Research & Development Actuary

**The Role**

Reporting to the R&D Director, the R&D Actuary Experience Analysis (EA) would have two core responsibilities:

- They would be responsible for the checking, planning and reporting of the annual analysis of in-force experience for all our core markets in Asia, along with carrying out other ad-hoc experience analyses; and
- They would also be responsible for managing the two R&D Data Analysts and their workloads, which involve new treaty implementation into S.A.P.

Very good communication skills will be of fundamental importance to be successful in the two core responsibilities. The annual EA will involve presenting results to senior management and occasionally clients, and S.A.P. Implementation will involve communicating with the Operations (Ops) team, and working as the “bridge” between Ops and R&D.

The role is part of the Asia R&D department which is responsible for analysing all the in-force treaties’ experience, in order to set best estimate assumptions for the Valuation department and to present results to clients to better inform them of their business’ experience. These experience analyses take several forms including Generalised Linear Models (GLMs). The department also lead the development of Terms of Trade (TOT) across all our lines of business and territories within Asia, via the use of GLMs and wider medical and policyholder behaviour research. These TOT are primarily for use by the Pricing department. Lastly the R&D department is also responsible for calibrating risk distribution functions for economic capital purposes.

The products covered in our analyses extends over the full range of Life and Healthcare products. Through their work, the individual will have the opportunity to work with a variety of experts, including colleagues in Operations, Corporate Actuarial, Marketing, Strategic Analytics and Underwriters.
- Support the overall Annual Experience Analysis project for the purpose of basis setting, for current in-force treaties. This will involve working closely with the Director to help plan and manage the overall project, guiding junior members of staff and checking their results, carrying out their own experience analyses and building (and presenting) ‘key messages’ presentations.
- Ad-hoc experience analyses (including GLMs) on behalf of both current and potential clients, and communicate results back to them, involving face to face meetings and presentations.
- Work closely with Operations to ensure successful delivery of the new treaty and addendum annual implementation plan into SAP. This will involve the management of the R&D data analysts, supporting them to clean raw data and check our SAP Extracts, and diagnosing / resolving complex problems that arise with the Extracts to ensure they are suitable for R&D’s needs in the Experience Analysis.
- Contribute to ensuring that the knowledge in the Operations team on the SAP Experience Analysis Extract (EE), and R&D’s requirements, is up to date. This may involve supporting Operations with complex mapping designs.
- Support the development and maintenance of the quantifying insurance risk framework across all lines of business through the calibration of probability distribution functions and documentation of methodologies.

**Qualifications & Experience**

Essential Expertise:

- Qualified Actuary with a minimum of 7 or more years’ of total experience;
- A strong background in conducting detailed experience analyses, and/or pricing, for Life and Healthcare products in Asia;
- Excellent communication skills, both written and verbal;
- Good awareness of SQL, Excel and ideally other systems such as R, Tableau or Emblem, and a willingness to adopt to new software or systems as required;
- Strong interpersonal skills and management skills;
- Strong understanding of actuarial principles and processes, and strong analytical skills;
- Strong knowledge of Asian life and/or health insurance products, common and unusual benefit designs and policyholder options.

Desirable Experience:

- Good understanding of Generalised Linear Models or other machine learning techniques;
- Ability to take the lead on projects;
- Experience in building tables of mortality /morbidity rates;
- Data mining and multi-variate analysis;
- Good at finding creative solutions to analytical problems