Sophisticated Pricing Builds Competitive Products — ④: Enterprise-Perspective Pricing

Authored by Jihyun Kim, Global Sales Executive RNA Analytics

Through the previous two articles, we introduced the need for a distributable-earnings metric that can represent the shareholder perspective — rather than the CSM metric alone — when pricing insurance products, and the Nested Scenario modeling methodology that can implement an appropriate projection of distributable earnings under the current IFRS 17/K-ICS regime. We showed that, by adopting Nested Scenario modeling, one can examine profit and capital impacts under a variety of scenarios at the pricing stage, reflect dynamic management strategy, and pursue a proactive pricing strategy grounded in forward-looking analysis.

Building on this, in this installment I introduce the usefulness of analysis that considers enterprise-level impact in pricing, and with that bring this pricing-methodology series to a close.

In pricing, profitability analysis is generally performed at the level of liability model points. This is a static approach in which assumptions such as costs and required capital are set at the product level, and profitability is tested under those given assumptions. Looking at pricing assumptions, however, many of them are elements determined at the whole-company level that are then artificially allocated for the purpose of model-point-level analysis; and strictly speaking, when a new product’s contracts come in and are combined with the in-force block, they also affect the level of the assumption elements applied in pricing.

Examining the enterprise-wide impact of new-business inflow alongside pricing can yield useful insights that unit-level profitability analysis alone cannot capture. Whereas unit profitability analysis is the basic method of testing whether an adequate margin is secured at the product-unit level against a given cost level, enterprise-perspective pricing can be described as a strategic tool for optimizing profit and capital at the enterprise level.

For example, consider a hypothetical situation of pricing an interest-rate-linked savings insurance product. Depending on the company’s pricing assumptions and pricing level, unit profitability analysis may yield a very low margin or, in severe cases, a negative margin. But suppose that, in this company’s in-force portfolio composition, liability duration is far longer than asset duration, so that interest-rate risk is large in K-ICS required capital. In that case, adding interest-rate-linked liabilities as new business at a meaningful scale would reduce the asset-liability duration gap and improve the capital position at the enterprise level. This is an opportunity of a different dimension from product-unit-level profitability. In this way, examining enterprise-level impact together with pricing analysis can, in some cases, lead to an enterprise-perspective optimal decision that differs from what one would conclude by looking at unit profitability analysis results alone.

From an enterprise perspective, whether pricing a particular new product is advantageous or disadvantageous depends on the state of the company’s existing in-force contracts and asset portfolio. Moreover, in enterprise-perspective pricing, one can go beyond merely confirming enterprise-level impact and comprehensively consider and propose approaches to the company’s sales and resource-management policies — such as product-portfolio strategy, asset-investment strategy, and cost allocation — in order to optimize the enterprise-wide contribution of adding the new product. This is an excellent way to effectively design an enterprise-optimization strategy through the product-pricing process and to achieve alignment at the level of enterprise-wide management.

On the technical side, the way to accurately measure the enterprise-wide effect of adding a new product is to run the in-force model both without and with the new product, and to take the difference in the values of the two cases for the key metrics of interest. Given the nature of pricing work — which requires rapidly testing a variety of scenarios — however, a process of running the full in-force model for every pricing test scenario is not realistic. As a practical solution, I recommend leveraging sensitivity tests of the in-force model. To this end, one builds into the company’s in-force projection model the capability to compute enterprise-level metrics such as asset-liability interaction and capital amounts at each future point, periodically performs sensitivity analyses for key scenarios of interest, and records and stores the results. Then, when pricing a product, one can refer to the sensitivity-analysis results computed in advance with the in-force model to estimate the new product’s enterprise-wide effect to an appropriate degree.

The emphasis, as an effect of adopting current-estimate-based IFRS 17 and K-ICS, on analyzing profit and capital impact when pricing products is, in broad terms, a desirable direction for the sound operation of insurance companies. At the same time, to survive and win in the industry’s fierce product competition, pricing analysis must become ever sharper and more sophisticated.

I hope this pricing-methodology series, which concludes with this installment, has been useful to insurance-company management wrestling with how to secure product competitiveness. A pricing function that adopts and actively leverages the shareholder-perspective pricing, Nested Scenario modeling, and enterprise-perspective pricing introduced through this series will, without a doubt, take a superior position in this fierce product competition.