Posted by At Barclays, each day is about being more – as a professional, and as a person. ‘Be More @ Barclays’ represents our core promise to all current and future employees. It’s the characteristic that we want to be associated with as an employer, and at the heart of every employee experience.
Data Analytics – Fraud
Job Description:
•Ensure effective score and rule performance management for fraud detection tools ensuring optimal False Positive rates and Key Performance Indicators such as alert volume SLAs, Victims of fraud, Fraud Losses are set and achieved.
•Production of the design, development and deployment of analysis and monitoring to prevent and detect fraud, responding to emerging trends and attack. Identify, monitor, escalate and respond to emerging fraud trends in MO, attack profile, customer profile.
•Provision of fraud systems/data Subject-matter-expertise in the evaluation and development of new fraud systems / tools and their implementation.
•Supports the delivery of predictive analytics and models to allow the development of new Fraud Management solutions and better understand fraud control strategies that may be deployed
•Able to communicate complex data/ system issues and solutions to a varied stakeholder audience
•Excellent communication skills, both verbal and written
•Ability to absorb large quantities of data at speed, making the right decisions quickly with limited data availability
•Advanced statistical understanding (ideally working knowledge of statistical modelling and neural networks)
•Passionate about data analysis and how this contributes to the business
•A self-motivated team player who is able to define structure and prioritise work for self, but who also has the flexibility and capability to change priorities when circumstances dictate.
Preferred Qualifications:
•Degree or equivalent in statistics, mathematics, operational research or related area or significant relevant experience.
•Knowledge of Fraud Risk systems and controls and their operating environments
•Understanding of issues relating to card and non-card fraud