Balancing actuarial and underwriting priorities in insurance pricing. Can you find the perfect equilibrium?

Actuarial projections should not be used as sole basis for decision-making; they are indicators based on previous experiences and available data. The accuracy of the projections is depends on data quality and availability. Management, risk teams, and underwriting can use this data as one of many inputs when designing real-world plans. Organizations can improve accuracy by incorporating extra variables such as current temperatures and sea levels into catastrophic loss data. By giving suitable weight to various variables, a balanced and dynamic formula can be developed. This approach enables management to compare previous facts to future predictions, resulting in a more complete awareness of potential risks and more informed decision-making.

There is an assumption that actuaries are not tuned in to ground realities because they do not work in the field. While it may be true to some extent, but actuaries and underwriters do work together to construct a sound bridge between mathematics and validation of assumptions (based on experience of underwriters of those in the field). Actuaries or anyone who works with data isn't detached from real-world insights. If, however, there is in fact such a disconnect, the firm should enable a setting in which both actuaries and underwriters are working together with space to question. The term actuarial insight cannot be and should not be a standalone component. This insight should take into account inputs from the on-ground teams.

Actuarial models and underwriters' risk evaluation are two sides of the same coin. When both of these come together in perfect harmony, the outcome is risk management at its best (or close enough to best). Actuaries should be encouraged to spend more time with underwriters not only at the time of pricing a specific policy, but also to understand the nuances that only an experienced underwriter can shed light on.

Two insurance companies, A and B, both insure a government universal health scheme using actuarial methods based on historical data, expected claims, and the number of insured families. Company A integrates subjective insights from its underwriters, who adjust risk profiles based on personal experience and intuition. This approach can lead to more aggressive pricing or coverage, potentially resulting in higher profits or significant losses, depending on the accuracy of their judgments. In contrast, Company B relies strictly on actuarial models, adopting a more conservative approach. This ensures more predictable outcomes but might also mean missed opportunities for higher returns or growth. Risk appetitte and experience plays a major role.

In my opinion, balancing actuarial analysis and underwriting is critical to effective insurance. Consider a house insuramce policy. Actuarial data may indicate higher premiums for homes in flood-prone zones. However, if underwriting considers elements such as recent flood defense investments, a history of proactive maintenance, and the homeowner's participation in community risk reduction programs, they can provide a more personalized and equitable premium. This complex approach not only represents the genuine risk, but also indicates a concern for individual circumstances. Insurers who thrive at this balance develop deeper customer relationships, increase satisfaction, and promote their reputation by demonstrating optimum pricing.