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How to Overcome IFRS 17’s Data Hurdles: Leaps and Bounds Required

Nov. 30 2020 by Grazia Cafagna, Director - Financial Services Solutions Management - CCH Tagetik

Reporting & Compliance

What does it take to master IFRS 17’s data requirements? To answer this question, let’s clarify what we mean by data mastery. FSN defines ‘data mastery’ as the ability to actively manage data as a corporate asset through tools that facilitate management and analysis in a way that delivers a competitive advantage. Data masters generate more effective business partnerships, delivering change and enjoying the high regard of the operational functions which they support. Meanwhile the laggards have to contend with under-developed processes that exhibit a lack of standardization and automation.”  

Data mastery involves the use of data and analytics to accelerate business-relevant insights that provide better decisions and deep understanding widely available throughout the enterprise.  It’s one of the fundamental processes in a digital transformation. While data mastery is largely a task of your ability to exploit data, it is a ground-up operation; data mastery begins with a data-driven foundation, which means automation and standardization at the base of every financial management processThis is especially true for IFRS 17 compliance. 

Even the most basic IFRS 17 compliance efforts require organizations to elevate the availability, quality, governance and handling of their contractual data; a task which seems basic enough, but quickly compounds in complexity when you consider the volumes of data that need to be sifted, sorted, and synthesized to satisfy this standard’s lengthy requisites 

The Most Common IFRS 17 Data Gaps 

While the data demands are long, we’re seeing organizations have the largest gaps in these three areas: 

No Central Data Repository and Difficult Normalization 

IFRS 17 requires you to gather data, centralize it, normalize it, process it, and then send it on for processing in cash flow and sending the journals to general ledger. The issue is data is spread throughout actuarial and risk. No one system has it all. And since data comes from all these different places, it needs to be normalized and enriched to be usable in an IFRS 17 platform. 

What’s more, the data requires is pretty granularIFRS 17 requires you to make cash flow data available by  unit of account in order to calculate your Contractual Service Margin (CSM). For those who’ve yet to digitize contractual information, this will entail a laborious and piecemeal process of extracting data from actuarial systems 

Lacking Financial Intelligence in Systems 

IFRS 17 requirements will have you running calculations on large volumes of data. Most of the systems finance teams have in place will require this information to be rekeyed by hand into spreadsheets or patched in from data silos across the organization. In-memory data processing is a critical capability for those wishing to create calculations quickly — so, everyone. 

Historical Data 

The full retrospective approach to IFRS 17 requires you to pull in historical data from the inception of contracts within your organization — potentially as far back as the 80s. That’s a lot of data and an equal amount of responsibility. You’ll have to unearth locked-in interest rates, historical coverage units and changes in non-economic assumptions, while ensuring the quality and availability of this data in a way that’s better than just cobbled together. Indeed, the availability of this data will determine the granularity you’ll have available in risk, CSM, and accounting engines.  

How CCH Tagetik Helps: 

  • Data Repository and IFRS 17 Subledger: CCH Tagetik’s centralized data engine houses granular financial and non-financial data from all corners of your organization and makes that information available at low, detailed levels. Our solution comes with a pre-configured IFRS 17 data model, an embedded workflow, and extensible modelling. 
  • Data Normalization, Enrichment, Data Quality Rules: Since our solution uses a centralized data engine, there’s no need for the lengthy normalization or extraction process from actuarial systems. It’s all right there for you, ready to be reported on. Our data quality checks are built-in and our controls automatic.
  • Data Processing and Financial Intelligence: Once your data is input or integrated into CCH Tagetik, our solution uses in-memory data processing to extract data and process calculations. You can use BBA, VFA, PA evaluation methods, understand cash flow details, and conduct onerous contract tests, simply and easily.  The result is near real-time information at your fingertips, fast calculations, and the ability to explore years, even decades, of data — down to detailed levels — without a long lag time.
  • Built-in Accounting Engine: Our accounting engine integrates into your IT landscape seamlessly. It has flexible mapping, which means DR/CR accounts and the option of one or multiple charts of accounts. It also has direct integration to general ledgers, which means you can draw data from and push data to your GLs.
  • Data Repository for All Current and Historical Contractual Data: It’s one thing to have a single source of financial data. It’s an entirely different thing to have a solution that manages financial AND non-financial data, like contractual data, which requires an entirely different set of dimensions that can vary by company, industry, and even contract type. CCH Tagetik for IFRS 17 gives you the flexibility to categorize and sort all your contractual data, as well as call upon it quickly.  

It doesn’t take a superhuman effort to become an IFRS 17 data master. It takes a super powered software 

Want to master your data and your IFRS 17 requirements in one fell swoop? Learn more about CCH Tagetik IFRS 17, download the whitepaper here!

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