extracting inflation factors corresponding to those identified for coverage exposures (above) establishes the common currency needed for ALM. Easier said than done, but now within reach of data science and product innovation. In the latter case, the anticipated exchange trading of health care and CPI futures for subcomponents will also remove significant basis risk for certain LOBs. We have designed these instruments in the past and are encouraged by our discussions on recent developments where issuance is likely.
The investment mandate starts with the design of an earmarked portfolio that best approximates CIFI’s inflation factors. The scale and composition of this “completion” portfolio recognize the inflation attributes in all other holdings as part of a rebalancing analysis. Once the CIFI benchmark is defined, a manager can take active bets with different securities -- including some with low inflation beta but high return prospects -- while still in general compliance with CIFI constraints using all the conventional tools and advanced models available for benchmark portfolio management today.
As always, active management latitude in this classic form needs guideline limits to preserve the ALM capital benefits that CIFI enables, and these could be very substantial. For example, CIFI creates an economic inflation basis (where none exists currently) which, in combination with the design of expected inflation futures contracts, creates a macro hedge that is more liability aware. However, the opportunity is even greater if sponsors achieve hedge-qualifying regulatory treatment.
There are certainly challenges to attaining the status of “hedge-effective” (credibility of metric, reliable computation of market value, statistical correspondence1, etc.). However, these same measurement challenges have been overcome with other risks, such as interest rates and credit. In this instance the incentive in capital efficiency is greater by order of magnitude, because the result would dramatically reduce RBC charges for certain higher return assets (CPI futures contracts, etc.) that are not eligible for “speculation” but are for hedging.
Another strategy that reduces basis risk could be an SPV with various collateral structures that explicitly perfect the CIFI cash-matching requirements needed for hedge accounting treatment. Due to the high capital charges for some inflation-benefitting assets, SPV funding costs (the equity tranche) should be much lower but remain attractive to potential sponsors.
While all the above applies to both primary underwriters and reinsurers, a significant investment benefit for each is derived simply from separating inflation loss frequency from severity. This distinction enables customized portfolio design that captures very different businesses and roles in the risk transfer chain. Generally, primary company inflation portfolios will include more private market holdings and have an income tilt. Conversely, reinsurers will lean toward total return and liquidity, consistent with CAT insurers’ lower balance sheet leverage. The absence of these separate risk ownership roles and associated investment strategies may explain why some previous efforts to match inflation assets with reserves have yet to fully achieve the desired results.
Step 4: Monitor and actively manage the revealed basis from both sides of the balance sheet by updating the liability index and, if needed, rebalancing the inflation portfolio to widen or narrow the basis depending on conditions and objectives. Standing operating procedure.
Operational Improvements
The potential benefits envisioned with the three Steps of this program include a lower cost of capital and sharper asset allocation. We believe rating agencies and regulators will view this inflation risk management initiative favorably, and our initial discussions and recent regulatory publications support this expectation2. Given the visibility of inflation risk, management and boards (like regulators) should welcome these additions to the risk-control arsenal. Modest reductions in required capital resulting from these improvements could expand ROE with potentially greater effectiveness than taking on additional overpriced investment risk (credit, illiquidity, etc.) or operating leverage. Increasing the scope of risk management always expands strategic financial alternatives.
Moving Forward
Inflation accounts for an increasingly large portion of insurance payments in certain lines and has become a critical topic for many boards and senior management teams. The escalating cost of insurance has, in turn, gained increasing attention in discussions surrounding the national economy. Of course, no one is saying “just buy gold” (now from Costco). Serious efforts by many very talented people in this business are underway. We all recognize the industry's current state needs to catch up to impressive advances taking place in many other areas of the business. The most successful financial intermediaries inevitably excel in actively managing all significant risks, even if imperfectly. Economic opportunities for these entities are sometimes greatest because spread risk is messy, as these conditions create new paths for those looking to set them. Companies that have developed analytically sound methods for managing inflation risk while avoiding a false sense of precision will have a competitive edge. We hope any flaws in our recommended game plan (errors of omission, understated difficulty, etc.) elicit additional ideas and collaboration.
We appreciate the differing opinions and contributions of several executives who scrutinized our ideas before this publication. Given their commitment to the industry’s future, we are not surprised by their enthusiasm for providing this input. But considering the demands on their time, we remain humbled by their involvement.
Bill Poutsiaka, Enterprise Driven Investing, LLC
Michael Ashton, Enduring Investments
Amnon Levy, Bridgeway Analytics
According to the Accounting Practices and Procedures Manual (AP&P Manual), a hedge is generally considered effective when “the change in fair value (cash flows or present value of cash flows) of the derivatives hedging instrument is within 80 to 125 percent of the opposite change in fair value (cash flows or present value of cash flows) of the hedged item attributable to the hedged risk.” A hedge can also be designated as effective “when an R-squared of .80 or higher is achieved when using a regression analysis technique.” Source: NAIC Capital Markets Special Report; U.S. Insurance Industry’s Exposure to Derivatives Reaches $3 Trillion in Notional Value at Year-End 2021; Michele Wong and Jean-Baptiste Carelus.
Prudential Regulation Authority Business Plan 2024/25; April 11, 2024. “The PRA expects a continued lag in the emergence of claims inflation in the data, which insurers should be alert to. The PRA will continue to monitor the ongoing impact through regulatory data collected and supervisory activities through 2024.”
