AI infinance
Finance runs on documents, checks and judgement calls that have to stand up to an auditor. AI is useful here when it does the reading, matching and flagging, and a named person still signs off. It is dangerous when nobody can say why it decided what it did.
Where AI helps
What we can build for a finance business, each one from a service we already run.
Know-your-customer and onboarding
Reads identity documents and company filings, cross-checks them, and prepares the file. An analyst reviews the exceptions instead of every case.
Agentic AITransaction monitoring
Models trained on your own history rank alerts by how likely they are to matter, so investigators start with the cases that count.
Machine learningClient and adviser questions
Answers drawn from your product terms and policies, with a clear handover to a licensed person when a question becomes advice.
Smart chatbotsReconciliation and reporting
Matches statements, invoices and ledgers, and drafts the routine report. Your team owns the breaks and the final numbers.
AutomationWhat we are building
Products of our own for finance. The ones still in development are marked; ask and we will tell you where they are.
What good looks like in Singapore
Examples of AI applied well by others, from published public programmes. They show the kind of thinking we bring. They are not projects we delivered.
Sharing red flags across banks
Public example. COSMIC, a platform launched by MAS with six major banks in 2024, lets financial institutions share information on customers showing multiple money-laundering red flags.
Pattern. One institution sees a fragment; the pattern only shows when the fragments are joined, under strict safeguards.
For you. Signals from across your own systems joined up before a person reviews them.
Source: mas.gov.sg(opens in a new tab)A shared rulebook for responsible AI
Public example. Project MindForge, led by MAS with banks, insurers and asset managers, published a risk framework and toolkit for using AI in financial services.
Pattern. In a regulated industry, the controls around AI are designed before the AI is deployed.
For you. Accountability, monitoring and explainability built into the system from day one.
Source: mas.gov.sg(opens in a new tab)Testing AI before it meets customers
Public example. AI Verify, a governance testing framework that validates AI systems against internationally recognised principles.
Pattern. AI you cannot test is AI you cannot defend.
For you. Defined checks before an AI system touches customers.
Source: smartnation.gov.sg(opens in a new tab)Your version of this is smaller, and that is fine
None of the above needed a national budget to be the right idea. Tell us the process you would apply it to, and we will tell you whether AI is the right tool.