Credit Risk Analyst

About Us:

One-third of the UK’s working-age population is unable to access mainstream financial services. These individuals are excluded from affordable credit and underserved by traditional financial institutions. Our purpose is “To improve the nation’s financial health through accessibility, affordability, and community.”

We are a fast-growing social FinTech company, empowering not-for-profit Credit Unions in the UK with cutting-edge technology. Our goal is to transform a select group of Community Lenders into a network of challenger banks that provide a viable alternative to high-cost lenders. 

With a small yet dynamic team of over 200 people, we offer the opportunity to make an immediate impact and grow with us. We currently have over 120,000 customers on our platform, and this number continues to grow rapidly. Our leadership team combines over 100 years of experience at leading financial institutions, including Credit Suisse, UBS, NatWest, Capital One, and Barclays.

The Role:

At Amplifi, data lies at the heart of all strategies. 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 objectives. As a Credit Risk Analyst, you will play a key role in optimising our credit risk strategies and ensuring robust decision-making that supports sustainable growth and excellent customer outcomes.

This role focuses on analysing customer data, evaluating credit risk policies, and monitoring portfolio performance to identify areas for improvement. You will also contribute to fraud detection and prevention strategies, leveraging your skills to protect both the business and our customers.

Working closely with the Credit Risk Manager and collaborating with teams across product, pricing, data science, and operations, you will develop actionable insights that inform decision-making and drive business performance.

Responsibilities:

• Conduct in-depth analyses of credit risk policies and portfolio performance, providing actionable insights to optimise risk management strategies.
• Support the development and implementation of credit risk models and decision systems, ensuring they align with business goals.
• Monitor key metrics related to credit risk and fraud, identifying trends and recommending improvements to strategies and policies.
• Contribute to fraud analytics by identifying and analysing patterns related to first-, second-, and third-party fraud, working with the Fraud team as needed.
• Present analyses, findings, and recommendations to stakeholders across the business, including senior management.
• Collaborate with the data engineering and product teams to enhance data quality and ensure efficient integration of credit risk tools and systems.
• Assist in testing and validating new credit risk tools, processes, and decision-making frameworks.
• Stay updated on industry trends, fraud prevention techniques, and regulatory changes, sharing relevant insights with the team.

This is an important 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 credit risk management.
• Is proactive, self-motivated, and comfortable working in a dynamic environment.
• Has excellent communication skills, capable of presenting complex insights to both technical and non-technical audiences.

To be successful, you should have:

• 2+ years of experience in credit risk, fraud analytics, or a related field, ideally within consumer lending.
• Strong proficiency in SQL to query and extract insights from large datasets; experience with Python is a big plus.
• Advanced Excel skills, including the ability to work with complex formulas, pivot tables, and data analysis tools.
• A solid grounding in probability and statistics
• A solid understanding of credit risk decisioning, strategies, and affordability assessment methodologies.
• Experience in creating data monitoring and KPIs with tools like PowerBI/Tableau or similar
• Familiarity with fraud detection and prevention techniques, as well as UK bureau data (e.g., Experian, Equifax, or TransUnion).
• Excellent analytical and problem-solving skills, with attention to detail and a data-driven approach.
• A degree in a numerate discipline (e.g., Mathematics, Statistics, Economics, or STEM) or equivalent practical experience.

Also Desirable:

• Experience working with decision systems and credit scoring models.
• Modelling experience, applied to Financial Services
• Experience of A/B testing
• Scale-up experience

• Competitive salary
• 25 days annual leave
• Private Health Cover via Bupa
• Cycle-to-Work Scheme
• Subsidised Nursery scheme
• Hybrid working (2 days from home)

Commitment:

We are committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.

Please note that all offers of employment are conditional on us obtaining satisfactory pre-employment checks, including a DBS check, a credit check and employment references.