Head of Analytics and Advanced Modelling

at  Guardrisk

INTRODUCTION

We are seeking a highly skilled and experienced Head of Analytics and Advanced Modelling to lead our analytics team within the non-life insurance sector. The ideal candidate will be a qualified or nearly qualified actuary with a strong foundation in general insurance principles. In this role, the candidate will be responsible for directing the development and refinement of underwriting models to assess risk, improve pricing accuracy, and enhance portfolio management. Additionally, the candidate will collaborate with business and other stakeholders to translate complex data analytics into actionable insights that drive business decisions and strategies.

REQUIREMENTS

• Educational Background:

• Qualified or nearly qualified actuary with successful completion of at least F103 General Insurance Principles exam.

Technical Expertise:

• Minimum of 8 years of experience in the non-life insurance industry.
• Proficiency in IGLOO/Remetrica software is highly desirable.
• Knowledge of climate modelling and its applications within the insurance industry.
• Expertise in exposure and aggregation modelling and monitoring.

ROLE PURPOSE

Lead the development and refinement of underwriting models to assess risk, improve pricing accuracy, and enhance portfolio management. Additionally, the candidate will collaborate with business and other stakeholders to translate complex data analytics into actionable insights that drive business decisions and strategies.

DUTIES & RESPONSIBILITIES

• Leadership & Strategy:

• Lead the analytics and advanced modelling team, providing strategic direction and fostering a culture of innovation and excellence.

• Oversee the development and implementation of advanced analytical models to support underwriting, pricing, risk management, and strategic decision-making.

Capital Modelling:

• Guide the team in using capital modelling software to perform sophisticated analyses on the economic impact of structures and products.

• Ensure the team provides insights on capital efficiency and risk transfer solutions.

Underwriting Analytics:

• Lead the development of advanced statistical and predictive models for risk assessment.
• Guide the continuous improvement and refinement of models based on new data and emerging market trends.
• Collaborate with the pricing team to translate model outputs into effective and competitive pricing strategies.
• Implement processes for ongoing monitoring, validation, and recalibration of models to maintain accuracy.
• Utilize data-driven insights to optimize portfolio management, ensuring balanced risk and profitability.
• Lead the delivery of real-time data analysis and risk assessments to underwriters.
• Guide the development of tools and dashboards that provide underwriters with accessible and actionable insights.
• Lead training initiatives to enhance underwriters’ understanding of model outputs and analytical tools.
• Incorporate feedback from underwriters to refine analytical models and tools, ensuring they meet evolving business needs.

• Support the development of strategies that enhance risk selection, pricing accuracy, and overall underwriting performance.

Reinsurance Optimization:

• Lead the team in conducting in-depth analysis of reinsurance treaties, structures, and financial impacts to assist the reinsurance team in obtaining optimal reinsurance structures from both an economic capital and regulatory capital perspective.

• Ensure the team supports the design and optimization of reinsurance programs to meet strategic objectives.

Climate Modelling:

• Oversee the development and refinement of climate models to assess the impact of climate change on the company’s risk portfolio.

• Ensure climate modelling insights are integrated into overall risk management and business strategy.

Exposure and Aggregation Modelling:

• Lead the team in developing and implementing exposure and aggregation models to monitor and manage the company’s risk exposure.

• Ensure regular monitoring and reporting on risk aggregation to support risk management strategies.

Stakeholder Engagement:

• Collaborate with senior management, underwriters, and other stakeholders to communicate analytical findings and influence business decisions.

• Lead the presentation of complex analytical concepts in a clear and concise manner to non-technical audiences, including clients and partners.

Regulatory & Compliance:

• Ensure all models and analytical processes comply with relevant regulatory requirements and professional standards.
• Keep the team abreast of emerging regulatory changes and industry trends.