Fraud Analyst at Amplifi Capital – London, England, United Kingdom
Job Description
About Us:
One-third of the UK working-age population is not able to access mainstream financial services. These people find themselves excluded from affordable credit and treated poorly by mainstream financial institutions. Too few are successfully supported on the journey to financial health. Our purpose is “To improve the nation’s financial health through accessibility, affordability and community.”
We are a fast-growing social FinTech company giving not-for-profit Credit Unions in the UK access to a state-of-the-art fintech. We aim to grow a select group of Community Lenders into a network of challenger banks offering a viable alternative to high-cost lenders.
The Role:
At Amplifi, data lies at the heart of all strategies and is key to combating fraud. As a fintech in the consumer lending space we strongly believe that innovative use of data and technology are key to delivering on our strategic growth objectives. The Fraud Analyst role plays a vital role of protecting us and our customers from fraudsters allowing us to offer the best products and services to our customers.
As a Fraud Analyst, you are expected to carry out analysis of data patterns relating to fraud, assess new tool and technologies to help us combat first, second- and third-party fraud. This role will be hands-on with data, and you will work closely with other teams to develop effective solutions. You will also interact with external suppliers to assess their proposed solutions and to stay abreast of the latest trends and innovations. You will report to the Credit Risk Manager and play a key role in guiding other colleagues on best practices to prevent fraud.
Requirements:
- Create, maintain and disseminate appropriate metrics for the monitoring of Fraud within the business
- Work with business stakeholders to identify fraud challenges and solutions that offer the greatest opportunities to the organisation
- Carry out analysis to support ongoing fraud prevention including acquisition fraud and in-life fraud
- Summarise and present performance, recommendations and proposals to stakeholders up to C-level execs and external stakeholders (such as partners and investors) with actionable insights
- Explore large sets of structured and unstructured data from disparate sources, including new, and unconventional ones, and come up with innovative ways of using this data. Design appropriate tests to collect additional data, if required
- Provide insights on advances in fraud prevention, identifying opportunities within the business for the execution of new ideas, tools and platforms
- Work with wider Data Engineering, Decision Systems, Decision Science teams to ensure proper testing, validation and deployment of data, new service and solutions
- Contribute to guidelines on fraud strategy and underwriting process, ensuring practices are aligned to regulations and well documented
- Support and mentor more junior colleagues
This is a pivotal role in the analytics team of a fast-growing business and hence the ideal candidate would be someone who:
- Is passionate about Data, Analytics and Fraud prevention
- Is self-motivated and proactive; shows ownership and initiative – Not afraid of being hands-on and possess a roll-up-your-sleeves attitude to get things done
- Has excellent communication and stakeholder management skills
To be successful in the role, the candidate should:
- Have at least 3 years of experience in risk analytics roles, including a significant exposure to fraud prevention projects, preferably in a consumer lending context
- Have strong ability in querying and extracting insights from large datasets using SQL
- Have a proven practical experience of fraud prevention technologies and techniques, including using UK bureau data (e.g. Experian, Equifax or TransUnion)
- Have a solid grounding in probability and statistics
- Have experience in creating data monitoring and KPIs with tools like PowerBI/Tableau or similar
- Preferably have a degree in a numerate (STEM) discipline or else have equivalent skills derived from self-learning / online courses
Also Desirable:
- Modelling experience, applied to Financial Services
- Financial services experience, particularly consumer credit
- Experience managing Proof-of-Concept projects
- Experience of A/B testing
- Scale-up experience
