Insurance Contracts: A comprehensive evaluation of the readiness status and measurement models for implementation of Accounting Standard Ind AS 117 for Insurance Companies in India

Abstract

Insurance contracts globally are accounted for as per IFRS 17 and in India the equivalent accounting standard is Ind AS 117. However, the implementation of Ind AS 117 for insurance companies was initial notified to be effective April 1, 2024 but subsequently deferred to April 1, 2026. The existing (global) research studies IFRS 17 globally (but not Indian scenario) and this paper fills the research gap by being the first forward looking academic paper to examine in-depth the implementation of Ind AS 117 for Insurance companies in India and identify associated challenges. Insurers can evaluate liabilities of insurance contract by using one of the three models viz.  General Measurement Model (GMM), Premium Allocation Approach (PAA) or Variable Fee Approach (VFA). The study employed 72 technically qualified respondents for primary data survey from 12 insurance companies and their audit teams. Using appropriate statistical and econometric tools, the survey re-affirms that GMM Model is more suitable for long term contracts and suits Life Insurance businesses while PAA model is more suitable for short term contracts (up to one year) and suits general insurance businesses and VFA model is applicable for contracts with direct participation features and suits Unit Linked Insurance plans. Since GMM model is far more complex than PAA model and has higher level of data requirements and implementation challenges, therefore the cost of implementation will be higher for life insurance businesses (because of GMM model) than general insurance businesses. The study also evaluates the applicability of systems, major associated challenges and the data related technical requirements of each model. However, expert opinions are divided on whether PAA model will give similar results to GMM model. The other findings are that voluntary adoption of Ind AS 117 ahead of timeline, though permitted, appears difficult and that relatively smaller size insurance companies face more execution challenges. The study finds that data-identification challenges are central to achieve successful compliance with the accounting standard. Consequently, Ind AS 117 will also accelerate AI adoption in insurance as AI will help resolve data challenges and minimize manual processes. Finally, implementation of Ind AS 117 has already been postponed once (as is common with accounting standards) and this paper identifies major challenges ahead of deadlines and is important for regulators, standard-setters, practitioners and researchers alike to prevent another potential deferral and reduce uncertainty as well as compliance costs.