Getting up to speed. Solvency II data and systems

9 Septembrie 2011

ERNST & YOUNG S.R.L.

 

Executive summary

Streamlined information technology systems and effective data management are core components of a Solvency II implementation initiative and key to the success of any business-driven program. Industry activity over the last 18 months has demonstrated that insurers recognize the importance of data quality in achieving Solvency II. Given the time pressures and broader change agenda, it is clear that data quality requirements continue to represent a major challenge and risk to many insurers’ ability to meet compliance deadlines.

Solvency II is not the only regulatory challenge insurers must prepare for. Insurers need to also factor in the proposed new international financial reporting standards under IFRS 4 Phase II.

IFRS 4 Phase II and Solvency II have many technical similarities. However, contract boundaries, discount rates, risk margins and the residual margin represent significant areas of potential differences between Solvency II and IFRS 4 Phase II, creating the need for solution blueprints to be adaptable to provide leverage opportunities. Since Phase II is likely to commence at a later date, data and system solutions for Solvency II will need to be validated against this new reporting standard to avoid expensive re-tooling when Phase II commences. All of these factors must be addressed when developing the IT strategy, and a single platform solution should not be considered without checkpoints for future developments.

In this article, we will address some of the regulatory requirements and EIOPA (European Insurance and Occupational Pensions Authority, formerly CEIOPS) comments in relation to data quality, take stock of the market response to date, and refl ect on the challenges still to come with IFRS 4 Phase II.

 

Solvency II requirements in relation to data

Data is at the very core of the Solvency II articles, and it is clear that any internal model approval process (IMAP) will focus heavily on data input to the model. It is widely recognized that the increased frequency of Solvency II reporting is likely to require organizations to collect and prepare data faster than they do today. Many in the industry are also finding that they need to aggregate or segment data in new ways, and to source additional data that they have not previously modeled.

But most importantly, EIOPA has set out a number of explicit and stringent data quality requirements, as shown in Figure 1.

For many non-life insurers, the Solvency II data requirements pose significant challenges for their liability data. Catastrophe modeling data is a particular concern, with issues around availability and granularity of key non-financial information. Specifically, these issues relate to the age of data, as there are potentially long lags between production of useable datasets (exacerbated for reinsurers), and a lack of granularity about geographical location for all the risks and error rates on building types and other descriptor fields.

For life insurers, there is increasing pressure to obtain greater transparency on asset and investment risk data, with counterparty exposure, corporate debt and liquidity of assets being targeted in particular.

The Solvency II QIS exercises have frequently highlighted to firms a number of additional data requirements to calculate solvency capital under the standard formula, and to populate the reporting templates. Additional processes and controls are likely to be required for all firms, for example, in the sourcing of additional data for complex assets for investment risk and counterparty risk modeling. The most recent QIS 5 exercise highlighted the granularity of asset data as a key challenge facing the industry. In many cases, the current data available was found to be insuffi cient for performing the full “look-through” calculations for the SCR as required by QIS 5. As a result, a suite of assumptions had to be made on the underlying asset mix, with minor changes to the assumptions, potentially resulting in material changes to model outputs. Regulators are likely to take a dim view of such assumptions being used in lieu of reliable asset data.

 

Taking stock — the market response to date

In our experience, the maturity of Solvency II data workstreams varies widely from insurer to insurer. Some organizations established strong early momentum as far back as 2009, and have moved steadily from gap analysis, through solution design, to implementation. Other organizations, including some major global institutions, have struggled to make significant progress to date and have begun 2011 by re-planning their data workstreams from the bottom up. Most insurance companies are somewhere between these two extremes, making headway in certain areas, but struggling in others.

Organizations seeking internal model approval only have a few months remaining before they may be required to demonstrate their compliance with Solvency II data requirements to local regulators. Given the relatively short time remaining, it is important that insurers take the opportunity now to review their data workstreams and confirm that they are on track to deliver.

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