AI in finance: A guide for Malaysian 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.

• Malaysia is one of ASEAN's most AI-forward financial markets. Bank Negara Malaysia (BNM) released a Discussion Paper on AI in the financial sector in 2025 to guide responsible adoption across the industry.

• 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 Malaysian 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 Malaysia, 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. BNM's 2025 Discussion Paper specifically flags agentic AI as an emerging area — describing it as AI systems capable of taking autonomous actions to achieve a goal, such as automatically freezing a suspicious transaction upon detecting fraud risk.

Conversational finance UX

This means interacting with your finance system through plain language. Ask, "What's our ringgit 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 Malaysian 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 Malaysian businesses operating across ASEAN, this is a real operational problem. Running entities in Indonesia, Thailand, and Vietnam alongside Malaysia means managing:

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

• Different tax treatments on the same categories of spend

• Multiple currencies and a ringgit base that creates FX exposure on every overseas payment

• MyInvois e-invoicing compliance in Malaysia alongside separate accounting requirements in each ASEAN jurisdiction

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

Malaysia's position makes it a practical place to start. BNM released a Discussion Paper on Artificial Intelligence in the Malaysian Financial Sector in August 2025 — the country's first formal regulatory engagement with AI in finance.

The paper outlines seven responsible AI principles and confirms that existing regulatory frameworks are broadly adequate for current AI applications. This gives businesses a stable foundation for adoption.

The National AI Office (NAIO), launched in December 2024, is coordinating Malaysia's shift from voluntary guidance to practical implementation under the AI Nation 2030 vision and the 13th Malaysia Plan (2026–2030).

Major Malaysian financial institutions are already moving. Maybank has committed RM10 billion to technology, data, and AI under its ROAR30 strategy (2026–2030). Affin Bank and RHB are deploying AI across customer analytics, fraud detection, and operational automation. For mid-market finance teams, the tools are now catching up.

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

Key AI applications for Malaysian 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 Malaysian businesses, this matters across both domestic and regional payments — from FPX and DuitNow transfers at home, to international transfers in Indonesia, Thailand, and Singapore. 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 an average of 20%¹, while Visa's Scam Disruption initiative prevented more than US$350 million² in attempted fraud in 2024.

Malaysia's own compliance landscape adds another layer. The Anti-Money Laundering, Anti-Terrorism Financing and Proceeds of Unlawful Activities Act (AMLA) imposes strict customer due diligence and sanctions monitoring requirements.

AI-powered systems that adapt to evolving financial crime patterns help businesses stay compliant without expanding their compliance teams in step with transaction volume.

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 Malaysian finance teams dealing with local regulatory complexity. Sales and Service Tax (SST) requires accurate expense categorisation: service tax runs at 6% or 8% depending on the category, with the scope expanded further on 1 July 2025.

Client entertainment is an additional complication: only 50% of those costs are deductible under Malaysian tax law, so miscategorised claims need to be caught at submission, not at audit.

MyInvois e-invoicing adds another layer, since LHDN requires records to be retained for seven years and vendors above certain turnover thresholds must now issue structured e-invoices rather than paper receipts — and LHDN audits mean those records need to be readily accessible, not buried in spreadsheets.

Accounts payable automation

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

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

In Malaysia, MyInvois makes this even more powerful by providing structured invoice data that AI can process directly, without manual extraction.

Businesses can validate the Unique Identifier Number (UIN) on each incoming e-invoice and route it to the right approver automatically, without re-entering data. Invoices containing errors must be rejected within LHDN's specified window. Miss it, and any correction has to go through a credit note or debit note process.

There is also a step that catches many businesses off guard: when paying an overseas supplier, Malaysian businesses may need to issue a self-billed e-invoice on the supplier's behalf and submit it through MyInvois — a compliance requirement that most global AP tools don't handle natively.

For businesses paying suppliers across ASEAN in currencies like CNY for goods from China, USD for SaaS platforms, or SGD for regional services, AI can also help optimise payment timing to reduce FX exposure.

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

The future of AI in finance in Malaysia

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 SST rules.

• A third schedules payment — via FPX if the supplier is local, or via the most cost-effective corridor for foreign suppliers.

• 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 Malaysian 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 Indonesian rupiah cash position moves outside its target range, a flag when spending in your Bangkok office changes unexpectedly, or a reminder to review FX exposure before a large SGD payment is processed.

Malaysia's 13th Malaysia Plan (2026–2030) and the AI Nation 2030 vision set the national direction. NAIO is translating that into sector-specific frameworks for financial services. 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.

Why Malaysian 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.

In early access testing across 150,000 expense evaluations, expenses verified by the Expense Policy Agent matched human approvers' decisions 99.4% of the time.

You can sign up for an account fully online; there's no branch visit required. Airwallex (Malaysia) Sdn Bhd is regulated by Bank Negara Malaysia as a licensed remittance business under the Money Services Business Act 2011 (Licence number 00743).

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 Malaysia?

Malaysian businesses are using AI across expense management, accounts payable, fraud detection, and cross-border payments. BNM's AI Survey 2024 found that the majority of banking institutions had already implemented at least one AI application — adoption has moved well beyond the pilot phase. 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 does AI help with MyInvois and LHDN compliance in Malaysia?

AI can validate incoming e-invoices against MyInvois Unique Identifier Numbers (UINs), route them for approval before LHDN's rejection window closes, and automatically generate self-billed e-invoices for overseas supplier payments. It also maintains a searchable audit trail — with receipts, approval timestamps, and correct SST categorisation — so your records are ready if LHDN audits your business. Retention for seven years is required, and manual processes make that difficult to maintain consistently.

How can my business in Malaysia 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. mastercard.com/us/en/business/cybersecurity-fraud-prevention/risk-decisioning.html

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

This publication does not constitute legal, tax, or professional advice from Airwallex nor 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 (Malaysia) Sdn. Bhd., a company incorporated under the laws of Malaysia with company registration number 201801007747 (1269761-X), is regulated as a licensed remittance business under the Money Services Business Act 2011 (Licence number 00743 with an expiry date of 3 August 2028, an E-Money Issuer and a registered merchant acquirer under the Financial Services Act 2013.)