The Payment Group at Swan leverages industry knowledge, payments expertise, and general insight to build and operate the API-based banking products and the platform that power cash collection, cash storage, and money movements for all Swan financial products.

Ultimately, the group is working toward a future in which all the complexities of handling money are hidden from Swan’s partners and end-users—whether that’s adopting new payment methods, reconciling various entries (technical, accounting, and cash), integrating with banks and financial partners globally, or addressing regulatory obligations.

Within this Group, the Payment Product team sits at the intersection of Strategy, Go-To-Market, Compliance, Risk, Data, and Engineering. The team oversees all stages of the product lifecycle — from discovery to sale — while aligning with the company’s global strategy and core objectives. The Payment Product team, consisting of Lead Product Managers and Product Managers, ultimately owns the payment product roadmap.

The Payment Product Manager leads the strategy and roadmap for a key area of our payment banking product. They are end-to-end accountable for the success of their product — strategy, delivery, adoption, performance, and impact.

They develop scalable, high-impact solutions within our payment platform by collaborating with clients, internal teams, and financial providers (card schemes, processors, fraud vendors, etc.) — turning evolving specs into thoughtful product capabilities.

As a Product Manager l Transaction Risk, you will own Swan’s transaction scoring engine — the signals, features, rules, Machine Learning models, and decisioning logic that protect Swan and its partners from fraud, while keeping legitimate transactions flowing.

You will report to a Payment Product Lead, and you will be the end-to-end owner of Transaction Scoring risk performance: Fraud Detection Rate, False Positive Rate, and the trade-off between them. The Head of Risk is Accountable for the fraud framework and risk appetite; you are Responsible for the day-to-day optimization loop.

Unlike other Product Managers at Swan, your closest build partner will be Data rather than an Engineering squad — and a dedicated data squad to build and run Machine Learning models may come later as the scope grows.

You’ll leverage AI boldly to amplify your impact — discovery, spec writing, signal analysis, ops automation, prototyping.

What you’ll do

• Own the transaction risk roadmap end-to-end. You are the single accountable owner of fraud detection on transactions—strategy, roadmap, delivery, and performance—across all payment flows (SEPA Credit Transfers, SEPA Direct Debits, cards issuing & acceptance, etc.).

• Push the Fraud Detection Rate/False Positive Rate frontier. Drive the iterative tuning loop on rules, features, signals, and Machine Learning models. Constantly improve Fraud Detection Rate at a capped False Positive Rate.

• Measure before deciding. Partner with Data and Engineering to make sure every flow emits the right signals, and that decisions are measurable end-to-end.

• Run the weekly Transaction Scoring Tuning loop with Flow Product Managers, Data Partner, and the FinCrime Lead. Turn pattern intelligence (new scam techniques, mule behavior, fraudulent IBAN lists) into shipped rules and model updates — fast.

• Implement AML-CFT and sanctions rules on the platform under the Compliance Team’s mandate — keep them up to date and partner with Compliance to monitor their performance and improve precision, in particular by driving false positives down while keeping detection high.

• Keep the platform consistent. Provide the signal taxonomy, data contracts, and change-management discipline so flow-specific Risk Scores (Merchant Risk Score, KYC/Customer Risk Rating) feed the Transaction Scoring engine cleanly.

• Also own external transaction monitoring. Whatever the tool or provider, you own every external check at transaction time that impacts acceptance rate or UX — work with each provider to monitor performance and tune their setup.

• Make trade-offs explicit. Translate abstract risk scores into concrete product actions (block, step-up, allow), and own the trade-off between fraud losses, user friction, and operator load.

• Make every decision auditable. Every rule, score, signal, and decision must be traceable and explainable end-to-end — so ops, FinCrime, Compliance, and post-mortems can always reconstruct why a transaction was blocked, stepped-up, or allowed.

• 3+ years in Product Management with end-to-end lifecycle ownership from discovery to release, ideally on a data-intensive or Machine Learning-powered product, or relevant experience as a risk/fraud strategist, data scientist, or fraud product specialist in a payments/Fintech/neo-banking environment

• Comfort with the Fraud Detection Rate/False Positive Rate trade-off. You’ve shipped or tuned detection systems (rules, models, or both) and know how to instrument, A/B test, and iterate on them

• Payments and fraud industry knowledge is a strong plus — card scheme rules, SEPA flows, scam typologies (APP fraud, mule networks, account takeover), AML-CFT basics

• Strong analytical skills — you can quickly become a subject matter expert in complex products, and you’re at ease with SQL/data tooling to investigate signals yourself, or you know how to leverage AI for this

• Tech-savvy, with a genuine passion for technology and product development

• Highly autonomous and comfortable using AI boldly to amplify your impact — discovery, analysis, prototyping, ops automation. You drive and lead efforts without waiting for an Engineering squad.

• Strong interpersonal skills, with a drive to coordinate and lead consistent efforts: you thrive in international teams, you’re enjoyable to work with, and you’ll pull together Risk, Compliance, FinCrime, Data, Engineering, and Operations on a daily basis

• Adaptable to changing requirements in a fast-paced environment, and comfortable operating under regulatory constraints

• Fluent in English; French is a plus

• 30-minute interview with a Talent Acquisition Specialist

• 45-minute interview with the relevant Payment Product Lead

• Take-home project/business case on a transaction scoring tuning problem

• 30-minute presentation of the business case to the Payment Product Lead & the VP Product & Operations - Payment, followed by a 30-minute interview with the VP Product & Operations - Payment

• 30-minute interview with the Chief Risk Officer or the VP Data

• Final interview with the Chief Product Officer