What I Do

AI systems that move financial outcomes.

I don’t build models. I build end-to-end AI systems — deployed inside banks, fintechs, and credit ecosystems.

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AI for Growth

Growth is won through intelligence.

I deploy AI systems that move approval rates, acquisition costs, and revenue per customer.

Outcome: Higher approval rates. Lower acquisition cost. More revenue per customer.

Who this is for

Banks growing credit portfolios, fintechs reducing acquisition cost, digital lenders increasing approvals for thin-file segments, and institutions building cross-sell intelligence.

AI credit decisioning

Real-time AI models using bureau data, alternative signals, and behavioural patterns.

Customer acquisition intelligence

AI-powered lead scoring and pre-qualification to identify high-quality applicants earlier.

Cross-sell & upsell AI

Propensity models that identify the right product, customer, and moment.

Approval rate optimisation

Model tuning that increases approvals for creditworthy applicants without raising default exposure.

Adaptive credit limits

Dynamic limits that grow with borrower repayment behaviour.

Thin-file lending enablement

Alternative data activation for borrowers with no formal credit history.

AI for Risk & Fraud

Fraud is stopped at the identity layer.

I deploy AI systems that verify who the user actually is — combining biometrics, behavioural signals, and anomaly detection to stop fraud before it happens.

Outcome: Lower fraud losses. Faster onboarding. Stronger compliance.

Who this is for

Banks moving beyond SMS OTP, digital lenders facing synthetic identity fraud, fintechs requiring BSP-compliant eKYC, and institutions preventing account takeover.

eKYC & biometric onboarding

Facial biometrics, liveness detection, and document verification compressed into a sub-3-minute mobile experience.

Synthetic identity detection

AI models trained to detect blends of real and fabricated data.

Behavioural anomaly detection

Real-time monitoring of user behaviour to flag account takeover, social engineering, or mule activity.

Account takeover prevention

Device intelligence, session monitoring, and behavioural AI blocking attempts before funds move.

PEP & sanctions screening

Automated screening integrated into onboarding and transaction monitoring.

Layered authentication

A post-OTP stack combining biometrics, liveness, device intelligence, and in-app verification.

AI for Credit Infrastructure

Financial inclusion happens at the infrastructure level.

I work with banks, credit bureaus, and regulators to build data architecture, scoring systems, and monitoring platforms aligned with BSP and CIC frameworks.

Outcome: Scalable credit infrastructure. Real-time decisioning. Regulatory alignment.

Who this is for

Banks modernising decisioning, credit bureaus integrating alternative data, regulators designing infrastructure, and fintechs needing scalable scoring architecture.

Bureau + alternative data integration

Credit bureau data unified with telco, e-wallet, e-commerce, and behavioural signals.

Real-time credit scoring

From monthly batch scoring to sub-second per-application assessment.

Portfolio risk monitoring

Early delinquency signals surfaced before traditional models flag them.

Cross-border exchange

Design and deployment of cross-border credit sharing frameworks.

BSP & CIC alignment

Systems designed for regulatory demands without slowing innovation.

Scalable data architecture

End-to-end architecture for real-time decisions at Philippine and ASEAN volumes.

Agentic AI & Decision Intelligence

Most AI stops at the dashboard. Real AI moves the outcome.

Autonomous workflows orchestrate data, models, and rules engines across onboarding, underwriting, and collections.

Outcome: Faster decisions. Lower operational cost. Systems that improve themselves.

Who this is for

Banks automating decision workflows, fintechs scaling without headcount, collections teams prioritising queues, and regulated institutions needing human-in-the-loop governance.

Autonomous decision workflows

AI agents that automate workflows from data ingestion to outcome.

Real-time orchestration

Layers that coordinate data feeds, AI models, and rules engines in real time.

Continuous learning systems

Models improving as repayment, fraud, and market signals accumulate.

Human-in-the-loop governance

Humans remain accountable for high-stakes decisions.

AI collections intelligence

Models identify accounts likely to respond to early intervention.

Explainable AI

Decisions made interpretable for risk teams and regulators.

Data Strategy

Decision-grade data beats dashboard-grade data.

Data strategy for AI, credit, identity, alternative data, and governance.

Focus areas

Data sourcing, data quality, governance, alternative data activation, regulatory alignment, and operating model design.

Platform Thinking

AI needs systems, not isolated tools.

Platform design that connects data, models, workflows, governance, and measurable business outcomes.

Focus areas

Reusable decision layers, production architecture, integration design, monitoring, and stakeholder adoption.