Quant Analyst

Overview

Our client is one of the leading insurance groups in the world. They own some of the most famous insurance brands in the UK, providing insurance for both private individuals as well as small and medium sized businesses. They provide insurance products like motor insurance, buildings and contents (household) insurance, travel and pet insurance. Commercial insurance products include Employer's Liability, General Liability and Professional Liability, as well as commercial motor and property.

The insurance industry is currently undergoing massive changes and capital modelling will be at the forefront of developments for the next 3 years. Our client is expanding its' team to ensure that internal capital models meet the regulatory standard, as well as provide business value. This regulation is called Solvency II, which is the insurance equivalent of Basel II. The aim is to harmonise capital and solvency requirements in the insurance market.

You will be supporting your manager to ensure delivery of all key business tasks related to quantitative actuarial analysis, capital modelling, validation and management. You will also help use the capital model and other analyses in all relevant business processes, including but not limited to:

• optimisation of capital efficiency
• input into strategic decision making
• input into the budget process
• reinsurance contract value measurement
• asset allocation and investment income modelling
• measurement of the volatility in outstanding claims reserves
• capital allocation to product lines, including use within pricing
• capital requirements for new products
• measurement of the potential capital implications of acquisitions/disposals

Candidate Requirements

• Experience using analytical and statistical techniques to make commercial decisions
• Excellent analytical skills gained within finance, insurance, banking, quantitative analysis etc
• Innovative thinking: ability to see problems from different angles in order to find solutions.
• Proven ability to work under own initiative and own issues to resolution
• Good communication skills especially to senior non-specialists.
• Relevant project management experience
• Evidence of contributing to projects that deliver real business change with quantifiable value added

A very strong mathematical and statistics background is required; candidates should ideally have a Master's level (or higher) in mathematics, statistics, operational research, physics, engineering etc, combined with excellent computing skills. There is no formal requirement for knowledge of (say) C++, although those who are familiar with Excel, SAS and Visual Basic programming will be at an advantage. Knowledge of stochastic modelling technique (eg Monte Carlo), modelling with @Risk etc will be useful but is not essential. Knowledge of Access and Oracle / SQL would also be useful.