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IFRS 17: More Than Technical Accounting

More than just compliance


In May 2017, the IASB issued a new insurance standard known as IFRS 17, which establishes principles for the recognition, measurement, presentation and disclosure of insurance contracts. The objective of IFRS 17 is to standardise the global insurance accounting landscape, thereby improving risk management, while simultaneously improving transparency and comparability of insurance contract information.


The new standard shares many characteristics with IFRS 9: Financial Instruments. IFRS 9 was issued by the IASB in July 2014 but proved difficult for banks to implement and operationalise in time to meet the effective deadline in January 2018. Both IFRS 9 and IFRS 17 aim to bring a more quantitative forward-looking approach to the accounting of affected credit exposures and insurance contracts. Both standards also introduce significant complexity in the granularity of required input data, calculations, results and disclosure requirements. Additionally, both require the cooperation and alignment of two separate functions within an organisation: Risk and Finance for banks and Actuarial and Finance for insurers.


However, the additional complexity, granularity and operating model changes associated with complying to these standards are not the core focus of many insurers. In fact, in some instances, these aspects are completely

neglected, as insurers are drawn into discussions about the technical accounting interpretations, actuarial modelling methodologies and other quantification challenges that IFRS 17 brings to the fore.


In our experience, neglecting these components and challenges have caused banks significant problems in their attempt to go live with IFRS 9, with some budgeting more to “fix” their IFRS 9 solutions than they had originally spent on implementation. Auditability, financial control and reconciliation, data driven disclosure as well as automated and governed data acquisition, are all proving very troublesome as banks attempt to find a better solution for their IFRS 9 compliance. In our opinion, banks should have ensured that these components received the same, if not more, attention than the complex quantitative models and methodologies that are now run with significant difficulty.


Whilst the quantitative and technical accounting components cannot be neglected, we advocate an IFRS 17 implementation approach that ensures a smooth transition to IFRS 17, by enabling an operational capability in the finance/accounting function, via optimised data architecture and data management. This operating capability will extend far beyond IFRS 17 and bring about significant general improvement in an insurer’s financial reporting function, thereby achieving considerably more than just IFRS 17 compliance.

"The additional complexity, granularity and operating model changes associated with complying to these standards are not the core focus of many insurers."

Critical components to solving the challenges



It is important to take a step back and look beyond the technical interpretation of IFRS 17, to the operational impact of the standard, and the significant impact it will have on data, systems and processes, as well as its requirement for a well-designed data architecture. IFRS 17 brings with it significant data complexity, especially relating to data granularity, auditability and lineage, hence the requirement for an appropriate data architecture to overcome these complexities.


Consider the following components of a successful IFRS 17 programme.



IFRS 17: Components for success 




  • Generating more granular results

  • Sourcing input data at a sufficiently granular level

  • Enabling auditability and lineage of data, assumptions and model actions

  • Improving data quality and governance

  • Developing a robust data architecture governance

1. Granularity of results


Previously, under IFRS 4, insurers were able to group insurance contracts at a higher level of aggregation. Under IFRS 17, however, insurers are required to create cohorts of insurance contracts according to three levels:

This grouping methodology will lead to an exponential increase in the volume and granularity of results (i.e. contractual service margin, cash flow profiles and risk margins) which need to be calculated in actuarial valuation models, accounted for in a GL structure or CSM sub-ledger, reconciled and interrogated.

2. Input data requirements  


The additional granularity in the grouping of contracts will require more granular input data for actuarial modelling and results disclosure. This additional granularity will include data on claims, premiums, direct and indirect costs and commissions, all at a contract level, to name a few. Furthermore, it is important that the IFRS 17 calculation input data be reconciled to the finance ledgers prior to it being consumed by the actuarial valuation models to ensure that the results meet accuracy and completeness requirements and to avoid onerous downstream reconciliation. From a disclosure requirement perspective, additional data requirements especially at a contract level, are equally important as insurers are required to disclose sufficient information capable of providing users of financial statements with a basis to assess the effect of contracts on an insurer’s financial position, financial performance and cash flow.

3. Auditability and lineage 


Under IFRS 17, an organisation’s data, systems and processes need to support the standard’s requirements on auditability, traceability and reproducibility. Actuarial models and the results they produce must become auditable reporting items, which involves the traceability and reproducibility of models’ input data, assumption sets and core model actions. The benefit of creating an operating capability that achieves auditability and lineage of IFRS 17 data, assumptions and actions, is that it ensures trust in the results produced. Such as operating capability also enables insurers to address regulatory and accounting requirements (i.e. BCBS239).[1]

4. Improved data quality and governance 


From an IFRS 17 perspective, the importance of creating a data quality and governance framework, that provides a mechanism for the rapid and effective resolution of data quality issues, cannot be overstated. It provides an organisation with a significant competitive advantage through lower costs, improved customer relations and increasingly consistent data across the organisation. More importantly, a robust data quality and governance framework creates trust in reporting, whether that relates to regulatory reporting or reporting that is more internally focused on productivity, customer activity or target achievements.

5. Data architecture - a critical component in solving the challenges



It is our opinion that the only way to overcome the significant operational challenges that IFRS 17 introduces, is to design a robust data architecture that can integrate data from different stages of the IFRS 17 process lifecycle. 

Enhanced data integration is emphasised by the IFRS 17 requirements regarding data granularity, accuracy and traceability to effectively support an insurer’s financial reporting process both internally and to the market. An effective integration should be capable of providing a single, unified data view by combining disparate source systems into a structured data framework. Through reduced data complexity, increased data availability and enhanced data integrity, a well-designed data integration approach will be able to deliver the IFRS 7 data requirements, as well as offer better insights and rapid decision making through improved business intelligence.


To achieve this we suggest the identification or creation of unique identifiers in the various data sets used for IFRS 17 reporting, to enable the required integration and allow insurers to follow an insurance contract from source to GL and vice versa. Proper design and implementation of a studious data architecture will provide the following benefits from a traceability, auditability and financial control perspective.

Where to from here? 



The IASB recently deferred the effective date for IFRS 17 by another year after the first deferment to 1 January 2022, thus, organisations must comply with the requirements for annual periods beginning on or after 1 January 2023. Nevertheless, organisations that find it desirable to perform a simulation and parallel run of their implemented IFRS 17 solutions will need to push a “readiness date” as soon as 1 February 2022, depending on the organisation’s financial period.


Regardless of an organisation’s choice of early adoption or not, we believe that the extension provided by the IASB provides a golden opportunity for organisations to ensure that they get the foundational elements right. This will enhance their IFRS 17 implementation efforts, ensuring they are more than just a costly compliance exercise. The additional time should be utilised to ensure that a robust and operationally sound solution is implemented.


To make use of this opportunity, organisations must, as a matter of urgency, assess the state of their data, systems and processes and consider whether they can handle the significant additional demands that IFRS 17 will place on them.

"Organisations must, as a matter of urgency, assess the state of their data, systems and processes."

How Monocle can help?



Monocle has helped many local and international insurers and banks with regulatory compliance and is regarded as an industry leader in assisting these organisations to implement sustainable solutions that address compliance demands. Monocle is currently assisting large insurers with IFRS 17 and using our deep knowledge of insurance, the regulatory requirements, as well as the data, systems and processes that underpin these requirements, we are able to design bespoke solutions. These bespoke solutions focus on embedding an effective data architecture and compliance process that will not only ensure insurers’ compliance with IFRS 17 in 2023, but also offer insurers the benefits of an operationally sound financial reporting function.


About Monocle



Monocle is a results-focused consulting firm, established in 2001, that specialises in banking and insurance. Our experienced consultants translate business and regulatory requirements into tangible and data-driven results to bridge the gap between business stakeholders and IT. In so doing, we believe in operating with integrity and transparency and working closely with our clients to determine and build a unique and pragmatic solution that will solve their challenges. At Monocle, we understand that institutional and subject matter expertise are critical to the success of any consulting engagement, therefore, we believe in having our projects overseen by senior consultants with years of experience. Over the last decade and a half, we have gained extensive institutional knowledge into all areas of financial services and have consulted in multiple regions including Africa, the UK, Scandinavia and Asia-Pacific.

[1]. BCBS239 refers to the Basel Committee on Banking Supervision’s standard number 239 titled, “Principles for effective risk data aggregation and risk reporting”. The standard’s overall objective is to strengthen banks’ risk data aggregation capabilities and risk reporting practices to enhance banks’ risk management and decision-making processes. Though the standard currently only applies to banks, we believe that, under South Africa’s new Twin Peaks regulatory model, insurers will, in future, have to comply with similar data aggregation requirements given the Prudential Authorities mandate to enhance financial stability and its responsibility of regulating both banks and insurers.

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