Fraud Pricing Analyst

Job Title: Fraud Pricing Analyst
Target Start Date: ASAP
Contract Type: Permanent, Part Time, Full Time, Job Share option available
Salary Range: £29,600 – £35,000
Location: Eastleigh – hybrid, once a month
Work Level: 3
Closing Date for applications: Friday 7th November
Hiring Manager: Hetal Sumaria

Fraud Pricing Analyst:
We are looking for a commercially minded and analytically strong Pricing Analyst to support the development and implementation of pricing strategies with a particular focus on fraud mitigation. This role will sit at the intersection of Pricing and Fraud, helping to ensure our pricing models and decisions reflect emerging fraud risks and opportunities.

The analyst will be the key pricing contact for the Fraud team, helping to assess, price, and implement fraud-related models and interventions across all lines of business.

Main Responsibilities

• Fraud-Focused Pricing Support:Collaborate with the Fraud team to assess new fraud data, support pricing of fraud models (e.g., ID theft, fronting), and act as the key pricing contact for fraud initiatives.
• Data Analysis & Insight Generation:Analyse fraud-related data across products and channels to identify trends, quantify impact, and integrate fraud variables into pricing models, while monitoring strategy performance.
• Pricing Strategy & Execution:Contribute to pricing strategies that balance fraud risk with commercial and customer outcomes, and support pricing changes through analysis and stakeholder engagement.
• Stakeholder Collaboration:Build strong relationships with Fraud, Underwriting, Product, and Data teams, and communicate insights effectively to both technical and non-technical audiences.
• Governance & Compliance:Ensure all pricing and fraud-related decisions meet governance and regulatory standards, with thorough documentation of methodologies and assumptions.

Skills and experience

• Holds a strong quantitative degree in Statistics, Mathematics, Actuarial Science and has experience in a data-driven role.
• Understands insurance products and distribution channels (direct, intermediary, aggregators), and considers broader business and strategic implications in pricing and fraud initiatives.
• Skilled in statistical analysis, data validation, and handling large datasets using SAS, SQL, or Python.
• Familiarity with predictive modelling techniques such as Logistic Regression, GLMs, GBMs, Decision Trees, and Neural Nets.
• Demonstrates a proactive approach to exploring data, challenging assumptions, and engaging with emerging fraud typologies and pricing techniques.

To find out more about this role and for information please contact Zoe Powell OR Hetal Sumaria.

Alternatively, click on the “Apply Button” to be considered.