£60K + bonus
8 months ago
The role holder will be responsible for defining strategies and preparing complex analysis using a variety of languages, systems and statistical techniques for preventing credit abuse. The role includes building and maintaining predictive models to support the detection of credit abuse
Key responsibilities include:
- The role will focus on detecting and preventing 1st Party (Credit Risk) credit abuse for all products. This includes the recommendations of all procedures, policies and strategies to help develop and optimise Fraud Prevention.
- Develop real-time decisions within fraud for transactional and monitoring systems. This may include Falcon, eVision, ThreatMetrix in order to minimise loss, reduce risk, and improve the customer experience.
- Ability to define and implement new decision system strategies and perform ongoing analysis to monitor their effectiveness.
- Responsible for helping to design and manage fraud reporting for the business, ensuring that it gives key insight that is both timely and accurate.
- Identify new and emerging fraud trends, undertaking ad-hoc analysis in order to recommend appropriate action for the business.
- Assist and lead initiatives working with internal and external partners to ensure effective execution of fraud strategies preventing forms of abuse.
- Liaison with external intelligence agencies. Building intelligence through analysis and collaboration. Effective management with stakeholders and liaison with external partners will help lead the fight against fraud.
- Assisting existing customer management teams within Credit & Collections / Data Science & Decision Science to disrupt abuse.
- University degree level or similar, preferably with a numerical background.
- High intellectual capability combined with commercial aptitude.
- Competent with all Microsoft Office software (Excel, Word and PowerPoint).
- Ability to work independently, with a high level of self-motivation.
- Experience of advanced programming.
- Creativity, energy and personal drive to succeed.
- Eye for detail and aptitude to both identify and solve complex problems.
- Ability to plan and anticipate and to work well under pressure.
- Good communication skills.
- Knowledge of the credit card sector and other lending products, or at least relevant experience in Financial Services
-Python / R (40%)
Please note, should you not receive feedback 28 days, unfortunately your application has been unsuccessful. However, we may be in touch with similar relevant opportunities.