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Solvency II and EIOPA requirements in relation to data - EY - Global

Solvency II and IFRS: are your data and systems up to speed?

Solvency II and EIOPA requirements in relation to data

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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.

EIOPA requirements

Many in the industry are 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 (European Insurance and Occupational Pensions Authority, formerly CEIOPS) has set out a number of explicit and stringent data quality requirements.

EIOPA data quality requirements

  • Embed a system of data quality management across the entity
  • Compile a directory of data attributes used in the internal model, stating each attribute's true source, characteristics and usage
  • Define and monitor processes for identification, collection, transmission, processing and retention of data
  • Ensure data processing from source to model is transparent and demonstrable
  • Define objective metrics for completeness, accuracy and appropriateness of data
  • Establish a data policy which sets out the entity's approach to managing data quality
  • Perform periodic data quality assessments, and implement a process for identifying and resolving data defi ciencies
  • Document instances where data quality may be compromised, including implications and mitigating actions
  • Provide an audit trail and rationale for data updates when applying expert judgment in lieu of reliable internal or external data
  • Agree with the role of internal and external auditors in assessing data quality
  • Establish a process to manage changes or data updates which materially impact model outputs

For many non-life insurers:

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.

Solvency II QIS

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 insufficient 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.

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