Direct approach to assess risk adjustment under IFRS 17

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.

Uso de las probabilidades en la preparación de información financiera: perspectivas desde las Normas Internacionales de Información Financiera

“…Berardi (2022) confirmó la importancia de las expectativas frente a eventos futuros, ya que podrían desencadenar diversos resultados, como se mencionó en el trabajo de Chiahemba y Ibiamke (2019), y esto tiene un impacto en la toma de decisiones, que como señaló Gómez (2004), se ve influenciada por las creencias asumidas. En ese sentido, dichos trabajos aportaron aspectos relevantes en el análisis / QUIPUKAMAYOC del concepto de probabilidad en las NIIF y se confirmó el uso de la probabilidad en modelos de pérdida crediticia según NIIF 9 (Brito & Júdice, 2023;Đurović, 2019;Delgado-Vaquero et al, 2020) y ajuste del riesgo según NIIF 17 (Signorelli et al, 2023). Esto indica que su uso es relevante para la estimación de escenarios.…”

“…Por su parte, Brito y Júdice (2023), Đurović (2019) y Delgado-Vaquero et al (2020) llevaron a cabo diversos estudios orientados a un modelo de pérdida crediticia basado en probabilidades de incumplimiento prospectivas bajo las consideraciones de la NIIF 9. Además, Signorelli et al (2023) se centraron en la distribución de probabilidad para el ajuste de riesgo de acuerdo con los requerimientos de la NIIF 17.…”