Finance systems in most insurance companies have been developed incrementally over the past 20 to 30 years. As insurance companies have grown, the system architecture has been augmented with layer upon layer of tactical End User Computing applications that are often poorly documented, uncontrolled and inefficient. This lack of focus on integration, standardisation and decommissioning has resulted in an architecture that cannot respond to the latest wave of change being driven by Solvency II. Now is the time for much needed investment, but change will have to be incremental and it is vital that each step in the path to the strategic end state is understood within the context of the process, people and desired outcomes.
To meet all the demands for Solvency II, it will be essential for the finance function to invest in the right system changes. Some of the benefits of doing this are;
- A greater insight and control over Finance & Risk data through the utilization of reporting applications and web-based tools, which reduces the effort and time required to generate information, and ensures greater focus on analysis.
- A flexible and agile financial consolidation system, that enables organisations to easily manage and maintain multiple reporting bases and changes to organisation structures due to regulatory changes and capital restructuring.
- An agile & integrated planning process allows management to rapidly respond to changing economic circumstances and can quickly provide the information to gain shareholders support.
Actuarial models are a unique aspect of insurance finance systems and new regulation and market demands will require a new approach to actuarial modelling. There needs to be a greater understanding of the results and methodology as use will come from a much broader range of stakeholders. A key challenge is ensuring complex changes specific to actuarial models are considered within the firm’s broader Finance & Risk transformation programme and future management framework.
Some of the areas to be addressed in model build are;
- Improved quality, transparency and controls on data input and use of assumptions
- Increased speed and efficiency of core actuarial models
- Manage capital aggregation & stochastic modelling to meet reporting requirements and allow projections/business planning
- Improved reporting speed, quality and controls