Fractional AI Transformation Lead
I drive the hard AI transformation programmes that stall without someone willing to hold the line.
20 years in financial services. Practitioner, auditor, transformation lead.
"Most financial institutions don't have an AI problem. They have a transformation problem. That is what I solve."
April Ann Fadallan-Piette, Founder & Principal Consultant, WizcaleMost financial institutions have the models, the mandate, and the investment. But enterprise-wide adoption breaks down in the room, through politics, resistance, and complexity.
I have been on every side of that room. Practitioner. Auditor. Transformation lead. That full arc is what makes the difference.
Schedule a ConsultationWhat I Do
I work with a small number of clients at a time, deeply not broadly. Every engagement is built around your specific stage, priorities, and constraints. You will work directly with me. Not a team of junior analysts with a deck.
For organisations that need to cut through the noise and identify where AI can genuinely move the needle. I help you build a clear, prioritised AI roadmap grounded in your business model, not generic frameworks.
From idea to production to revenue. I guide organisations through the full AI/ML delivery lifecycle, ensuring models don't just get built, but get deployed, adopted, and generate measurable business value.
Putting data and AI at the centre of how your organisation operates, across customer journeys, internal processes, and decision-making. This is not a technology project. It is a business transformation enabled by AI.
The hardest part is not the strategy. It is holding the line through the organisational resistance, ambiguity, and politics that every real transformation brings. I have done this across multiple business units, in a complex regulated environment, under real commercial pressure.
And everything we build, we codify. The capability stays after the engagement ends.
Building the guardrails that make AI sustainable, not just compliant. I help organisations design governance frameworks that enable responsible AI adoption while meeting regulatory expectations.
Proof of Work
These are not consulting recommendations. This is work I led, drove, and delivered in one of Asia's most complex regulated banking environments. Every number is auditable.
Proving that an AI-driven operating model could work across fundamentally different business and support units, at a standard rigorous enough to justify enterprise-wide scaling.
Led flagship DDOM implementations across Global Transaction Services (three use cases, 13 ML models) and Internal Audit (ML audit toolkit and issue summarizer). Each implementation required building cross-functional workstreams from scratch, driving stakeholder alignment without formal authority, and codifying every learning into reusable playbooks.
Global Transaction Services achieved 65% lead acceptance and 42% lift versus control. Internal Audit surfaced risks earlier and improved risk-type accuracy. Both became proof points that accelerated enterprise-wide scaling of the AI-driven operating model.
The corporate banking division needed to grow its open account trade portfolio, but traditional lead identification and relationship manager-led coverage had hit their limits. High-potential companies existed in the market but were invisible to the team because there was no systematic way to find or prioritise them.
Built a network graph AI model that used transaction data and corporate network connectivity to identify and prioritise high-potential prospects across six Asian markets. Rather than just generating a lead list, the model surfaced contextual insights that gave relationship managers a credible reason to engage each prospect. Integrated into the corporate banking cross-sell engine at scale.
SGD 6M incremental economic value in Year 1, scaling to SGD 10M in Year 2 across six markets. Model integrated into production and extended to additional use cases.
The FX business needed to grow revenue while improving customer satisfaction, in a highly competitive, margin-compressed environment.
Integrated AI-driven insights into sales, relationship manager, and back-end operations workflows and customer journey digital touchpoints. Re-organised the operating model into horizontal workstreams to break through silos and accelerate product and service time to market. Led delivery of cross-sell, attrition, and pricing propensity models.
15% FX revenue growth and 4.47/5 customer satisfaction score. This demonstrated that AI-driven personalisation can simultaneously improve commercial and customer outcomes.
With hundreds of AI/ML models in development, the organisation lacked a standardised approach to model delivery, risk management, and regulatory compliance.
Co-developed the 3A Methodology (Ask, Analyse, Act), a standardised approach to developing and deploying AI capability across the enterprise. Led the AutoML initiative to industrialise model delivery. Built model inventory and explainability utilities aligned to MAS FEAT principles.
AI/ML model delivery time reduced from 4 months to 2 weeks. The 3A methodology became the backbone of the enterprise AI protocol, supporting 800+ models in production.
The broader DBS AI-Driven Transformation initiative, which these workstreams contributed to, was attributed SGD 370M (US$274M) in incremental economic value by 2023, reduced model deployment time from 12–15 months to 2–3 months, and established operating frameworks enabling bank-wide AI/ML scale. Documented in Harvard Business School case study on DBS' AI transformation journey.
About
Founder & Principal Consultant, Wizcale
I am a statistician from the Philippines with 20 years in financial services, spanning credit risk, model governance, and enterprise AI transformation.
My career gave me a rare end-to-end perspective: from using models to drive business decisions, to auditing them for regulators, to leading the cross-functional programmes that put AI at the centre of how a bank operates.
I founded Wizcale in 2024 to bring that same hands-on approach to financial institutions earlier in their AI transformation, advising on strategy, governance, and delivery. My work at DBS is documented in a Harvard Business School case study.
Since founding Wizcale, I have been providing hands-on advisory on AI strategy, governance, and AI/ML delivery, primarily to SME founders across Singapore, Philippines, and Taiwan. Alongside this, I design and prototype AI-enabled workflows and agentic systems to validate use cases and stay current with implementation realities, not just strategy.
Engaged as subject matter expert by leading global consulting firms advising BFSI clients on AI transformation, governance, and strategy.
Speaker, Women in AI (for Good), on practical AI adoption.
Postgraduate Diploma in Digital Business | Emeritus (MIT Sloan & Columbia Business School)
Bachelor of Science in Statistics (Honours) | University of the Philippines – Diliman
Applied GenAI for Digital Transformation | MIT Professional Education
Make.com Certified (Intermediate)
Who I Work With
How We Work Together
Every engagement is structured around your needs, not a fixed retainer or a bloated project scope.
Hands-on. Tightly scoped. Built to hand over.
I come in with clearly defined scope, drive the hard flagship projects, build the structures, codify everything for your team, and stay until initial value is realised and your BAU team is ready to own it. Nothing leaves with me.
Typical engagement: 6–12 months. Often begins as a Project Advisory.
One outcome. Properly delivered.
A governance framework. A maturity and readiness assessment. A use case roadmap. A proof of concept. Defined scope, defined timeline, clear output.
Typical engagement: 6–12 weeks.
Senior AI presence when you need it most.
Board-level AI leadership during a transition, a CDAO search, or a critical window requiring credible senior oversight. Near full-time availability, strategic direction, and stakeholder alignment, without the permanent hire.
Typical engagement: 3–6 months.
Get in Touch
I work with a small number of clients at a time. If your institution has invested in AI but adoption isn't moving at the pace your board expects, and you want a practitioner who has done this before, not just advised on it, I would like to hear from you.
Schedule a Consultation