Our Client is part of a FTSE 250 company listed on the London Stock Exchange and since 1997 it has developed into an international financial services group specialising in the provision of credit and insurance with operations in the UK and Ireland, Poland, the Czech Republic, Hungary, Slovakia and Mexico.

The company has a clear strategy: to maintain steady growth in the UK; expand their international operations; increase the range of financial services on offer; and become a leading international provider of financial services to its chosen markets.

Reporting into the Risk Director:

• Personally, and/or by leading of a team of Analysts, design, develop and apply appropriate models and data sources to predict relevant risk behaviour
• Research and understand all data sources available and their respective power for risk modelling and develop appropriate analytic datasets
• Define sample windows, good-bad definition, data classings and build appropriate models using regression, multivariate analysis, or analogous techniques.
• Develop behavioural scoring models for customer management, collections and recoveries
• Apply scorecard segmentation techniques as relevant
• Develop alternative customer management and collections policies, and by undertaking champion-challenger testing; derive and apply increasingly profitable strategies
• Evaluate the cost / benefit of utilising external data sources or software tools to improve discrimination power, and make purchase recommendations
• Liaise with Finance and Marketing to ensure customer management strategies maximise customer profitability and profit margins
• Develop risk segmentation to determine eligibility for cross sell and retention programmes
• Provide necessary assumptions and assistance to Finance to enable effective profitability analysis by risk segment
• Contribute to cross functional work on maximising profitability of customer propositions
• Lead the monitoring of the portfolio's credit performance, identification of trends, forecasting bad debt, and providing the basis for effective bad debt provisioning
• Establish relevant MI for monitoring arrears performance, collections and customer management tests and strategies
• Forecast and report bad debt trends against target
• Undertake relevant analyses and make recommendations for corrective action as relevant
• Work with Finance to develop and implement an accurate provisioning methodology which meets Finance and Business requirements
• Liaise with Finance, Marketing, and Operations teams to produce detailed financial and operational statistics
• Manage the planning process for the above to ensure that all developments are delivered within appropriate time and cost scales
• Liaise with Operations for implementation of Credit policies
• Including User Acceptance Testing processes
• Document all Processes, and Decisions
• Document underwriting policies and bad debt provisioning methodologies
• Provide auditable documentation for all customer management credit policies
• Liaise with internal customers and both internal and external suppliers
• Maintain awareness of relevant legislation and its implications on the customer management process and its underlying data requirements
• In particular Credit Reference data

You can ideally offer:

• An Honours degree ideally in a quantitative subject such as Mathematics, Statistics or Operations Research
• A minimum of five years experience in modelling and analysis using statistical techniques such as regression, cluster analysis, multivariate analysis and profitability analysis
• Experience of customer strategy management, and collections processes
• Three years team management experience including prioritisation and workload allocation, and team work at a senior level
• Experience of credit risk modelling or similar, including hands-on knowledge of SAS or equivalent statistical packages
• Programming, database extraction and reporting skills
• Demonstrable understanding of how external factors influence credit risk

To apply for this role click here to email us quoting Ref: JA1009 or call 020 7274 7998