PRODUCT LEADERSHIP · PAYMENTS · REGULATED SAAS · APPLIED AI
Complex problems.
Clear product decisions.
I'm Rhys Dowsall, a Product Manager and Product Owner with 7+ years' experience turning customer, commercial and regulatory complexity into practical outcomes across financial services and SaaS.
Available for Product Owner, Product Manager and Business Analyst opportunities · Belfast / UK remote
SELECTED IMPACT
SELECTED WORK
Real problems. Measurable outcomes.
Not a catalogue of job descriptions — a few examples of the problems I've worked through and the decisions behind them.
01 · PAYMENTS & SAAS · PLOTBOX
Scaling digital payments—without scaling the risk
As Product Owner for the Finance stream, I worked across payment links, card and ACH workflows, bulk processing, settlement and reconciliation as PlotBox Pay moved into a higher-volume phase.
The problem
Payment capability had to support more volume and more complex customer workflows while preserving financial controls, clear status visibility and a safe release path.
Product decisions
I shaped a card-first bulk-payments MVP, separated ACH as a follow-on, defined confirmation, permission and reporting safeguards, and used feature flags and controlled customer validation.
Delivery constraints
The work crossed customer operations, finance, Engineering and external payment services. Security gaps and reconciliation needs meant release readiness mattered as much as feature scope.
Programme outcome
Monthly PlotBox Pay throughput grew from approximately $230k to $1.5m over roughly six months. That is programme-level context—not a claim that one feature caused the full increase.
02 · REGULATED FINTECH
PSD2 & stronger authentication
Mapped affected digital banking journeys and coordinated delivery of an interim OTP solution followed by biometric authentication.
Outcome: regulatory change delivered while protecting the customer journey.
03 · AI & PRODUCT DISCOVERY
AI Product Discovery Assistant
Building an experiment that turns unstructured customer feedback into evidence-backed themes and opportunities, with traceability and human oversight designed in.
Explore the project ↗PRODUCT LAB · EXPERIMENT 01
Would you ship it?
94% accuracy sounds pretty good. But is it good enough?
A two-minute experiment in AI product judgement, risk and making decisions with incomplete information.
Make the call ↓AI FEATURE EVALUATION · STAGE 1 OF 2
94% accuracy2.1% hallucination+17% CSAT£0.11 / conversation
Would you ship it?
Choose using the evidence available. You can revise your call when more context appears.
NEW EVIDENCE · STAGE 2 OF 2
Your initial call:
The errors are not evenly distributed.
Some customers receive incorrect payment dates, account balances and arrears information. Aggregate accuracy hides a small number of potentially high-impact failures.
High-severity riskFinancial harm and loss of customer trust
What is your decision now?
MY PRODUCT CALL
Your revised call:
Run a controlled, low-risk pilot.
Do not approve a broad release from an aggregate accuracy score. Preserve the value while containing the risk:
- Block autonomous answers for payments, balances and arrears.
- Route high-risk or uncertain cases to a person.
- Measure errors by severity and customer impact—not just volume.
- Set stopping thresholds, monitor the pilot and expand only when the evidence supports it.
The important skill is not guessing the “right” first answer. It is identifying missing evidence and adapting the release plan when the risk changes.
HOW I WORK
Evidence before theatre.
I tend to gravitate towards messy product problems: payments that don't reconcile, processes with too many manual steps, requirements that aren't as simple as they first appear, and increasingly, questions about where AI genuinely helps.
DiscoverUnderstand the real problem
PrioritiseMake trade-offs explicit
DeliverTurn insight into change
MeasureLearn what actually happened
EXPERIENCE
PlotBoxProduct Owner — Finance
Avant MoneyDigital Product Manager
Vodafone IrelandService Delivery — via Teleperformance
First Derivatives / KXBusiness Development
LexisNexisLegal Research & Training
LET'S TALK
Interesting product problem?
I'm always happy to talk product, payments, digital transformation, applied AI and the awkward problems in between.