Breadth of coverage continues to be a winning formula for Moody’s Analytics in is approach to Solvency II. Its RiskIntegrity Suite supports both the standard formula and internal models, and includes proxy modelling, process and data management, and regulatory reporting. Insurers appreciate the ability to adopt a comprehensive implementation or pick and mix modules to integrate with existing infrastructure.
As a representative at one European mutual remarks: “Different vendors proposed solutions specialised in various aspects of the regulatory process, while Moody’s Analytics was the only one to provide a solution that enables compliance with the full process, from loading assets and liabilities, to the generation of the required reports for the European Insurance and Occupational Pensions Authority and the local regulator.” A Scandinavian financial services group says: “We were particularly impressed by the modularity of the Moody’s Analytics solution, an important aspect in order to guarantee the flexibility and scalability required for future growth of the business and to support the consequent automation needs.”
Automation has been an important theme in the industry over the past year, not only to support growth, but also to achieve efficiency in Solvency II implementation and to begin to extract some added business value from investments made, says Colin Holmes, managing director, insurance solutions for Moody’s Analytics’ enterprise risk solutions group who is based in Edinburgh. He cites the example of a large life firm that realised, although its Solvency II processes were in place well ahead of time, it was going to take more effort than the company wanted to carry them out. “RiskIntegrity’s ability to streamline and automate 'business as usual' processes has been key to the firm reducing ongoing costs and operational risks,” Holmes says.
Efficiency is also critical in being able to produce timely results, especially as reporting deadlines are tightened over the first three years of Solvency II. This is where the use of proxies to model assets and liabilities comes in and Moody’s Analytics has made a number of enhancements to its RiskIntegrity Proxy Generator module over the past 12 months. For example, it has tightly integrated scenario generation and function fitting, reducing the level of implementation required by incorporating these into a single software module. “We partnered with clients to help us develop the RiskIntegrity Proxy Generator in a way that would be most helpful to them. This is an area of our Solvency II software package where we have helpful feedback from clients, which has resulted in the module being exceptionally strong,” says Holmes.
One of the trickiest challenges insurers face in the current economic environment with extremely low or even negative interest rates is valuing products with guarantees, such as with profits and variable annuities. Here again Moody’s Analytics has worked closely with clients, this time to enhance its Economic Scenario Generator (ESG) to meet their needs, particularly in the context of Solvency II. This has included adding Solvency II-ready market consistent calibrations, enhancing the modelling of negative interest rates, and upgrading real-world interest rate modelling and calibration.
“Market practitioners have traditionally used a log-normal convention for quoting swaption implied volatility used to calibrate market-consistent scenarios. However, log-normal implied volatilities become very unstable as interest rates get closer to zero and cannot be calculated for negative strike rates. In response to this, we engaged with clients and market data providers and worked hard to improve our ESG software and calibration toolkit to offer clients a range of options for quoting volatility as well as a number of different interest rate models,” Holmes says.
While accuracy of modelling and reflecting changes in the economic environment are critical features of an ESG, performance and control have become increasingly important as insurers now need to produce large numbers of scenario sets for calculating technical provisions and best-estimate liabilities, and as inputs to internal model or standard formula calculations. Over the past two years, Moody’s Analytics has further improved the performance of its ESG and completely overhauled the automation module. Among the enhancements to the module are the ability to automatically apply volatility or matching adjustment to the risk free curve and a method for treating the adjustments in Solvency II standard formula stresses, as well as an intuitive and easy-to-use interface that allows users to configure all of their automated runs without specialist coding skills or tools. As a result, a large number of clients in Europe have now implemented the module, says Holmes.
A European life group chose the automation module primarily for the speed and run-time benefits, but also valued the fact that it integrated Moody’s Analytics’ new interest rate modelling methodology. “The advanced multi-factor models give us the ability to accurately value liabilities and produce high-quality validations and reports,” says the firm.
The ability to streamline and automate 'business as usual' processes is key to reducing ongoing costs