Assessment of modeling and adoption challenges faced by actuaries in risk-based supervision in insurance companies in Uganda.
Abstract
The insurance landscape in Uganda is undergoing a significant transformation, marked by regulatory authorities' growing emphasis on risk-based supervision as a cornerstone for bolstering financial stability and enhancing consumer protection. Within this evolving regulatory environment, this dissertation undertakes an in-depth examination of the challenges faced by actuaries as they navigate the adoption of risk-based supervision within Uganda's insurance sector. Key findings from the research reveal that actuaries encounter a myriad of challenges on this journey. Complexity of the models stands out as a formidable hurdle, with 20.56% of respondents acknowledging the intricate nature of the mathematical models underpinning risk-based supervision. These models, essential for assessing and managing insurance risks, demand a high level of mathematical proficiency and specialized training, underlining the need for focused educational efforts within the profession. Furthermore, the research underscores the pressing issue of insufficient data availability, as 24.66% of respondents cite limited access to comprehensive and reliable data sources as a significant challenge. Inadequate data not only hinders actuaries' ability to make informed decisions but also compromises the reliability of risk-based supervision, necessitating efforts to improve data collection and quality control within the industry. The study also highlights the concern of a lack of actuarial expertise, with 21.92% of respondents expressing reservations about the availability of actuaries with specialized knowledge and skills in risk-based supervision. Addressing this shortage is essential to equip actuaries with the expertise needed to navigate the regulatory complexities effectively.
Additionally, limited computational resources emerge as a practical constraint, as 32.88% of respondents acknowledge the challenge of inadequate access to powerful computational resources. These resources are crucial for actuaries to conduct sophisticated risk modelling and assessment, emphasizing the need for investments in computational infrastructure. Collectively, these findings shed light on the multifaceted challenges actuaries face in the adoption of risk-based supervision within Uganda's insurance sector. These challenges encompass the complexity of mathematical models, data availability and quality, the shortage of specialized expertise, and limitations in computational resources. Addressing these challenges is pivotal to facilitating the seamless integration of risk-based supervision, thereby enhancing the stability and sustainability of Uganda's insurance industry.