Context

The International Accounting Standards Board (IASB) issued the new standard for insurance contracts – IFRS 17. It applies to annual reporting periods beginning on or after 1 January 2021.

IFRS 17 proposes considerable accounting changes and adoption of IFRS 17 will require massive information extraction from insurance policies within an insurance company notably around following topics

  • Reassessment and regrouping of existing insurance contracts: IFRS 17 has proposed three methods – Building book approach or General measurement model, Premium allocation approach, Variable fee approach – of valuing insurance contracts from inception. The insurance companies need to review their existing books of business and ascertain the contracts reclassification required for choosing the right measurement method. The additional IFRS 17 requirements for grouping contracts within a risk-portfolio are profitability (onerous/non-onerous/others) and contracts that are incepted not more than a year apart.
  • Data management: The contract grouping requirement as discussed above will present a huge data challenge for the insurance companies both while transitioning to IFRS 17 and in future. Huge amounts of historical data need to be analyzed and then aggregated to arrive at the transition-day requirements. Historical assumptions and experiences starting from the transition date will then need to be captured going forwards. The granularity at which the data is captured in the future and the sources of these data need to be clearly identified. There will be a need for increased data storage. Of particular importance will be the quality of data and its availability in a timely manner thus requiring controls and workflows to be in place.

Key words: IFRS17 Insurance Contracts Information Extraction Manual Review Contract Classification Analysis Aggregation Data Granularity

Why CODEXO

CODEXO turns 100% of the content of all contracts into an exhaustive, accurate and traceable data system that users can easily access and query across to

  • Reduce uncertainty for better decision making
  • Slash cost time and uncertainty for agile in depth audit & control at scale, and
  • Integrate over existing infrastructure seamlessly for immediate data agility without replacing legacy systems

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