FinCrime Decision Quality Officer: Customer Impact
Finom
The FinCrime Decision Quality (DQ) Officer is a rare, high-impact role shaping how Finom makes risk decisions.
You are an experienced financial crime professional with deep expertise in Transaction Monitoring and Customer Due Diligence, and a track record of challenging and improving risk decisions using data and evidence.
In this role, you will evaluate, challenge, and improve financial crime decisions made by operational teams — particularly account declines and account closures — from the customer perspective. For example, was an account closed based on weak signals? Could enhanced monitoring have been applied instead?
Your goal is to design and continuously improve a framework to identify and reduce incorrect decisions affecting legitimate customers (e.g., false positives in onboarding and offboarding), and translate insights into improvements across rules, models, and decision logic.
This is not a traditional QA or audit role — you will influence how financial crime decisions are made across the organisation.
Decision Quality sits within the 2nd Line Financial Crime Risk function and reports directly to the Managing Director responsible for FinCrime Risk.
Your ultimate North Star will be to achieve 0.01% False Outcomes Rate with 99.9% confidence level.
Responsibilities
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regular identification of customer-impacting errors in:
Account declines
Fincrime-driven account closures
Fincrime-driven account restrictions
root cause analysis of unjustified actions and error patterns (controls, risk signals, decision logic, or analyst behaviour)
prepare and present clear and regular data-driven metrics & insights to various stakeholders in 1LOD and 2LOD as well as senior management of Finom Payments
escalation of errors to the right team within 1st or 2nd LOD - to improve the methodology, processes or guidance
Follow up on the initiatives targeted at reducing the number of incorrect decisions & challenge incomplete or ineffective fixes implemented by responsible functions
You will leverage advanced analytics and AI tools to scale decision quality assessments, identify patterns, and uncover systemic issues
Drive automation of assessments of False Outcomes for legitimate customers by deploying available automation tools and/or AI in order to increase efficiency of review, and drive up the confidence level of the False Outcome Rate
Drive the development of tools, systems and processes to achieve measurable prevention of customer-impacting errors in accordance with the FinCrime strategy for 2026 and beyond
You will also collaborate with Machine Learning Engineers, Product and Development teams to create and optimise the models to transition from post-factum identification of false outcomes to predictive prevention before the decision is taken
Produce work instructions and other materials to document standards and processes of the function
Initiate and perform other tasks and projects as reasonably required to drive key metrics and objectives of the function
Leverage advanced analytics and AI tools
Drive automation of False Outcome assessments
Develop tools, systems, and preventive processes
Produce documentation and standards
Perform additional tasks and projects
Coordinate the end-to-end Decision Quality review process
Who you are
- Strong experience and expertise in fincrime: CDD, TM, AntiFraud in a bank or fintech;
- Proven track record of using data to challenge or recalibrate risk rules, limits, or policies;
- Solid analytical skills: you can structure problems, dig into data with product/BI partners, and quantify impact;
- Experience running root‑cause analysis and turning it into systematic fixes rather than one‑off patches;
- Excellent communication skills: you can summarise complex risk topics in simple, sharp narratives for senior stakeholders as well as junior analysts;
- Comfort presenting to senior management and constructively challenging decisions when needed;
- Ability to work cross‑functionally with Ops, Risk, Product, and Data teams;
- A builder’s mindset: you are happy to start hands‑on and then scale into a more structured function/team over time;
- Prior experience setting up decision‑quality, QA, or model‑governance style functions;
- Experience in high‑growth fintech environments;
- Knowledge of EU regulatory expectations around CDD/TM and offboarding.
You are a critical thinker who is comfortable challenging decisions with evidence, not opinions. You enjoy living in the intersection of risk, customer fairness, operational efficiency, and data.
You should have:
What success looks like
- You achieved material reduction in customer-impacting errors related to customer account opening and closure;
- You created a сlear, trusted framework for assessment of false outcomes;
- You understood and planned out the path to predictive prevention of false outcomes;
- You developed a productive working dynamic with the representatives of 1st and 2nd LODs which produces measurable improvement to the key metrics.
Interview Process
Recruiter Interview -30 mins
1st Interview - 60 mins
case & test
Final Interview 60 mins