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Perspectives

IFRS 17: Data management and process improvement

A new era of insurance accounting

Implementing International Financial Reporting Standards (IFRS) 17 will bring significant changes to an entity’s process and systems and will require significant coordination between many functions of the business–notably between finance and actuarial. These changes can also create a fundamental shift in the way data is collected, stored, and analyzed, and can significantly impact business operations, financial systems, and forecast methodologies as they adjust to the new standard.

May 24, 2018

A blog post by Wallace Nuttycombe, principal, Deloitte & Touche LLP and Bryan Benjamin, senior manager, Deloitte & Touche LLP

The combination of demanding regulatory changes, big data requirements, and growing consumer expectations creates the opportunity to invest in proper data management solutions that enhance the data integration and automation in the insurance industry. Adopting IFRS 17 will likely be complicated, and preparedness is crucial; but is enough being done to prepare for such a significant change?

To help companies better prepare for IFRS 17 and implement the best solutions for the change, we explore what is driving this change in data functions, challenges that are likely to emerge, and tips to help a company find and implement the right solutions for the business.

How an organization manages and uses its data to derive business insights that are accurate and timely will be critical to its success.

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Drivers of increased data functions for IFRS 17 tech requirements

  • Increase in granular valuation requirements: The need to measure and report insurance liabilities using an explicit building blocks approach. The "building blocks" consist of the unbiased mean of best estimate cash flows, the development of Risk Adjustment (RA), and the Contractual Service Margin (CSM).
  • Restatement of prior year numbers: The need to complete a comprehensive data mining exercise to combine current and historical data to achieve the retrospective application requirements upon transition.
  • More detailed disclosure and reporting: The requirements of IFRS 17 will require significant change the chart of accounts, and the new financial information including extensive disclosures are going to be done at a level much more granular than what is done today.
  • Increase in use of market data: The need to measure discount rates based on current market interest rates—and tracking changes in discount rates at a "group of contracts" level—will necessitate obtaining, storing, and tracking interest rate data in a volume never before seen under current IFRS.
  • Segmentation of portfolios in annual profitability groups: The need to split each portfolio of insurance contracts into a minimum three separate annual profitability groups.
  • More data integration and automation: IFRS 17 requirements also accentuate the need to have high-quality data that is accurate to support the financial reporting process both to the market and for internal management consumption to direct the business. This creates pressure for more data integration and automation and strong, scalable, and flexible IT platforms that can support the financial reporting processes that operate in a well governed and controlled environment.

Current Challenges in finance and IT infrastructure for IFRS 17 implementation

Many insurance companies currently operate a fragmented and complex legacy infrastructure. This landscape often leads to high operational costs driven by significant duplication of data and processes by multiple stakeholders fulfilling similar demands.

To address these fundamental challenges, companies should ask themselves:

  1. What business needs do we need to address as a result of IFRS 17?
  2. How can we leverage our current IT infrastructure to address business and compliance needs?
  3. What data management solutions can we build or buy to address both business and compliance needs?

Let's start with the first question. Identifying the business needs to implement IFRS 17 is key and insurance companies will need to focus on and address the most critical needs to move forward.

What business needs do we need to address as a result of IFRS 17?

Efficiency: Data requirements will increase significantly from IFRS 17, but companies cannot let the increased volume result in less decision useful output. Companies will need to find solutions that can save time in processing the increased volume of data with the same, or even greater, efficiency than previous solutions.

Control framework: One of the key requirements under IFRS 17 is the need for accuracy and auditability of processes and data used in financial and solvency reporting. Companies will also need to provide reconciliations of different reporting balances to different stakeholders.

Disclosure requirements: IFRS 17 will increase the volume of disclosures in response to a need for a deeper explanation of what is already a more complex measurement approach to contracts and demand from investors for greater transparency of reported numbers.

Management information: Understanding how risks and return interact is intensive and requires timely and accurate data, so companies need to effectively manage their risks as well as enhance their returns.

How can we leverage our current IT infrastructure to address business and compliance needs?

A critical step for insurance companies will be to perform a current state IT assessment. For each system that forms part of the overall finance and actuarial IT architecture, a technical and business assessment should be performed to evaluate if the system is an appropriate platform for IFRS 17 and whether enhancements are required. This should be in progress now, or starting as soon as possible.

What data management solutions can we build or buy to address both business and compliance needs?

There are many things to understand when looking for and choosing the right data management solutions (DMS) for a company. Before choosing, first consider:

The maturity of a company's current finance and IT infrastructure: Insurance companies with more mature infrastructures will likely invest more on solutions that can help move them along their digital journey, while companies with less mature infrastructures should look to first getting the basics right.

The size, nature, and complexity of business operations: Big companies offering multiple products in different jurisdictions will need to invest much more in DMS to facilitate efficiency across the jurisdictions they operate in comparison to smaller companies. Do not lose sight of in-country regulations that may limit cross-border data storage.

The maturity of an insurance market and its regulatory environment: Companies operating in more mature insurance markets with regulatory environments that have already evolved to reflect the principles of IFRS 17 have generally made more investments in DMS than companies in other markets.1

There are a number of DMS available to companies, including digital solutions, automation, and centralization solutions to work within a company's unique requirements.

Digital solutions

Digital solutions include newer technologies available that can be used by the finance and actuarial functions to enhance their existing capabilities or provide new and different capabilities. These include:

  • Cloud computing: Cloud enables scalable, elastic technology to deliver on-demand services over the internet. Many adopters of cloud have derived significant cost benefits, although the highly fragmented and bespoke solutions present in some insurance functions can be challenging to move into the cloud.
  • In-memory computing: This refers to storing large data volumes in 'main memory' to get much faster response times. Given the expected large increase in data volumes resulting from IFRS 17, this can enable real-time analysis of quantities of data that were previously unimaginable.
  • Advanced analytics and visualization: Finance and actuarial functions can achieve new levels of insight and productivity by investing in tools that enable the enrichment of the current analytics processes. These include predictive modeling tools, enhanced planning, and forecasting techniques that can provide timely and accurate business insights in a format that is easily understandable.

Data automation solutions

  • Data manipulation technologies: This type of technology includes standard enterprise extract, transform, load (ETL) tools and more computational solutions such as R and some SAS technologies. These can be used in various processes that are currently manual or undocumented by applying automated processing solutions in targeted areas.
  • Robust spreadsheet solutions: Building workflows, robotic solutions to automate the interfaces between spreadsheets, or new software engineering principles to build and maintain spreadsheets are all solutions that can be used to maintain current spreadsheet processes but increase output through new technology.

Data centralization solutions

  • Data warehouses: These systems hold large quantities of structured data from the actuarial, finance, risk, asset, policy, and transactional sources. A data warehouse can provide highly robust solutions if properly implemented but can often be expensive.
  • Unstructured databases: This involves developing a store or 'data-lake' that holds the source data with limited transformation and relies more on powerful extraction and analysis technology, including in-memory computing.
  • Sub-ledger: This involves creating a sub-ledger within the existing systems to address specific data aggregation and reporting requirements. By developing a sub-ledger to store and process the granular data required to deliver the numbers and disclosures for IFRS 17, the general ledger can be better protected from the scale of the change.

Investing in DMS is a necessary step in addressing the business and compliance requirements of IFRS 17 and other related regulations (such as the Financial Accounting Standards Board's project on Targeted Improvements for Long Duration contracts–see our next blog post for an overview), but it is a significant undertaking. Given the non-negotiable IFRS 17 implementation timeline, these efforts should commence as soon as possible, starting with an assessment of the relevant business and compliance requirements. There is no "one size fits all" solution, and each company will need to develop its unique DMS; but investing in DMS that enhances automation and integration to work with the specific needs of the company is critical to a successful IFRS 17 implementation.

To learn more about the impact of IFRS 17 and how to prepare for the new change, take a look at our previous article that offers tips to better prepare for and implement the new standard.

References

1 Deloitte. Data management in the new world of insurance finance and actuarialaccessed May 1, 2018.

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This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication.

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