In the middle of implementing the new IFRS rules for Financial Instruments, Insurance companies see now the new standard for Insurance Liabilities arise. After long discussions over years, the IASB committed in November 2016 on the effective date of Jan 1st, 2021 with the clear side-statement that it won´t consider to further postpone the adoption date of the regulations. Having the necessity of a comparison period in 2020, Insurance companies have now 3 years to prepare processes and software to support IFRS 17.

How to approach IFRS17? The task is huge:

  • Teaching a large number of life and non-life policy systems on how to do IFRS17 would result in a costly exercise…
  • Enhancing Actuarial Systems appears also not optimal – as they are not built as accounting systems

SAP proposes a 3rd option: establish a central subledger instance, with central methods, audit trail, General Ledger and Data Warehouse connections. The process most likely will look like:

  1. Register the policy information (on the most granular level) in the infrastructure. Gain auditability with a comprehensive versioning concept
  2. Store actuarial output like: Best Estimate Cash Flows, Risk Adjustment, Earning Patterns etc. in a pre-configured data container.
  3. Perform the monthly/quarterly closing, taking care about Initial Recognition for Building Block and other approaches, Subsequent Measurement, Calculating the CSM, Accrual/Deferral of the CSM etc.

SAP Accounting for Insurance Contracts out of the Insurance Analyzer Product Family acts as a central IFRS subledger in any Finance and Risk system architecture

 

THE BIG VISION beyond IFRS 17:

IFRS17 is a major task itself. SAP even broadens that vision and offers additional solutions within the Insurance Analyzer product family. Once established this subledger, customers can gain more value and insights:

  • measure profitability on single-contract level. Learn who are the most profitable customers, sales channels etc.
  • calculate Solvency II Pillar 1 and other Risk Based Capital models.

 

Think big, start small.

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