AI in finance: A guide for Singapore finance teams (2026)

Key Takeaways:

• AI in finance has moved from drafting summaries to executing entire workflows: cutting close time, preventing fraud, and improving payment success rates.

• Singapore is one of Asia's leading markets for AI adoption in finance, supported by a clear regulatory framework. In 2026, MAS released an AI Risk Management Toolkit to help businesses deploy AI responsibly.

• Airwallex's Expense Policy Agent automatically reviews every expense your team submits, enforces your policy across entities, currencies, and languages, and flags violations with the exact rule that applies.

AI in finance is reshaping how Singapore businesses manage everything from expense approvals to cross-border supplier payments, and the shift is happening faster than most finance teams realise.

This guide breaks down what AI in finance actually means for your team, from the key concepts to understand, to the four core functions where it delivers the strongest returns in Singapore, and what it takes to build the right foundation for adoption.

We'll also show how Airwallex's AI agents can automate tasks such as expense reviews, bill verification, and policy enforcement across your financial operations.

What is AI in finance?

AI in finance refers to using artificial intelligence to automate and improve financial processes — from matching invoices to purchase orders, to routing payments through the fastest corridor, to reviewing every expense against your company policy.

Finance is a natural fit for AI. Most of the work is high-volume, repetitive, and rule-based, with clear outcomes that are easy to measure. Data is structured, processes are documented, and success is defined. That's the environment where AI performs best.

There's a good chance your finance team already encounters AI without calling it that. Some examples include:

• Rules-based automations that match invoices to purchase orders

• Risk scores that flag suspicious transactions

• Accounting software that categorises expenses based on how your team has categorised similar ones before

What's changed is the scope. The AI running in finance today doesn't just follow preset rules: it learns from every transaction, adapts to new patterns, and increasingly acts on its own. That shift, from AI that assists to AI that executes, is what this guide is about.

Key concepts in AI in finance

A few terms come up whenever AI and finance intersect. Understanding them helps you evaluate tools and ask the right questions.

Machine learning

Machine learning is how AI learns. It analyses patterns in historical data to make decisions: recognising fraud indicators, or identifying which payment routes succeed most often for a given corridor.

AI agents

Agents are AI systems that plan and execute tasks within defined boundaries. They assess situations and complete workflows, from receiving an invoice through to executing payment.

Agentic AI

Agentic AI is the autonomous capability that separates AI that recommends from AI that acts. To learn more, read our guide on what is agentic AI.

Conversational finance UX

This means interacting with your finance system through plain language. Ask, "What's our SGD cash position this week?" and AI gathers the data and answers for you.

Unified infrastructure

Your business accounts, payment systems, cards, and finance software on one platform with shared data. This lets AI see your entire finance operation rather than isolated snapshots from disconnected tools.

APIs

APIs (Application Programming Interfaces) are what let agents act, not just analyse. Without them, an agent can review an invoice but can't approve or pay it.

These six concepts connect: agents use machine learning to decide, APIs to act, and unified infrastructure to see the full picture. Remove any one piece, and AI drops from autonomous to merely assistive.

Why AI matters for Singapore finance teams

Finance operations don't scale the way the rest of your business does. Revenue can grow quickly, but finance teams generally grow in step with transaction volume. Every new market, currency, and entity adds manual work.

For Singapore businesses operating across ASEAN, this is a real operational problem. Running entities in Malaysia, Indonesia, and Thailand alongside Singapore means managing:

• Different payment rails for each market (FAST, DuitNow, PromptPay)

• Different tax treatments on the same categories of spend

• Multiple currencies hitting the same ledger

• Separate accounting requirements across jurisdictions

AI handles much of this work automatically, and unlike a new hire, it doesn't slow down as volume grows.

Singapore's position makes it a practical place to start. The country is ranked third among 15 global AI financial hubs¹, and MAS has published clear guidance for businesses adopting AI responsibly.

It has since released an AI Risk Management Toolkit covering traditional, generative, and agentic AI, developed with leading financial institutions. This gives you a ready reference point for deploying AI with the right controls.

Want to use AI in your finance operations? Explore Airwallex Spend or sign up for an account to access our Expense Policy Agent.

Key AI applications for Singapore finance teams

AI is already delivering measurable results across four core finance functions. Here are a few examples:

Payment optimisation

One of the clearest improvements is in how payments are routed and recovered.

When a payment fails today, most systems either retry on the same route or push the issue to a manual queue. AI takes a more adaptive approach. It learns from live issuer response patterns across your transaction history and adjusts routing decisions in real time.

For Singapore businesses, this matters across both domestic and regional payments — from FAST and PayNow transfers at home, to SWIFT and local rails in Malaysia, Indonesia, and Thailand. The result is fewer failed transactions, fewer manual follow-ups, and less time spent resolving payment exceptions.

Airwallex’s Optimize 360 is built around this idea. It applies real-time intelligence across these key areas:

• Network acceptance: optimising routing based on issuer behaviour, geography, and cost

• Payment recovery: using smart retries triggered by decline codes and issuer feedback

Fraud detection and financial crime compliance

AI also plays a major role in identifying fraud that rule-based systems often miss.

Instead of looking at transactions one by one, AI systems analyse patterns across full transaction histories. This makes it easier to detect subtle anomalies such as duplicate invoices with small variations, unusual vendor payment sequences, or account takeovers that mimic normal behaviour.

The impact is already well documented. Mastercard’s Decision Intelligence Pro improved fraud detection rates by around 20%³ on average, while Visa’s Scam Disruption initiative prevented more than US$350 million⁴ in attempted fraud in 2024.

Airwallex’s fraud engine operates across three layers:

• Behavioural and device signals, assessed in real time on every transaction

• Adaptive rules that evolve as fraud patterns change

• Smart 3DS flows that are only triggered when necessary, reducing friction for legitimate users

Expense management and reconciliation

Beyond payments and fraud, AI is also reshaping day-to-day finance operations like expense tracking and reconciliation.

It can capture receipts, categorise expenses according to company policy, and reconcile transactions with accounting systems continuously, not just at month-end.

This is especially useful for Singapore finance teams dealing with local regulatory complexity.

Goods and Services Tax (GST) input tax credits, for example, require accurate expense categorisation at 9%. CPF rules add another layer of complexity, since certain allowances are CPF-liable while others are not.

AI that understands policy in plain English helps reduce the manual burden across multi-entity ASEAN operations. For more on how this works in practice, see Airwallex's Expense Policy Agent and The End of Month-End.

Accounts payable automation

AI also streamlines the accounts payable process end-to-end.

It can extract invoice data using OCR and natural language processing, match invoices against purchase orders and delivery receipts, route exceptions to the right approver, and schedule payments automatically.

In Singapore, InvoiceNow — the national e-invoicing network managed by IMDA — makes this even more powerful by providing structured invoice data that AI can process directly, without manual extraction.

For businesses paying suppliers across ASEAN in currencies like Malaysian ringgit, Indonesian rupiah, or Thai baht, AI can also help optimise payment timing to reduce FX exposure. Reconciliation happens continuously in the background rather than being left to period-end close.

For a closer look at how this works end-to-end, see our guide to accounts payable automation.

The future of AI in finance in Singapore

The AI tools available today mostly handle discrete tasks — one agent processes an invoice, another flags a suspicious transaction. What's coming next is these agents working together, with less human hand-holding between steps.

Coordinated agents working together

Today, most AI in finance operates in silos. An expense tool has its own AI. Your payment platform has another. They don't talk.

The next shift is agents that hand off to each other across an entire workflow:

• An invoice arrives, and one agent captures and validates the data.

• A second checks it against your budget and GST rules.

• A third schedules payment — via FAST if the supplier is local, or via the most cost-effective corridor if they're in Malaysia or Indonesia.

• A fourth updates your cash forecast automatically.

None of this requires manual handoffs. But it only works if those agents share the same underlying data — which means fragmented tools running on separate systems break the chain.

AI as a strategic partner for ASEAN expansion

Right now, AI mostly answers questions you already know to ask. The direction it's heading is proactive — surfacing things you didn't think to look for.

For a Singapore CFO managing ASEAN operations, that shift starts to look very practical.

Instead of waiting for reports, you might receive timely prompts such as a warning when your IDR cash position moves outside its target range, a flag when spending in your Kuala Lumpur office changes unexpectedly, or a reminder to review FX exposure before a large MYR payment is processed.

As more of your financial operations are connected through a single platform, the value of AI increases as well. With a more complete view of cash flow, payments, and expenses across entities, it becomes better at spotting patterns and surfacing what matters.

Read more about where this is heading: Towards Autonomy: The Next Era of Finance.

Why Singapore businesses choose Airwallex for agentic finance

If you're ready to put AI to work in your finance team, the easiest place to start is Airwallex.

Our AI agents are pre-built for the tasks that take up most of your team's time — expense policy enforcement, invoice verification, and payment routing. Just upload your expense policy, connect your team, and the Expense Policy Agent starts working immediately.

You can sign up for an account fully online; there’s no branch visit required. Airwallex is licensed as a Major Payment Institution and regulated by MAS.

Frequently asked questions (FAQs)

What is AI in finance?

AI in finance means using artificial intelligence to automate finance functions — processing invoices, detecting fraud, routing payments, and reconciling accounts. It covers machine learning, AI agents, and generative AI, each suited to different tasks.

How is AI used in finance in Singapore?

Singapore businesses are using AI across expense management, accounts payable, fraud detection, and cross-border payments. Large banks like DBS have deployed it at scale; for mid-market businesses, AI is increasingly available through finance platforms that embed agents directly into everyday workflows.

What is the difference between analytical AI, generative AI, and agentic AI?

Analytical AI spots patterns, such as flagging a suspicious transaction. Generative AI produces content, like drafting a report. Agentic AI takes action: it completes a task end-to-end, such as processing an invoice from receipt through to payment.

Does AI replace finance teams?

No. AI handles repetitive, high-volume tasks so your team can focus on work that requires judgement — supplier relationships, financial planning, and strategic decisions. The role shifts, but it doesn't disappear.

How can my business in Singapore get started with AI in finance?

Pick one high-volume, repetitive process first — expense management or accounts payable are common starting points. Airwallex's Expense Policy Agent requires no integration project: upload your policy, connect your team, and it starts reviewing submissions immediately.

Sources:

1. reuters.com/business/world-at-work/singapore-urges-financial-firms-use-ai-create-better-jobs-2026-05-20/

2. https://www.mas.gov.sg/schemes-and-initiatives/project-mindforge

3. mastercard.com/us/en/business/cybersecurity-fraud-prevention/risk-decisioning.html

4. usa.visa.com/about-visa/newsroom/press-releases.releaseId.21286.html

This publication does not constitute legal, tax, or professional advice from Airwallex, nor does it substitute seeking such advice, and makes no express or implied representations / warranties / guarantees regarding content accuracy, completeness, or currency. If you would like to request an update, feel free to contact us at [[email protected]]. Airwallex (Singapore) Pte. Ltd. (201626561Z) is licensed as a Major Payment Institution and regulated by the Monetary Authority of Singapore.