AI Product Manager for Fintech
Fintech products operate in one of the most heavily regulated, trust-sensitive environments in software. I help fintech teams ship compliant, trusted, and commercially successful products — as a fractional AI PM who understands APRA, ASIC, PCI-DSS, open banking, and the UX craft needed to make financial products that users actually trust and regulators approve.
Why fintech products need an AI PM who understands regulation and trust
In fintech, a poorly scoped compliance feature does not just delay your roadmap — it can trigger a regulatory breach. A trust failure in the product experience does not just hurt NPS — it can collapse a user's willingness to keep money in your platform. These stakes demand a PM who has internalised the regulatory landscape and can translate it into product requirements without turning every story into a compliance ticket.
I help fintech teams move fast inside the regulatory constraints by mapping compliance obligations early, designing trust-forward UX that satisfies regulators and converts users, and using AI to power smarter fraud detection, personalised financial insights, and automated compliance monitoring.
$20M+
Revenue influenced across product launches
1B+
Impressions generated through product and growth execution
12+
Products launched from 0→1 across multiple sectors
How I help fintech teams as your AI PM / PO
- Regulatory compliance mapping: translating APRA, ASIC, PCI-DSS, and CDR obligations into product acceptance criteria and roadmap sequencing
- Trust UX design: disclosure flows, consent mechanisms, security signalling, and dispute resolution that satisfies regulators and converts users
- Open banking and API integration product requirements: CDR consent design, data cluster strategy, and financial data feature development
- AI-powered fraud prevention: risk model requirements, friction-tier UX design, and measurement frameworks for fraud loss vs. abandonment
- Financial product personalisation: LLM-driven insights, spend categorisation, and recommendation features built on defensible data practices
Engagement models
Built for fintech companies navigating licensing milestones, compliance audits, and product-market fit — with flexible structures that match your funding stage and regulatory calendar.
Fractional PM/POCompliance product auditOpen banking product sprintAI fraud prevention roadmap
FAQs
How do you approach regulatory compliance (APRA, ASIC, PCI-DSS) in fintech product work?
Compliance in fintech is not a constraint on product — it is a product requirement like any other, and it needs to be sequenced into the roadmap with the same rigour as a feature. I map the applicable regulatory obligations early in discovery: APRA prudential standards if you are operating in the deposit-taking or insurance space, ASIC licensing and disclosure requirements for financial product issuers, and PCI-DSS scope for anything touching card data. The output is a compliance requirements register that feeds directly into acceptance criteria on stories. I also help teams design compliance-forward UX — disclosure flows, consent mechanisms, dispute resolution — that satisfies the regulator without destroying conversion.
How do you build user trust in a fintech product, particularly for newer or challenger brands?
Trust in fintech is built through a combination of social proof, security signal design, and transparency in the product experience. For challenger brands without incumbent trust equity, I focus on: surfacing relevant credentials (AFSL holder, ADI status, or equivalent) at the moments of highest user anxiety; designing security flows that feel reassuring rather than alarming; and creating transparency in fee structures, data usage, and dispute processes that the incumbent banks historically avoided. I also use A/B testing to validate which trust signals actually move conversion — not all trust signals are equal and the wrong ones can create friction.
What is your experience with open banking and banking API integrations in Australia?
The Consumer Data Right (CDR) and Open Banking framework in Australia creates both a product opportunity and a technical complexity. I have worked with teams building on top of accredited data recipient infrastructure and understand the product decisions involved: which data clusters to request and why, how to design consent flows that achieve high completion rates while meeting CDR consent standards, and how to translate raw financial data into user-facing insights that justify the data sharing. I work closely with engineering to define the API integration requirements and with legal/compliance to ensure the CDR implementation is accreditation-ready.
How do you incorporate fraud prevention into fintech product design without degrading user experience?
Fraud prevention and user experience are in constant tension in fintech — every friction point you add to stop fraud also stops legitimate users. I approach this as an optimisation problem: using AI-powered risk scoring to apply friction selectively (step-up authentication, transaction delays, manual review) based on real-time risk signals rather than blanket rules. The product goal is to make the friction invisible to low-risk users and proportionate to the risk level for flagged transactions. I define the risk model requirements in collaboration with the data science team, design the UX for each friction tier, and instrument the system so the team can measure both fraud loss rates and legitimate transaction abandonment.
Building a fintech product that earns trust and stays compliant?
Let's map your compliance obligations, identify your trust gaps, and build a product roadmap that moves fast without regulatory risk.