Beyond IFRS 17: Data integration is a huge opportunity for insurance finance, not a compliance-related chore
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Many insurance CFOs are updating their data architecture in direct response to upcoming regulatory changes. However, as Sempre insurance sector lead, Stephen Pass explains, this should not be seen as yet another operational expense to be begrudgingly approved.
If data from across the organisation is integrated, if its quality is ensured and if it is made readily available, the whole business can benefit. This goes way beyond ticking the compliance boxes: it’s about reinforcing the finance function’s position at the centre of decision-making, and boosting business resilience.
1. IFRS 17 might be the trigger for data transformation, but it’s just the beginning…
After a Covid-related reprieve, the deferred effective date for IFRS 17 is set for 1 January 2023.
The topline aim of the new regime is to establish “unified standards for insurance contracts, related accounting, valuation and reporting for enterprises’ assets and liabilities”.
In practice, it means that the financial, actuarial and risk aspects of your operations can no longer be treated as separate areas. If data silos exist between finance and operations, as well as between different divisions within the business, achieving and maintaining compliance is going to be a huge struggle.
Currently, one of the most pressing questions we field from insurance finance leaders is, “What changes do we need to make to achieve compliance?”, along with “Can we report what we need to disclose, accurately, and on time?”.
The answer often involves lifting and moving organisational data into a centralised data repository e.g. a data lake. We ensure that silos are removed, so information from all areas of the business can be viewed in one place. We also ensure that optimal management processes are in place to ensure data quality.
From this foundation, many insurers go a step further, implementing an end-to-end solution covering all the calculations, allocations, impact assessments and disclosures required for IFRS 17 compliance.
None of this is foolproof: successful implementation requires a combination of data expertise and insurance sector knowledge. This is not a stop gap to fix a specific compliance challenge, its benefits extend far beyond IFRS 17…
2. Easing your wider reporting burden
IFRS 17, GDPR and MiFID II/IDD all have at least one thing in common: they all focus on the need for transparency. Whether in relation to your own organisation’s financial position, the information you have on policyholders or IBI purchasing decisions, it’s increasingly assumed that you will be able to provide clear, accurate and granular information – both to the regulator and to customers.
We’re seeing it again with the move towards mandated climate-related financial disclosures (CFD). Organisations – insurers included – will ultimately be required to provide high-quality granular data on the impact of their operations and assets on climate change.
Recognise this direction of travel, and you realise that making your data integrated, accurate and available does not just help you get a handle on your current compliance workload. It also provides a framework for meeting future requirements – whatever form they may take.
And of course, for finance leaders, less time grappling with compliance means more time for focusing on business growth.
3. Better spending decisions: Supplying finance with a vantage point
Who are our policyholders and how much money are we making from them?
Are our products and applications still seen as being complex – have new disrupter business stolen a march on us?Are we focusing our resources in our most profitable areas?
These might seem obvious questions, but it’s surprising just how often they go under-addressed – at least at a business-wide level.
Good business development managers, senior underwriters, sales and retention executives will know their specific business divisions inside-out. But in deciding whether to scale or wind-down a particular offering, they are not necessarily analysing it from a business-wide perspective. It just isn’t in their division-specific remit.
This is where the finance function comes in.
Once data is integrated, available and optimised for quality, it enables successful implementation of self-service analytics and planning tools. The very best of these (IBM Planning Analytics and Anaplan among them) enable an approach increasingly referred to as extended planning and analytics (xP&A).
xP&A involves making your operational, financial and strategic data, as well as planning and analytics capabilities, available on a single platform. It means you can drill into the operational data – including on a policy or departmental level, analyse the level of resources it takes to service a particular offering or client, including workforce, marketing and commission spend.
Ask questions and run differing model scenarios (e.g. ‘What if we reduced promotional resources on x product by x%?’), and immediately get answers on what this means in terms of both operations (e.g. workforce requirements) as well as in terms of the business’ bottom line.
4. Evidence-based answers at the point of need
Updating your data architecture does not just boost the availability and utility of data that already exists within the business. It also makes it easier to integrate external data sources into your decision making.
To see the benefits this can bring to insurance firms, we’ll take the example of a professional indemnity division and rewind to the conclusion of the Stamp Duty Holiday in 2021. Early reports are of missed cut-offs and other errors by conveyancers, thereby increasing the company’s risk of exposure to professional negligence claims.
Using your analytics solution, and integrating very early data supplied by professional regulators, you can model what this might mean not just for your prof neg book, but for the financial position of the business as a whole.
Later, more concrete information arrives from both internal risk assessors and claims handlers, as well as from external sources. The beauty of integrated, cloud-based data architecture combined with self-service analytics is that as soon as new data arrives and the variables shift, you can instantly generate an updated predictive forecast.
Key business questions – for instance, around re-insurance options and reallocation of funds from one pot to another – can be answered rapidly, and with the most up-to-date information available.
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As a start, scalable, cloud-based data warehousing is the foundation for compliant reporting: especially in an age when regulators expect you to dig into the data to provide complete transparency.
But potentially much more valuable than this, it also opens the door to powerful decision making capabilities. It puts the finance function much closer to the core business, creating a clear link between operations, strategy and the financial health of the business.
About the Author
Stephen Pass, Sector Lead – Insurance & Professional Services
Stephen is a Sector Lead for Insurance and Professional Services at Sempre Analytics. Stephen brings with him a strong data and analytic background, having held positions in leading global companies such as Teradata and Lloyds Banking Group, this awarded him valuable international experience in enterprise level software and services sales strategy.
Stephen’s deep experience solving business problems helped the Banking and Insurance industry make the best of opportunities from digitalisation. His strategic approach in identifying and understanding the market direction from the customer needs, alliances and the competitive landscape enabled his clients to develop their data analytics roadmap to become more operationally efficient and truly data-driven.
