By John Bowers, Actuarial Product Director at RNA Analytics
Whether led by the actuarial or finance department; opting for integrated software (measurement engine plus accounting engine); or completing measurements in existing actuarial software and then outputting results to sub-accounts, achieving automated data flow between upstream and downstream systems is central to success.
Separately, the role of the upper-layer measurement model/measurement platform under IFRS 17 is such that the efficiency of the platform will directly determine the overall implementation effectiveness of any IFRS 17 project.
Moreover, in seeking to establish the impact of software on implementation, it is useful to consider the following:
Can the design efficiency of a model affect the efficiency of measurements? Is the upper-layer measurement model that complies with IFRS 17 requirements directly purchased as integrated software? Or is it developed in close collaboration with users using the standard IFRS 17 model within actuarial software, achieving compliance with IFRS 17, in the simplest way possible?
Does the measurement model support the revaluation and recalibration as required by the standard, such as YTD? IFRS 17 offers the accounting policy option of YTD, requiring that each period's financial statements within the reporting year be measured directly from the end of the previous year to the reporting date. Further, during the actual process of producing financial statements, it is often necessary to test and adjust the results, requiring the measurement results to be recalibrated and recalculated. If the built-in logic of the model or software cannot strictly support YTD or make recalibration convenient, it will inevitably consume a significant amount of time and effort with each recalibration, with potentially severe efficiency downsides.
Is the measurement process visualised? Visualisation of the measurement process is beneficial for users to understand the model, and analyse the reasons for changes in reports. It also helps the relevant departments comprehend the calculation process, and facilitates the work of auditors. Additionally, this aspect is often associated with one of the biggest challenges and pain points in the implementation of IFRS 17: that of identifying the reasons for discrepancies in reports. We believe that all project implementation stakeholders should have deep insights into this issue.
Does the measurement model/software require substantial hardware support? During the implementation of IFRS 17, if the choice of measurement model/software is not carefully considered, the cost of the hardware configuration required to support the measurement model, and even the corresponding datacentre equipment, could become significant.
Does it include sub-accounts? In the implementation of IFRS 17, some insurers choose not to present detailed sub-accounts. Others, in looking to satisfy internal controls compliance and meet audit requirements, opt to present both accounts and generate sub-accounts and detailed accounts. Naturally, there will be significant difference in the complexity, resource burden and the cost of each approach.
A note on predictive capabilities
An increasing demand for enhanced functionality and efficiency in the predictive aspects of actuarial models, driven not just by IFRS 17 but also by solvency regulations and valuation assessments, has exposed certain deficiencies in traditional life insurance actuarial models.
For instance, both solvency stress testing and quarterly solvency reports require solvency predictions. Despite the relatively short forecasting horizon for solvency predictions, regulatory provisions still allow the use of simplified methods, such as the risk carrier factor approach, under certain conditions. In the context of embedded value and new business value assessments, where the minimum capital prediction period is longer, the existing Embedded Value (EV) approach does not impose restrictions, allowing the use of methods for simplified calculations.
The permission to use these simplified methods is evidently associated with the limitations of traditional life insurance actuarial models in predictive functionality. This association leads to a situation where, for practical operability, a compromise may be necessary, sacrificing some precision and rationality in solvency predictions and value assessments.
Furthermore, the implementation of IFRS 17, which requires simultaneous prediction of future cash flows at the time of assessment, compels insurers to confront issues related to model predictions.
As insurers around the globe continue to report under the standard, it will gradually become easier to more accurately quantify the tangible impact of dedicated actuarial software on outcomes in the implementation of IFRS 17. Already, though, it is becoming apparent that property insurance companies have begun to use life insurance actuarial software for actuarial assessments – a development of note in an industry where the pace of regulatory change shows no signs of slowing down any time soon.
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