The Role of Data Quality in Solvency II Compliance and Beyond

The Role of Data Quality in Solvency II Compliance and Beyond W H I T E PA P E R This document contains confidential, proprietary, and trade secret information (“confidential information”) of Informatica Corporation and may not be copied, distributed, duplicated, or otherwise reproduced in any manner without the prior written consent of Informatica. While every attempt has been made to ensure that the information in this document is accurate and complete, some typographical errors or technical inaccuracies may exist. Informatica does not accept responsibility for any kind of loss resulting from the use of information contained in this document. The information contained in this document is subject to change without notice. The incorporation of the product attributes discussed in these materials into any release or upgrade of any Informatica software product—as well as the timing of any such release or upgrade—is at the sole discretion of Informatica. This edition published April 2008. White Paper Table of Contents Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Developing a Comprehensive Data Management Approach . . . . . . . . . . . . . 4 Datatypes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Managing Data Quality Enterprise-Wide . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Managing Data Quality Over Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Managing Data Quality in Real Time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Using the Right Technology to Ensure Compliance. . . . . . . . . . . . . . . . . . . . 7 Beyond Compliance: Reaping the Long-Term Benefits of High-Quality Data 9 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 The Role of Data Quality in Solvency II Compliance and Beyond 1 Executive Summary With the release of the draft Directive for Solvency II (Solvency II) in July 2007, the European Union took a giant step forward in streamlining regulation of the insurance industry. Often called “Basel for insurers,” Solvency II is somewhat similar to the banking regulations of Basel II. The proposed Solvency II framework has three main areas (pillars): • Pillar 1 consists of the quantitative requirements (for example, the amount of capital an insurer should hold). • Pillar 2 sets out requirements for the governance and risk management of insurers, as well as for the effective supervision of insurers. • Pillar 3 focuses on disclosure and transparency requirements. Consolidating rules from 14 different pieces of legislation, Solvency II is ambitious and expected to have a far-reaching impact on the industry. The objectives of the legislation include: • Improving consumer protection • Modernizing supervision • Strengthening market integration • Increasing the international competitiveness of European insurers Solvency II is designed to help the insurance industry calculate its capital requirements more efficiently using a sophisticated risk-based system. Current EU solvency requirements only cover insurance risks. With Solvency II, insurers will be required to also hold capital against three different kinds of risk: 1. Market risk such as a decline in the value of an insurer’s investments 2. Credit risk—for example, when debt obligations are not met 3. Operational risk such as malpractice or system failure 2 1 Wikipedia, http://en.wikipedia.org/wiki/Solvency_II (November 2007) White Paper In light of such recent events as turbulence in the credit markets, changing weather patterns (like those that caused extensive flooding in the United Kingdom and central Europe in the summer of 2007), and the continued threat of terrorism, Solvency II’s more sophisticated and comprehensive risk model is both appropriate and welcome. This new model, however, demands a new approach to managing data and ensuring and maintaining its quality. Solvency II’s more sophisticated approach to risk management, financial reporting, and corporate governance requires insurance companies to put comprehensive standards, policies, and processes in place for the use, development, and management of data. Data management and data quality are no longer nice options; they are essential. The European Commission hopes to have Solvency II fully implemented by 2012, but insurance companies have much to gain—particularly in more efficient and effective capital and risk management—if they start implementing a comprehensive data management approach now. Not only will they be set up to comply with future regulations, but they will also reap operational and financial benefits today. This white paper outlines the issues insurance companies should take into account in developing a comprehensive data management approach to ensure compliance with Solvency II requirements. The Role of Data Quality in Solvency II Compliance and Beyond 3 Developing a Comprehensive Data Management Approach Ultimately, Solvency II is about managing risk exposure by holding regulatory capital to a confidence interval of 99.5 percent. To accurately calculate their overall risk exposure and capital requirements, insurance companies must have access to and insight into all their data. And this data must be of high enough quality for the more data-intensive tasks of risk analysis and Solvency II compliance. A comprehensive data management approach must address: • The variety of datatypes an insurance company handles • The volume of data processed “Member States shall ensure • The quality of data in its systems that insurance and reinsurance Datatypes undertakings have internal processes Insurance companies handle a huge variety of data. The body of Solvency II-relevant data is and procedures in place to ensure growing all the time. It comes from multiple sources. More data from more source systems is being used to drive risk calculations, forecasting, business intelligence, and corporate performance the appropriateness, completeness management. and accuracy of the data used in To conduct accurate statistical risk analyses, companies need to examine data throughout the enterprise—including all aspects of customer, commercial, financial, and operational data at the the calculation of their technical lowest level of detail. To better manage risk, insurance companies need to bring together data from systems that in the past operated as silos and had little or no relation to each other. provisions.” To add another layer of complexity, insurance companies must have insight into not only the data they have, but also the data they lack if they are to effectively manage their potential exposure to Article 80, Solvency II risk. Let’s say a company has a list of geographical areas that are prone to flooding. This list is an example of data the company has. An example of data it lacks is information about customers and policies that may be materially affected when an employer closes up shop. Data Volumes Insurance companies also grapple with a huge amount of data. Each risk component requires different levels of data. Credit, market, and underwriting risk analyses demand vast quantities of data. As an evolving discipline, operational risk requires less, but it still demands data. And data is not static. Information is constantly changing, and those changes need to be reflected accurately. Raw data is transformed via risk methodologies into usable information that, in turn, creates more data that needs to be managed and measured.