"Basel for insurers" is how the European Union's Solvency II Directive is often described. Under the directive, insurance companies must actively consider their risk exposures to current and future investments over extended timeframes and ensure they have sufficient capital reserves to cope with potential risks.
But Solvency II is not just a European insurance industry issue: it affects the entire global buy-side value chain. Whenever an insurance company outsources asset management to a third party, that investment manager will be required to provide much of the data that the insurance company needs to meet its regulatory obligations. In turn, the asset servicing firms (such as custodian banks and fund administrators) that support the asset manager also will be called on to provide critical data inputs required by Solvency II.
Solvency II presents a number of complex data challenges for insurers and their service providers. For example:
Quantitative Report Template (QRT): Sourcing and mapping the correct data to populate the primary disclosure template known as the QRT will represent a large challenge for most firms. Not only will the QRT require the proper mapping and data inputs, but firms also will need appropriate controls that provide an audit trail and provenance of securities and portfolio data. Errors or omissions – of which there is a high risk – will likely result in regulators demanding additional ad hoc reporting, or even supplementary capital requirements where a firm's disclosures are deemed unsatisfactory.
The data needed spans a host of categories, including instrument, issuer, classification (e.g., issuer, sector), geography, ratings, risk and fair value price. It then needs to be formatted consistently and mapped to the QRT, with transparency into the data's source.
Capital adequacy calculations: Insurers' Minimum Capital Requirement (MCR), Solvency Capital Requirement (SCR) calculations and risk reporting depend on accurate and regular asset and liability valuations, based on market prices for liquid instruments and evaluated prices for harder-to-value securities. To conduct internal valuations, a range of underlying market and economic data is required, such as Solvency II-specific benchmark curves, rates and surfaces used to aggregate, model and manage cash flows. Regulators also seek transparency into the valuation methodologies, with a clear connection between the data inputs and price outputs.
In addition, various securities, issuer, sector and ratings classification data are essential to understand the attributes/risk profile of the securities held by the insurer, and the issuers concerned. These include:
- Complementary Identification Codes (CIC) for instrument and asset class definitions
- Legal Entity Identifiers (LEI) to uniquely identify issuers and counterparties
- Nomenclature statistique des activités économiques dans la Communauté européenne (NACE) to define the business sector of companies held in insurance portfolios
Fund holding exposures
Insurers could face a higher capital requirement unless they have an accurate view of their investment holdings. This requires detailed "look-through" of the securities held by collective investment vehicles to identify and classify fund holdings by security and issuer, with the data then aggregated across holdings.
Sourcing timely and accurate constituent data across multiple fund portfolios is a key requirement. The fund holdings content also needs enriching with additional security-level information, such as CIC codes and other industry classifications, if firms are to aggregate their risk exposures accurately. Insurers who work with multiple asset managers face another burden of aggregating data from all of their asset managers, which may be provided in different formats, thus requiring added work to standardize.
Credit Quality Steps (CQS): To provide transparency into the credit risk associated with investments, insurers must include a CQS number in their regulatory reports. The CQS is based on ratings from the three major agencies (Moody's, Fitch and S&P), with the second-best value used for the SCR calculation and reporting. However, sourcing ratings from all three agencies involves substantial cost and requires end user firms to acquire the appropriate license from the agencies for this calculation to be performed. In addition, running the CQS analytics takes significant IT and data management overhead and effort.
To power the capital adequacy calculations, risk mitigation, and disclosure tools and workflows demanded by Solvency II, market practitioners need access to a multitude of data sets. Key data capabilities to consider are:
- Listed market pricing: Timely and frequent pricing for the broadest possible coverage of liquid and illiquid securities traded on listed markets, in order to calculate the net asset value of a fund's holdings.
- Evaluated pricing: Reliable, timely and transparent evaluated pricing for harder-to-value securities.
- Reference data sets: Including the provision of extensive security reference data; support for different industry instrument, country and sector codes for cross-referencing; legal entity classifications; and global ratings data.
- QRT population: Correct formatting and detailed mapping of the required data set to the QRT. Regulators also want transparency into the data's source, backed by a complete audit trail.
Ultimately, there is no single key to unlock the challenges industry participants will face. Instead a collaborative approach – built on partnerships between data vendors, analytics providers, ratings agencies, asset servicers and the insurers themselves – will be essential for institutions to meet the disclosure requirements of Solvency II.
About the author: Tim Lind is head of legal entity and corporate actions for Thomson Reuters.