What is agentic finance? Malaysia guide (2026)

Key Takeaways:

• Agentic finance is the operating model where AI agents handle defined finance tasks — from expense review to bill verification — continuously and autonomously.

• Malaysia is one of the most active markets for agentic AI adoption in ASEAN, with Bank Negara Malaysia (BNM) publishing an AI governance discussion paper at MyFintech Week 2025 and leading enterprises already deploying agents across finance workflows.

• Airwallex's Expense Policy Agent does the heavy lifting for you: it reviews every expense the moment it's submitted, flags policy breaches with a direct citation of the rule that applies, and auto-approves compliant spend.

Agentic finance is rapidly becoming the defining term in modern business finance, but for most Malaysian finance teams, it still raises more questions than answers.

You may have encountered it at MyFintech Week, in industry reports, or during software demonstrations. But what does agentic finance actually mean, and how does it affect day-to-day finance operations?

This article explores what agentic finance means, how it works, and what it looks like inside a modern Malaysian finance function. 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 agentic finance?

Agentic finance is the operating model where AI agents execute finance tasks across your systems, each owning a specific job and acting with a measured degree of autonomy.

Instead of a human opening a dashboard to approve an expense, an agent reads the policy, evaluates the claim, and either clears it or flags it with a cited reason.

The human role shifts from processing transactions to setting policy, reviewing exceptions, and making strategic calls. The agents handle the routine work. Humans handle the judgement.

This shift is accelerating quickly. A Deloitte poll of finance and accounting professionals found that 80.5% expect AI agents to become standard tools in the profession within five years.¹

In Malaysia specifically, 86% of business leaders say they are confident they will use AI agents as digital team members to expand their workforce capacity in the next 12 to 18 months.²

What agentic finance is not

Three things are commonly confused with agentic finance: rules-based automation, gen AI copilots, and crypto "agentic finance".

Rules-based automation — like traditional expense software — follows fixed instructions. It can approve expenses under RM200 if a receipt is attached. It cannot interpret nuance, handle edge cases, or adapt when your policy changes. Agentic AI does all three.

Generative AI copilots are the AI chat assistants built into finance tools that summarise data and answer your questions. They are reactive: they respond when you ask. AI agents are proactive: they act without being prompted.

DeFi and crypto "agentic finance" is a separate concept that often appears in the same search results as this article. It refers to AI agents making autonomous transactions on blockchain networks. That is not what this guide covers.

How agentic finance works in practice

Most finance teams aren't starting from scratch. You already have some form of automation in place. Understanding where you sit in the progression helps you see how to get to the next step.

Stage 1: Automation (where most Malaysian finance teams are today)

Software has made it possible to automate repeatable, rule-based tasks:

• Invoices get matched to purchase orders.

• Approvals follow preset workflows.

• Payments are scheduled in advance.

The problem with this is that automation is rigid, with each workflow running in isolation.

Change a supplier's payment terms and someone has to update the rules manually. Open a new entity in Singapore and the whole configuration needs to be rebuilt for that market. Add a new expense category and someone has to update the code to define what "compliant" means in the system.

Stage 2: Agents that understand context

The next stage is where AI agents move beyond rigid rules and start applying judgement.

Traditional automation relies on predefined rules. For example, you might configure a system to flag any meal expense above RM80. An AI agent works differently. It can read your expense policy written in plain English and understand:

• What the RM80 limit means in context

• When exceptions should apply

• How rules differ across teams, offices, or countries

When an expense is submitted, the agent reviews it in context. It decides whether it complies with policy, flags anything unusual, explains its reasoning, and points to the exact policy section it is using.

The same applies to invoice verification. Instead of simply matching fields between documents, an agent reads the invoice alongside the purchase order, identifies discrepancies such as pricing errors, and flags them before payment is approved.

For finance teams operating across ASEAN, this becomes especially powerful. A single agent can apply a global expense policy while still accounting for local nuances — from Malaysian RM meal allowance caps to Singapore per-diems and Indonesian reimbursement workflows — without needing separate setups for each market.

Stage 3: Autonomous finance operations

At the most advanced stage, multiple agents run in the background simultaneously: each handling a specific part of your finance operations, within the limits you set.

Here are some examples of what that might look like:

• A payment routing agent selects the fastest and most cost-effective path for each transaction

• An FX conversion agent triggers currency conversions automatically at payout, based on thresholds you define

• A compliance agent runs checks at the point of onboarding rather than waiting for a batch review weeks later

Malaysian banks are already piloting this. In March 2026, Mastercard completed its first live agentic transaction in Malaysia with CIMB and RHB — an AI agent booking transportation autonomously using tokenised credentials. 

Visa followed in April 2026 with its Agentic Ready programme, enrolling Alliance Bank, CIMB, and Maybank in a controlled environment to test how AI agents initiate payments on behalf of consumers. The infrastructure for agentic finance is being built in Malaysia now.

What agentic finance actually looks like

If you want to see agentic finance in action, Airwallex Spend is one of the most practical starting points available today. It comes with AI agents built directly into the expense management workflow, and these AI agents help you do the heavy lifting.

Our Expense Policy Agent, for example, reviews every card expense and reimbursement your team submits against your actual policy — written in plain English, no special formatting required.

Learn more about Airwallex Spend or sign up to start using our AI agents.

Why the infrastructure layer matters

Agents are only as capable as the data they can see.

An expense agent that cannot access accurate exchange rate data does not know whether a hotel invoice in US dollars actually breaches your RM policy limit. A payment routing agent that cannot see your cash position across entities cannot optimise for both cost and liquidity at the same time.

This is why agentic finance works best when the financial infrastructure — accounts, FX, payments, cards — runs on the same platform as the agents, like in the case with Airwallex.

Agents with complete, connected data act with confidence. Agents working across fragmented systems are operating with an incomplete picture.

Why Malaysian businesses choose Airwallex for agentic finance

If you want to get started with agentic finance without building anything from scratch, Airwallex is the most direct path.

Our AI agents are pre-built for common finance team use cases such as expense policy enforcement, invoice verification, and more. They sit inside a platform that already handles your accounts, cards, payments, and FX.

Simply upload your expense policy, connect your team, and the Expense Policy Agent starts working immediately — reviewing submissions, clearing compliant expenses, and flagging exceptions with a plain-language explanation.

Airwallex is licensed in Malaysia as a MSB Class B (remittance business only) licensee and is regulated by Bank Negara Malaysia (BNM).

Frequently asked questions (FAQs)

Is agentic finance the same as DeFi?

No. Decentralised finance (DeFi) uses AI agents to make transactions on blockchain networks — it is a crypto-native concept. Agentic finance, as used in this article, refers to AI agents handling business finance operations such as expense management, invoice verification, and payment processing inside your company's existing systems.

How is agentic finance different from automation?

Automation follows fixed rules. It breaks when conditions change and cannot apply context or judgement. Agentic finance uses AI agents that read your policies in plain English, evaluate each transaction in context, and explain their reasoning, so your team can see exactly what the agent decided and why.

Do I need to replace my existing finance tools to use agentic finance?

Not necessarily. Some platforms, including Airwallex, offer pre-built AI agents that layer on top of your existing finance workflows. You can start with a specific use case, such as expense policy enforcement, without overhauling your entire stack.

How do I know if an AI agent's decisions can be trusted?

Look for full auditability. Every decision an agent makes should be traceable: you should be able to see what the agent evaluated, what rule it applied, and what conclusion it reached. If a vendor cannot show you a clear audit trail, the system is not ready for production use in finance.

Is agentic finance suitable for small businesses?

Yes, agentic finance is suitable for small businesses, especially those dealing with cross-border payments, multiple currencies, or growing manual finance workloads. It is less useful for very simple, single-entity operations.

What should I look for when evaluating an agentic finance platform?

Three things: whether your finance team can configure the agent's behaviour directly without developer support; whether every agent decision produces a clear audit trail; and whether the platform can handle your actual data, not just clean demo data.

Sources:

1. https://www.deloitte.com/us/en/about/press-room/trust-main-barrier-to-agentic-ai-adoption-in-finance-and-accounting.html

2. https://news.microsoft.com/en-my/2025/05/08/microsofts-2025-work-trend-index-malaysian-workforce-and-leadership-align-on-intelligent-agent-integration/

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.)