3 weeks ago

Credit Risk Analyst (Senior)

Solihull 30K - 70K Permanent

Job Reference: DWO87

A number of opportunities have come up for Senior Credit Risk Analyst’s at all levels to work for a market-leading Financial services organisation right in the heart of Solihull. With this opportunity, you will get a chance to work with a fantastic team working on some exciting Greenfield projects, while also working with or getting trained to work with Machine Learning software.

This is a new role within Credit Risk to provide analytical support to a transformation project within the Asset Finance business line. For the first 12 months, the role will involve creating both Credit Risk and  Financial Crime /Fraud models, configuration of new rules in both Fraud and Credit Risk Decision Engine applications and creation of an on-going monitoring framework.

After the initial 12 month period the role will transition into a joint Financial Crime and Credit Risk role, taking responsibility for the development, analysis, validation, implementation and monitoring of Financial Crime / Fraud rule sets, models and portfolio monitoring. 


  • Producing in-depth documentation of the models and the production framework to the required standard to obtain the relevant sign-off
  • Implementing the models into the live environment in a manner that is consistent with the development objectives, ensuring 100% accuracy and timeliness of the calculation of the outputs
  • Creating and producing the required regular validation of the models
  • Ensuring the regular monitoring of the stability, integrity and effectiveness of the models, highlighting adverse changes and proposing remedial action plans
  • Timely production of the full suite of monitoring reports required as part of the model governance framework
  • The development of Financial Crime and Credit Risk Application and Behavioural Scorecards that will be used throughout the account lifecycle, from application stage through to portfolio monitoring
  • The development of optimised Fraud and AML rule sets to ensure risk appetite is met whilst reducing false positive rates
  • Implementing and configuring optimised Financial Crime rule sets in specialist fraud applications and monitoring the fraud model model outputs to ensure stability of the framework, identifying adverse changes to be actioned
  • Ensuring data integrity, documentation, validation, stability and controls are in place for all data elements used within the modelling and live production of the model outputs
  • Supporting in the development and execution of the end-to-end application journey
  • Providing support and development to junior analysts
  • Providing support as needed by the Head of Data Science and Financial Crime Manager 


  • Proven experience in statistical modelling and analytics in Fraud / Financial Crime
  • Good working knowledge of third-party Financial Crime data sets and Identification/Authentication CRA data
  • Good knowledge and understanding of general statistical modelling (Logistic and Linear Regression, Scorecard development, Reject Inference, Fraud rule optimisation) and related stats (Gini, information value, K statistic, R squared, population stability etc.)
  • Excellent verbal and written communication skills
  • Ability to work independently and, at the same time, support the wider project team as needed

Qualifications and experience

Educated to degree level (min 2:1) in mathematics, statistics or equivalent. Modelling experience using SPSS or SAS and experience using Machine Learning techniques and tools would be preferable.

If you feel you have the required skills and experience to be considered for this opportunity and would like to hear more details, please forward an up to date version of your CV, and you will be contacted back within 24 hours.

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