Raffles Consulting Services
Prepare for MAS AI Pathfinder by testing financial-institution eligibility, PathFin.ai solution fit, controls, costs and adoption evidence.
MAS AI Pathfinder supports Singapore-based financial institutions adopting and deploying market-tested AI solutions listed on PathFin.ai. MAS states support of up to 50%, capped at S$200,000. Listing and funding do not replace the institution’s technology, data, model, outsourcing, conduct and operational-risk responsibilities.
Test MAS AI Pathfinder fit before selecting a vendor
Confirm the applicant is a Singapore-based financial institution and identify the relevant licence, business unit and regulated activity. Define the use case, users, customer effect and measurable operating problem. Then confirm that the proposed solution and provider appear on the current PathFin.ai route and that the planned deployment matches the listed market-tested use case.
The MAS grants page gives the current support level and cap. The FSTI 4.0 overview places AI Pathfinder within the wider financial-sector innovation scheme. Check the current application materials and award terms before commitment because the overview is not an approval for a specific institution or solution.
Build an adoption case, not a technology shopping list
Document the current process, failure modes, cost, volume, service level and risk. State what the AI will and will not decide. Define target measures, affected policies and the human roles required. Compare adoption, integration and change costs with the expected benefit. Label projections and avoid assuming the grant will make a weak use case economical.
Map data sources, permissions, quality, retention, cross-border flows and sensitive attributes. Record model or service dependencies, explainability needs, fallback operation and exit options. Where a third party provides the AI, assess subcontractors, incident notification, audit rights and evidence access. A market-tested label does not answer the institution’s deployment-specific questions.
Connect grant milestones to responsible AI evidence
Set acceptance tests for accuracy, harmful outcomes, bias where relevant, security, privacy, resilience and human intervention. Define who may approve launch, restrict use, suspend the service and accept a residual risk. Make milestones measurable without revealing protected customer or security information unnecessarily.
Separate grant deliverables from continuing supervisory obligations. Use the MAS AI risk-management readiness guide for the wider governance map and the human-override test for intervention evidence. Funding closeout should leave a control file that remains useful after reimbursement.
Turn the decision into a controlled file
Use a dated decision record that identifies the applicant, business need, current official source, chosen route, responsible owner, costs, milestones and evidence. Separate facts already verified from forecasts and assumptions. A catalogue listing, supplier statement, consultant recommendation or portal acknowledgement does not establish approval. The company remains responsible for its declarations and commercial decision.
Give each quotation, contract, invoice, payment and deliverable a stable reference. Preserve earlier versions and explain material changes instead of silently replacing them. Where the authority, tax adviser, auditor or another professional must decide a point, record the open question and obtain the required view. Do not convert uncertainty into a confident eligibility statement.
Review before commitment and again before closeout
Run four reviews: suitability, authority, implementation and closeout. At suitability, test the entity, activity and business outcome. Before commitment, freeze the proposed scope, vendor and financial assumptions. During implementation, compare actual work with approved terms. At closeout, reconcile deliverables, accepted results, invoices, full payment, operating evidence and obligations that continue.
Name the person who may approve each stage and the records that person must see. Procurement should not treat a draft application as permission to contract. A project team should not treat supplier completion as company acceptance. Finance should not treat a submitted claim as cash received. Clear status words prevent accidental commitments and weak reporting.
Handle exceptions without rewriting history
Maintain an exception log for changed facts, delayed milestones, supplier variations, cost movements, missing records and failed tests. State the effect on scope, eligibility, timing and expected value. If an authority decision or formal variation is required, use the published route before relying on the change. Silence and helpdesk receipt are not approval.
If a material defect appears, pause the affected acceptance, filing or claim item. Keep original evidence, assign corrective action and set a review date. Do not backdate records, move costs between categories or adjust a baseline after seeing the result. A candid exception with an owned resolution is more credible than a clean-looking file that cannot explain what happened.
Plan handovers before the original project team disperses. The handover should identify the current version, source locations, system access owner, next review date, open exceptions and any condition that continues after payment or filing. Restrict personal, financial and commercially sensitive records to authorised users, while giving each responsible owner enough information to perform the assigned control. Record the external event that should trigger an earlier review, such as a changed programme page, revised authority letter, supplier failure or material business change.
Verify the final outcome independently
Ask someone who did not prepare the final pack to compare the decision, current official source, approved terms, deliverables, payments and operating evidence. Recalculate totals and sample source records. The reviewer should be able to reproduce the conclusion without relying on the preparer’s memory. Record unresolved points with named owners and dates.
Use the Singapore business support decision guide for the wider decision and keep this article as the narrower operating guide. After submission, preserve the receipt and reconcile questions, adjustments and the final registered or paid outcome. Continue any reporting, retention, asset-use or other condition that survives closeout.
Practical review checklist
- Institution and use case confirmed
- PathFin.ai fit checked
- Full adoption cost modelled
- Data and vendor controls assessed
- Launch and fallback tests approved
MAS AI Pathfinder readiness is credible when a qualifying institution has a real use case, a current listed-solution fit, a full-cost adoption case and deployment controls that remain effective after the grant project closes.