Actuarial Analyst
3 weeks ago
The Actuarial Analyst in the Reserving Team at Kshema will play a pivotal role in supporting the company's reserving functions. This position involves assisting in the estimation of technical reserves, analyzing data, and contributing to the development and implementation of reserving strategies. The ideal candidate will work closely with senior actuaries and other departments to ensure the accuracy and adequacy of reserve estimations.
Key Responsibilities:- Assist in the monthly, quarterly, and annual reserving process, ensuring compliance with regulatory requirements and internal policies.
- Analyze historical data and trends to support reserve estimations and adjustments.
- Contribute to the development and refinement of reserving methodologies and models.
- Collaborate with the claims, finance, and underwriting teams to provide insights from reserving analyses.
- Prepare and present reports and findings to senior actuaries and management.
- Contribute to the preparation of solvency forms and Appointed Actuary Reports to be submitted to the regulator.
- Support the actuarial team in responding to queries from auditors and regulators regarding reserving practices and figures.
- Stay updated with industry trends, regulatory changes, and best practices in reserving.
- Work on the implementation of new regulatory regimes like Risk-Based Capital (RBC) and IFRS17 within the company.
- Analyze competitors' financial results, reserving methodologies, and risk management practices to provide useful insights to senior actuaries.
- Participate in cross-functional projects and initiatives as required.
- Progress towards actuarial qualifications with a recognized actuarial body is highly desirable.
- 1+ years of prior experience in an actuarial function within the insurance industry is advantageous, especially in reserving or related areas.
- Proficiency in MS Office Suite, VBA, and Python along with the use of emerging technologies is desirable.
- Ability to use emerging techniques like data analytics and machine learning.
- Strong analytical and problem-solving skills.
- Strong attention to detail and ability to handle complex data.
- Good communication skills, with the ability to present findings clearly and concisely.
- A team player with a proactive approach to tasks and projects.
Educational Qualification:
- Bachelor's degree in actuarial science, mathematics, statistics, commerce, or a related field.
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