KEY CHALLENGES TO INSURANCE RISK MODELLING: A SURVEY OF UK GENERAL INSURANCE ACTUARIES AND RISK MANAGERS

Transcription

1 INSIGHT REPORT RISK MANAGEMENT KEY CHALLENGES TO INSURANCE RISK MODELLING: A SURVEY OF UK GENERAL INSURANCE ACTUARIES AND RISK MANAGERS IN ASSOCIATION WITH GRANT THORNTON

2 1 Key Challenges to Insurance Risk Modelling INTRODUCTION Insurance firms are already looking beyond the introduction of Solvency II to work out how they can make their risk modelling process more efficient and take advantage of the considerable investments they have made to comply with the new regulations. In the second quarter of 2015, FIS and Grant Thornton ran a confidential survey of 31 senior general insurance actuaries and risk managers in the U.K. to identify key challenges in their risk modelling processes, and the strategic implications. The survey sample was carefully focused on the leaders of the teams responsible for insurance risk modelling, with nearly 90 percent of the respondents involved in capital modelling and about half also responsible for reserving and/or pricing (Figure 1). Five key findings The survey revealed significant concerns about the efficiency and effectiveness of the end-to-end risk modelling process and the challenges that teams face: 1. Half of senior risk professionals think their risk modelling processes need re-engineering within the next three years, with more than a quarter of those responding saying the need is more urgent, i.e., as soon as possible this year 2. Resourcing ranks as the top challenge when managing the end-to-end risk modelling process, with worries over finding appropriately skilled human resources clearly beating other concerns 3. Validation is the major area of concern in terms of efficiency, with 80 percent of those that responded saying they lack the time and resources to carry it out as effectively as they would wish 4. New pinch points in the calculation cycle are emerging, with validation taking up a significant 4.4 working days, or more than one fifth of the average time per cycle (nearly double the time spent on the traditional core task of gathering data) 5. Operational control and data quality are also often seen as big challenges now that teams need to consider each part of the modelling and data handling process Figure 1: What are your areas of responsibility? Capital modelling 32% 7% 19% 29% Pricing 3% 7% Reserving 3%

3 Key Challenges to Insurance Risk Modelling 2 Key findings in more detail survey results Re-engineering risk modelling processes More than a quarter of respondents said that their risk modelling processes need urgent re-engineering, as soon as possible this year, with just over half saying re-engineering is needed within the next three years (Figure 2). Nearly all of those responding agreed they would need to re-engineer their risk modelling processes in the longer term, with only one person thinking that re-engineering was simply unnecessary. The concern about the risk modelling process is likely to be the result of significant changes and new processes introduced within a relatively short timescale to meet Solvency II regulations. While each process may be fit for purpose in isolation, their integration into day-to-day business procedures may need to be improved to gain efficiencies. Some respondents voiced particular concern about data gathering, data cleansing, and validation, with one commenting that, Validation controls need further development, particularly engagement and challenge from business units. Figure 2: How many agree that their risk modelling processes need to be re-engineered? AGREE STRONGLY AGREE Our risk modelling processes need to be re-engineered 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Urgently as soon as possible this year Mid-term within the next 2-3 years Longer term within the next five years

4 3 Key Challenges to Insurance Risk Modelling Resourcing the most significant challenge to the risk modelling process The most significant challenge that teams face is finding the right resources to perform the modelling process, particularly human resources. Nearly all the total sample (27 out of 31) named resourcing as one of their most significant challenges and nearly two thirds ranked it as one of their top three challenges (Figure 3). Resourcing is tough to get right because firms can find it difficult to hire experienced staff with the required skills to run the risk modelling process and, more often than not, to operate and improve the specialist systems used for insurance modelling. Figure 3: What percentage ranked each factor as one of their top three risk modelling challenges? Ranked a top 3 model challenge 0% 20% 40% 60% Resources Speed Operational control Reporting to regulators Data quality Transparency Auditability Coping with data Cost Usability of models (internal or vendor) Reporting internally Error reduction

5 Key Challenges to Insurance Risk Modelling 4 Validation processes are a major area of concern Eighty percent of those responding agreed they lack the time and resources to effectively carry out the validation process and almost 25 percent strongly agreed. Figure 4 shows the degree to which respondents feel they lack the time and resources to effectively carry out a range of key processes. The degree of concern over the effectiveness and efficiency of the validation process is striking. However, the important word here is effectively. Companies expect to be compliant with Solvency II, but they still feel that they lack the time and resources to carry out the process as effectively as they might wish. Until a few years ago, teams often devoted minimal time and resources to validating the risk modelling process and tended to focus on checking data. However, validation is now a much more wide-ranging and integrated concept. In a Solvency II context it encompasses data, models, systems and processes, as well as how model output is reported and applied, e.g., for business decisions as well as capital adequacy. This can create challenges. For example, commenting on the end-to-end risk modelling process, one respondent said their approach was fit for purpose but that, validation and reporting of model output needs improving, particularly in terms of efficiency and embedding within business decisions. Validation is not the only part of the modelling process causing concern. Reporting, particularly reporting to regulators, also lacks time and resources according to many teams and some larger teams worry about the resources available for data cleansing. Figure 4: Which processes do you lack the time and resources to effectively carry out? We lack the time and resources needed to effectively carry out: Validation Reporting Data cleansing Assumption setting Calculation runs Data extraction and loading Data gathering Disagree Agree Strongly agree

6 5 Key Challenges to Insurance Risk Modelling Pinch points in the calculation cycle The reason for the resourcing concerns became evident when teams reported how long it took them to complete each part of the modelling process. Figure 5: How do teams spend their time during each calculation cycle? VALIDATION DATA GATHERING REPORTING DATA CLEANSING Teams spend around 21 person days on the average calculation cycle (e.g., about five working days for a team of four), and the single most intensive process is validation, with teams on average spending 21 percent of their time on this activity (Figure 5). ASSUMPTION SETTING CALCULATION RUNS 8% DATA EXTRACTION AND LOADING Reporting (18 percent) and assumption setting (18 percent) also eat up time. Other activities take up less time, including the actual calculation runs (14 percent). Of the three data-related activities, gathering the data and cleansing the data (11 percent and 10 percent, respectively) take more time than extracting the data and loading it into the calculation system (8 percent). Figure 6 sets out the typical process waterfall timeline. 10% 11% 21% 18% 14% 18% Figure 6: Calculation cycle process waterfall (with percentage of time spent on each activity) 0% 20% 40% 60% 80% 100% Data gathering Data cleansing Data extraction and loading Assumption setting Calculation runs Validation Reporting

7 Key Challenges to Insurance Risk Modelling 6 Operational control and data quality are also big challenges FURTHER INFORMATION Figure 7 illustrates the degree to which respondents agreed each of a range of key factors represents a significant challenge. Resourcing is clearly the top concern, but data quality and operational control are also regarded as challenges. Indeed, many of the factors in Figure 7 represent a challenge to some teams, with only usability of models, cost, reporting internally, and error reduction gaining relatively few votes. We would welcome your comments on these findings. Please contact getinfo@fisglobal.com or Simon.h.sheaf@uk.gt.com quoting Key Challenges to Insurance Risk Modelling in the subject line. A forthcoming white paper will discuss the survey results and their implications in more detail. Figure 7: Which factors are significant challenges? The following are significant challenges to our end-to-end risk modelling process: Resources Data quality Operational control Reporting to regulators Coping with data Transparency Speed Auditability Usability of models Cost Reporting internally Error reduction Agreement

8 About FIS Prophet solution FIS Prophet solution is a leading actuarial modeling system that helps insurance and financial services firms develop more profitable products faster, improve risk management decisions, and meet their reporting responsibilities efficiently. Prophet provides comprehensive coverage across life, general insurance, health and pensions for all major insurance markets on a single platform, providing common models, code, assumptions and reporting capabilities, plus end-to-end data management and business intelligence. It offers actuaries an easy-to-use, flexible product design environment combined with a controlled, enterprise-level production environment, enabling the fast delivery of accurate, auditable and clearly presented information to risk managers, senior management and regulators. Prophet can be deployed on-premise, hosted or on the cloud, and is relied on by more than 10,000 users at over 850 customer sites in more than 65 countries. About Grant Thornton Grant Thornton is one of the world s leading organisations of independent assurance, tax and advisory firms, providing bespoke solutions to the finance sector. We help dynamic organisations unlock their potential for growth by providing meaningful, forward looking advice. With more external issues affecting the financial services sector than ever before, knowing which way to turn is an increasing challenge. Our clients tell us they are confident in our ability to proactively anticipate market activity, we listen to their needs and create fit-for-purpose solutions rather than off-the-shelf services. For more information, please visit grant-thornton.co.uk twitter.com/grantthorntonuk linkedin.com/company/grant-thornton-uk-llp About FIS FIS is a global leader in financial services technology, with a focus on retail and institutional banking, payments, asset and wealth management, risk and compliance, consulting and outsourcing solutions. Through the depth and breadth of our solutions portfolio, global capabilities and domain expertise, FIS serves more than 20,000 clients in over 130 countries. Headquartered in Jacksonville, Florida, FIS employs more than 55,000 people worldwide and holds leadership positions in payment processing, financial software and banking solutions. Providing software, services and outsourcing of the technology that empowers the financial world, FIS is a Fortune 500 company and is a member of Standard & Poor s 500 Index. For more information about FIS, visit twitter.com/fisglobal getinfo@fisglobal.com linkedin.com/company/fisglobal 2016 FIS FIS and the FIS logo are trademarks or registered trademarks of FIS or its subsidiaries in the U.S. and/or other countries. Other parties marks are the property of their respective owners. 1404