Head of Credit Risk

We’re looking for a Head of Credit Risk: This is a high-impact role with direct exposure to the CRO and close collaboration with Product, ML & Data Science, Operations, and Engineering. You will be designing the risk foundations from the ground up and shaping the future of SME lending in Europe. 

What You Will Be Doing

• Own and drive the development of end-to-end credit risk framework for all credit products including eligibility, underwriting, scoring models, limit setting, risk appetite, monitoring, and reporting. Engage with external vendors, where necessary, to enhance the credit risk detection capabilities;

• Create the methodology for and closely work with Machine Learning Engineers to develop and continuously improve Finom’s Credit Risk Engine so it could be proudly recognised as best in class: excellent risk parameters AND a smooth customer experience;

• Partner closely with Heads of Product and Engineering to embed risk into product design and strategy from day one;

• Architect the data strategy: Decisioning tools, transactional data, multi-country bureau landscape, behavioural data, accounting software, government registry data and first party transactional signals on Finom’s accounts. Guide the ML & DS team in building, validating, and iterating credit scoring and related risk models.

• Build and own the portfolio monitoring stack;

• Design, build and calibrate the early warning indicators / credit monitoring system: transaction velocity, balance deteriorating, payment pattern changes, supplier/customer/revenue concentration shift, signals from the external data sources

• Act as a strong Second Line of Defence (2LoD), ensuring robust origination, monitoring, and collections processes;

• Own and continuously improve credit risk policies, risk appetite frameworks, and reporting;

• Ensure alignment with EMI / PS4 regulatory requirements and evolving European standards;

What you'll bring:

• 7-10+ years of experience in credit risk, with hands-on expertise in SME lending and credit cards and the associated credit risks and fraud risks;

• Strong experience with automated underwriting and risk models in fintech or digital banking environments;

• STEM/quantitive degree: physics, data science, applied mathematics, statistics, econometrics or quantitive finance is a strong plus;

• Solid understanding of risk governance, policies, and processes management;

• AI-native mindset — comfortable leveraging AI tools and agents to enhance productivity and decision-making;

• Unit-economics/ product led growth mindset (eligibility, conversion, expected loses, cost of risk, false-positives as missed revenues, risk-adjusted margin), not just control;

• Critical thinker with a strong ownership mindset, who is keen to challenge traditional approaches;

• Highly collaborative, with the ability to align diverse stakeholders (Product, Legal, Finance, Engineering, ML/DS);

• Analytical, structured, and pragmatic — able to combine deep detail with big-picture thinking.