RISK IN INSURANCE COMPANIES

Transcription

1 RISK IN INSURANCE COMPANIES As of January 2016, the new risk framework Solvency II has become applicable in the Insurance world. Coupled with a low interest rate environment, its introduction can mean a significant change in the way of doing business as well as its risk assessment. This note summarizes the most important risk related challenges for the future of the Insurance business.

2 1. LOW INTEREST RATE ENVIRONMENT The profitability of life insurance undertakings is under strong pressure in view of the current interest rates environment and declining premium payments. The unfavourable financial conditions on the life insurance business make them particularly vulnerable. Operational and underwriting losses can not be covered easily by the investment returns due to their low level. Therefore a better control of the underwriting and operational risks is obliged. Some efforts to improve cost management are also needed. Insurance companies should carefully ponder their realisation of capital gains and continue strengthening their solvency positions. Improvements in the solvency position of financial institutions through retained earnings and/or capital issuance will be key to facing the new challenges resulting from the economic environment and the increasingly heavy regulatory requirements Solutions can be found and have to be developed for the main risks of your liability portfolios and in the process of your company.

3 2. DATA MANAGEMENT The concept of data science offices is becoming more and more popular. Building and staffing such an office requires the implementation of a data ownership model. The definition of terms such as data owner or data steward is essential to manage the frequent changes of data through multiple systems and processes. The insurers should take care of the different aspects related to the data ownership, such as: creation or production of data use of the data change or update of the data The questions «who», «when», «the frequency», «the validation process» and «control process» should be addressed to.

4 3. DATA QUALITY The Solvency II directive is the first insurance regulation to introduce strict requirements for data quality. Among others, the directive recommends: The importance of setting up robust internal controls around the collection and storage of risk data To assess risk on data using the following principles of Accuracy Completeness Appropriateness That data used for the SCR calculation should be accurate and consistent with the wider management and financial reporting across the organization

5 4. BIG DATA Currently the market is evolving from a framework of traditional data to a data framework of high volumes, with multiple forms originating from complex sources The Big Data era will allow insurance companies to have a better understanding of their customers and will change the way of doing: Insurance underwriting Insurance pricing and Products offering Claims Management Fraud Detection Real-time Risk Management based on dynamic predictive models

6 5. POLICY ADMINISTRATION SYSTEM The transformation of the policy administration systems should continue in order to offer the following advantages: Lower IT costs Operational efficiency Underwriting and rating automation Improved product flexibility and speed One single view on the customer Identify the legacy data quality

7 6. ENTERPRISE RISK MANAGEMENT Enterprise Risk Management is relatively new. The quantitative elements are well developed and it is now time to pay more attention to the qualitative key ones. The recognition of the limitations of models and their assumptions should lead, on top of pure risk modeling, to the set-up of: Model frameworks driving business decision-making Governance and risk policies Fit and proper risk management Data and process management with documentation Independent reviews All these processes have to be integrated in a common platform. Risk Management should not be left solely to the risk managers. The risk culture has to be embedded throughout the entire organization

8 7. SOLVENCY 2 MODELS AND THEIR VALIDATION Asset, liability and financial data are often a significant area of change for firms developing and applying for approval of an internal model. For companies for which the standard Solvency 2 formula does not fit well with the risk profile, the company can still start designing partial/internal models and properly analyze the need of undertaking specific Parameters (USP) for a subsequent calibration (e.g. non-life insurance may replace the standard risk factors for the premium and reserve risk with their own parameters). Every model will not be ready by the start of Solvency 2 and a time buffer could be necessary in order to make models in line with regulatory requirements. Internal model approval requests that the model meets further governance requirements and standards of statistical quality. Use tests need evidence that the firm's governance system has an understanding of the underlying data limitations of its internal model. Initial validation of their internal model will have to include a robust data validation exercise, including both inputs and outputs, as part of this process.

9 8. SOLVENCY 2 AND THE ORSA Own Risk Solvency Assessment (ORSA) evaluates the current and future Solvency needs for a company. Moreover the deviations of the risk profile from the assumptions of the Solvency II Standard formula or the (partial) internal model are also assessed. The business and Solvency projection plan should be considered through the cycle and find solutions to keep a level of capital comfort in any cases (also in Stress Testing conditions). The ORSA should offer to the company a view on its solvency evolution in function of its strategy, Risk Appetite and Capital Risk management. All these different concepts has to be known, developed and applied through the governance of the company.

10 9. SOLVENCY 2 AND THE ACTUARIAL FUNCTION The role of the Actuarial Function is defined by a list of tasks in Article 48 of the Solvency II Directive: Coordination of the calculations of the technical provisions Review the appropriateness of the models and assumptions, the quality of the data and its sufficiency. Reporting requirement to the AMSB Regulatory deliverables An appropriate operating model for the Actuarial Function should take into account: The overall objectives of the management body The skill base and resources of local teams Compliance with the Solvency II Directive on independence and conflicts of interest Companies should first plan an appropriate operational model for the Actuarial Function model, this will save costs in the long run and improve the quality of the delivered information in due time.

11 10. SOLVENCY 2 AND REPORTING A few key considerations for the Solvency II reporting are: Choosing the right technology solution between the options available to insurers Dealing with the uncertainty around technical issues e.g. volatility adjustment and by extension getting comfort over the Solvency II balance sheet The challenges of getting asset data and dealing with the constraints placed by asset managers The power of narrative reporting and how this should be used How Pillar III could change the way in which insurers are viewed by the market Pillar III directives provide challenges around internal controls for each step of data processing, as it will require insurance companies to enhance enterprise reporting processes, while bringing together information from disparate data sources. Each insurance company will need to review and validate their data quality within a short timeframe,.

12 IF YOU WANT TO KNOW HOW BUSINESS & DECISION CAN HELP YOU FACE THESE CHALLENGES, PLEASE CONTACT: Arnaud Piccin Business & Decision - Risk & Finance Practice Arnaud.Piccin@businessdecision.com 12