Insuring the Life Insurer

Reinsurance - How insurers bet against themselves

Buying insurance is like betting against yourself and winning.

Reinsurance is a risk management tool that life insurance companies use to transfer a portion of their risk to another insurance entity, known as the reinsurer.

The main reinsurance companies worldwide, often referred to as “the big players” in the industry are Munich Re, Swiss Re, Lloyds of London, and Berkshire Hathaway Reinsurance Group.

The top three goals of reinsurance include risk transfer, capital relief, and solvency improvement.

Risk Transfer

Risk transfer in reinsurance is the process by which an insurer (the ceding company) shifts the financial burden of certain risks to a reinsurer. Let \( L \) represent the total losses. If an insurer cedes a proportion \( c \) of the risk to a reinsurer, the losses retained by the insurer are \( (1 - c)L \), and the losses borne by the reinsurer are \( cL \).

If the total losses \( L \) are $1,000,000 and the ceding proportion \( c \) is 0.40, the losses retained by the insurer are \( (1 - 0.40) \times 1,000,000 = $600,000 \) and the losses borne by the reinsurer are \( 0.40 \times 1,000,000 = $400,000 \).

Capital Relief

Capital relief refers to the reduction in the required capital that an insurer must hold by transferring risk to a reinsurer. Let \( K \) be the required capital for a given risk exposure. With reinsurance, the required capital \( K’ \) is reduced to \( K’ = K(1 - c) \), where \( c \) is the proportion of risk ceded.

If the required capital \( K \) is $5,000,000 and the ceding proportion \( c \) is 0.50, the new required capital \( K’ \) is \( 5,000,000 \times (1 - 0.50) = $2,500,000 \).

Improved Solvency

Solvency improvement through reinsurance involves enhancing the financial stability of an insurer by reducing potential large claims and providing additional financial resources from the reinsurer. The solvency ratio \( S \) is given by \( S = \frac{A}{L} \), where \( A \) is the total assets and \( L \) is the total liabilities. Reinsurance helps improve \( S \) by reducing \( L \).

If an insurer has total assets \( A \) of $10,000,000 and total liabilities \( L \) of $8,000,000, the solvency ratio \( S \) is \( \frac{10,000,000}{8,000,000} = 1.25 \). With reinsurance reducing liabilities by $1,000,000, the new solvency ratio is \( \frac{10,000,000}{7,000,000} = 1.43 \).

How Much to Reinsure?

Actuaries use several methods and considerations to determine the appropriate amount of reinsurance for a given portfolio:

Risk Assessment

Risk assessment involves evaluating the risk characteristics of the insurance portfolio, including mortality rates, policy types, sum assured amounts, and historical claims experience. Let \( X_i \) represent individual risks, where \( i = 1, 2, \ldots, n \). The total risk exposure \( R \) is given by \( R = \sum_{i=1}^n X_i \). Reinsurance is determined based on the aggregated risk \( R \).

If an insurer has 5 policies with individual risks \( X_1 = 100,000 \), \( X_2 = 200,000 \), \( X_3 = 150,000 \), \( X_4 = 250,000 \), and \( X_5 = 300,000 \), the total risk exposure \( R \) is \( \sum_{i=1}^{5} X_i = $1,000,000 \).

Retention Limits

Retention limits are the maximum amounts of risk that an insurer is willing to retain on a single policy or risk. When the insurer’s retention limit is \( R_{\text{lim}} \) and the total risk is \( R \), the amount ceded to reinsurers \( R_c \) is \( R_c = R - R_{\text{lim}} \) for \( R > R_{\text{lim}} \).

If the total risk \( R \) is $1,000,000 and the insurer’s retention limit \( R_{\text{lim}} \) is $500,000, the amount ceded to reinsurers \( R_c \) is \( 1,000,000 - 500,000 = $500,000 \).

Catastrophic Risk Modeling

Catastrophic risk modeling involves estimating potential losses from extreme events to determine the necessary reinsurance coverage. Let \( L_{\text{cat}} \) represent the losses from catastrophic events. The reinsurance coverage required \( R_{\text{cat}} \) is determined by \( R_{\text{cat}} = P(L_{\text{cat}}) \times E(L_{\text{cat}}) \), where \( P \) is the probability of the event and \( E \) is the expected loss.

If the probability \( P \) of a catastrophic event is 0.01 and the expected loss \( E \) from such an event is $10,000,000, the reinsurance coverage required \( R_{\text{cat}} \) is \( 0.01 \times 10,000,000 = $100,000 \).

Cost-Benefit Analysis

Cost-benefit analysis involves comparing the cost of reinsurance premiums with the benefits of risk transfer and capital relief. Let \( C_{\text{prem}} \) be the cost of reinsurance premiums and \( B_{\text{RT}} \) be the benefits of risk transfer. The net benefit \( NB \) is \( NB = B_{\text{RT}} - C_{\text{prem}} \). Reinsurance is optimal when \( NB > 0 \).

If the cost of reinsurance premiums \( C_{\text{prem}} \) is $200,000 and the benefits of risk transfer \( B_{\text{RT}} \) are $300,000, the net benefit \( NB \) is \( 300,000 - 200,000 = $100,000 \).

Regulatory Requirements

Regulatory requirements refer to the rules and guidelines set by regulatory bodies regarding the minimum levels of reinsurance required to ensure the financial stability of insurers. Let \( R_{\text{reg}} \) be the regulatory required reinsurance. The actual reinsurance \( R_{\text{act}} \) must satisfy \( R_{\text{act}} \geq R_{\text{reg}} \).

If the regulatory required reinsurance \( R_{\text{reg}} \) is $750,000, the insurer must ensure that the actual reinsurance \( R_{\text{act}} \) is at least $750,000.

Use Case for AI in Reinsurance

AI can significantly enhance the reinsurance process in life insurance. For example, AI algorithms can analyze vast amounts of historical data to identify patterns and predict future claims more accurately. Machine learning models can optimize retention limits by continuously learning from new data and adjusting recommendations based on real-time risk assessments. Additionally, AI can streamline the underwriting process by automating data collection and analysis, improving the efficiency and accuracy of reinsurance decisions. This helps in better risk management and enables insurers to offer more competitive and personalized products to their customers.