Direct approach to assess risk adjustment under IFRS 17

Прямой подход к оценке корректировки на риск в соответствии с МСФО (IFRS) 17
Thiago Signorelli, Carlos Heitor Campani, César Neves
2022-01-01

IFRS 17Monte Carlo simulationcollective risk theorynonfinancial risksrisk adjustment
ABSTRACT This paper aims to develop a method that can be adopted by insurers to assess the risk adjustment for nonfinancial risks (RA) required by International Financial Reporting Standards 17 (IFRS 17). Unlike other methods, the method proposed here directly returns the RA for each liability related to a group of insurance contracts: remaining coverage and incurred claims. Moreover, each portion of the RA is correctly allocated to the corresponding actuarial liability, which constitutes an advantage over other methods. The method follows IFRS 17 directives and contributes to standardize accounting practices of insurers around the world, thus increasing the degree of comparability between financial statements in different jurisdictions. This paper should be relevant for insurance companies, for insurance market supervisors and regulators, as well as for practitioners in general. The method takes advantage of the collective risk theory and of the Monte Carlo simulation technique to adjust probability distributions used to calculate two different loading factors that, when applied to the carrying amount of unearned premiums and to the expected present value of incurred claims, directly return the RA for each liability related to a group of insurance contracts: remaining coverage and incurred claims. Our results show that, for large-scale portfolios, the central limit theorem holds and the distributions used to assess the loading factors can be well approximated by the normal distribution. Additionally, the values obtained for each loading factor are small, which means that the RA is relatively low when compared to the carrying amount of unearned premiums and to the expected present value of incurred claims. This result is in line with the law of large numbers, which states that, for large-scale portfolios, the risk borne by the insurer becomes considerably lower, since it is easier to predict the behavior of aggregate future claims.
1
Collective risk theory and Monte Carlo simulation generate loading factors that, when applied to unearned premiums and expected present value of incurred claims, directly produce the risk adjustments.
2
For large portfolios, the central limit theorem supports approximating the relevant loading-factor distributions with normal distributions.
3
Loading factors are small in large-scale portfolios, indicating relatively low risk adjustments consistent with the law of large numbers and improved predictability of aggregate claims.
4
The method allocates each risk-adjustment portion to its corresponding actuarial liability, addressing an advantage over alternative approaches.
5
The paper develops a direct method for calculating IFRS 17 risk adjustment for nonfinancial risks separately for remaining coverage and incurred claims.

risk adjustment for nonfinancial risks (RA) in groups of insurance contracts, covering remaining coverage and incurred claims liabilities

direct assessment and allocation of the risk adjustment to the corresponding insurance liabilities under IFRS 17

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Publication Date
2022-01-01
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Authors
Thiago Signorelli
Carlos Heitor Campani
César Neves
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