Fintech · Regulated SaaS · Product Governance
FlowPay — Product Governance & KPI System
Context
Product team operating in a growing environment where increasing regulatory and technical complexity requires clear, aligned, and decision-ready governance structures.
Scope
Scenario-based exercise using public dataset; designed to reflect enterprise decision workflows.
Problem
Teams lacked a shared view to assess whether credit decisions remained fair, interpretable, and compliant as data and models evolved.
My Role
Product analytics & UX-led dashboard design translating business and regulatory/ operational goals into KPI definitions, decision-ready views, and documentation.
Key Decisions
Structured role-based governance views
Prioritized trend-based fairness
signals over static compliance checks
Translated responsible AI and privacy requirements into measurable product KPIs and review checks.
Outcome
Improved clarity in fairness and compliance monitoring
Increased confidence in decision stability
Clear KPI structure for fairness/compliance monitoring, with role-based views supporting consistent review and decision-making.
Decision Impact Summary
Key Insight
Fairness and compliance risks were not detectable through static compliance checks, but emerged through trend-based KPIs and role-specific governance views as models, data distributions, and approval logic evolved.
Decision Supported
Enabled leadership, data, and compliance teams to continuously assess whether credit decisions remained stable, interpretable, and compliant, supporting informed trade-offs between model performance, fairness thresholds, and regulatory exposure.
Business Impact
Reduced regulatory and reputational risk by introducing decision-ready governance signals, increasing confidence in long-term product stability, audit readiness, and responsible AI operations in a regulated fintech context.
UX Dashboard
UX Strategy & Dashboard Architecture
WorkWave is structured into three executive-ready dashboard layers, each aligned with a specific organizational decision need.
Executive & Risk Leadership —
Governance Overview
bias trends over time
feature importance (e.g. income, age, credit history)
mitigation impact
drift detection
bias level
credit score
Data Science & ML Teams —
Fairness Analysis
approval distribution
fairness baseline vs outcomes
Analysis Summarys
Compliance & Legal Teams — Regulatory Alignment
AI Act compliance checklist
GDPR data-mapping overview
readiness score
Incident trend
audit-ready documentation
Why it matters
Shows how product analytics and UX-informed governance translate regulatory
complexity into actionable product decisions in regulated SaaS environments.
Applicable contexts
Fintech · Regulated SaaS · AI Governance · Enterprise Software
Extended case details available upon request.