A strenuous regulation Regulatory compliance costs money and may disruptively alter the business environment. Recent statements from a senior official of the United Kingdom’s financial services regulator and from the chief executive of the UK’s largest insurer gave impetus to this assertion – at least as far as Solvency II is concerned. In March 2012, a deputy governor from the Financial Services Authority (FSA) expressed frustration at the enormous expense the regulator and insurance companies would be forced into if they are to comply with the new EU-wide insurance standard. According to him, Solvency II legislation runs the risk of being so complicated that it could cloud instead of providing clarity to the European Union’s risk regime. Most important, the FSA official was concerned that the new regulation is likely to flood supervisors with massive volumes of data that will ultimately do little to improve supervision and reduce risks. Prudential’s chief executive on the other hand sees Solvency II as an encumbrance for EU-based insurers with a large part of their business in other jurisdictions such as the Asia and the Americas. New data challenge calls for new data management solutions? While not everyone will necessarily agree with the grim view taken by the two executives, their verbalized thoughts highlight one of the biggest challenges facing insurance companies in the European Union as Solvency II comes into effect – data management and data warehouse infrastructure.
For the largest insurers, the old ways of managing and reporting risk data are simply impractical under the new framework. They must update their risk engines and data warehouse in response to the new challenges and demands. Risk engines, data warehouses, scenario generators and actuarial models are the primary technological components for Solvency II compliance. This is particularly so for insurance companies that have adopted an internal capital model. But how do risk engines work? Well, they aggregate data from several sources, compute risk exposure and capital adequacy, and generate reports for management decision making and regulatory compliance. In many respects, risk engines are simply data processors. This means their effectiveness is heavily dependent on how well the infrastructure and systems that feed them function. In particular, input data quality, consistency and integrity are crucial in guaranteeing the accuracy of output from risk engines. It is not just Solvency II that will place higher expectations on risk engine technology and require more robust and formalized data warehouse and data management processes. Emerging best practice may in fact end up being the key driver of such changes. Insurance companies that are more forward looking will go ahead to enhance and formalize their systems in preparation for Solvency II compliance well before the deadline. Getting the right data warehouse and risk engine Suitability – When shopping for an off-the-shelf data warehouse and/or risk engine solution for purposes of Solvency II, it is important to always bear in mind that virtually every data warehouse is best primed for a specific industry. Put differently, a data warehouse that may perform exceptionally well for a manufacturing company may not necessarily work as well for a bank. Similarly, the data warehouse that an insurance company eventually buys to facilitate Solvency II compliance must be one that is in active use and has been highly rated by the insurance industry.
Note however that irrespective of how suitable the data warehouse is, there are bound to be several aspects of the data warehouse and/or risk engine that will require additional tweaking in order to meet each insurer’s specific requirements. The key is in identifying the vendor whose product will deliver the most ‘quick wins’ and require the least customization. Flexibility – How easily can the risk engine and data warehouse be adopted to changes in regulation? And how well can the same engine and warehouse be used for global financial services companies whose businesses fall under several regulations (e.g. Solvency II, Basel III and Dodd Frank)? As opposed to purchasing a different technology solution for each regulation, the best solution would be one that can be adopted across multiple regulations. Consolidated data – Giant multi-national insurance companies often have the financial firepower to acquire best-in-class systems. But the realities of Solvency II imply that simply purchasing sophisticated systems is not sufficient. A single repository is necessary that will ensure data is relayed to enterprise risk engines in a controlled and structured way. The single repository should include inbuilt checks and balances that ensure the completeness, accuracy and relevance of data irrespective of its source system.