The Risks of AI in Finance: What Every Accountant Should Know

As artificial intelligence (AI) is increasingly used in finance, it's important for accountants and finance professionals to understand the risks involved. Using AI brings real benefits but also significant risks that must be managed. This guide takes an even-handed look at the risks of AI in finance — what they are, why they matter, and how to manage them. Note that this is a developing area, so always follow your organisation's policies, professional standards and relevant regulations, and stay aware of current guidance. For related material, see our guides on AI governance and risk management.

Why understanding AI risks matters

AI can offer real benefits in finance, but using it without understanding the risks can lead to serious problems. Because finance involves accuracy, confidentiality, significant decisions and accountability, the risks of using AI carelessly are significant — potentially affecting the quality of work, the security of data, and trust. Understanding the risks isn't a reason to avoid AI; it's what allows it to be used safely and responsibly. Accountants and finance professionals, given their responsibilities, need to be aware of these risks so they can use AI appropriately and manage the downsides. Being clear-eyed about the risks — alongside the potential benefits — is part of the balanced, professional approach to AI that the profession requires. Far from being purely negative, understanding the risks empowers professionals to use AI in ways that capture its benefits while protecting against harm. This is why awareness of AI risks is an important part of engaging with the technology responsibly.

The key risks

Several risks are particularly important when using AI in finance:

• Inaccurate outputs — AI can produce errors, including confidently-stated ones, so relying on unverified outputs is risky.
• Data security and confidentiality — putting sensitive financial or client data into AI tools can create serious security and confidentiality risks.
• Over-reliance — leaning on AI without applying judgement can lead to errors and skill erosion.
• Bias — AI can reflect biases in its data, leading to unfair or inappropriate outputs.
• Lack of transparency — it can be hard to understand how some AI produced an output, which matters where explanation is needed.
• Accountability gaps — the risk of responsibility being unclear, when it actually remains with people and organisations.
• Inappropriate use — using AI where it isn't suitable, or in ways that breach policies or regulations.

These risks are real and significant in a finance context, which is why managing them is essential.

Why these risks are significant in finance

These risks carry particular weight in finance because of what's at stake. Accuracy is fundamental in finance — errors can have real financial, compliance and trust consequences, so the risk of inaccurate AI outputs is serious. Confidentiality is a core professional obligation, making data security risks especially important. Accountability is central — finance professionals and organisations are responsible for their work, and this can't be offloaded to a tool. Decisions based on financial information can be significant, so the quality and appropriateness of AI-supported analysis matters. And the profession operates within regulation and standards that must be upheld. In short, the very things that make finance important — accuracy, confidentiality, accountability, the significance of decisions, and regulation — are exactly what AI risks can threaten if not managed. This is why finance professionals need to take AI risks seriously and manage them carefully, rather than using AI casually.

How to manage AI risks

The good news is that these risks can be managed with a sensible, professional approach. Always verify AI outputs, treating them as something to check rather than trust. Protect data, following policies and regulations on what can be put into AI tools. Avoid over-reliance, continuing to apply your own judgement and maintain your skills. Be alert to bias and the appropriateness of outputs. Retain accountability, never treating AI as a way to offload responsibility. Use AI only where appropriate, and in line with policies and standards. Follow governance and guidance from your organisation and professional body. And stay informed, since this is an evolving area. By managing the risks this way, finance professionals can use AI to capture its benefits while protecting against the harms — the balanced, responsible approach the profession requires. Always follow current policies, standards and regulations, as guidance in this area continues to develop.

Frequently asked questions

Why do AI risks matter in finance?

Because finance involves accuracy, confidentiality, significant decisions and accountability, so using AI carelessly can seriously affect work quality, data security and trust. Understanding risks allows AI to be used safely.

What are the key risks?

Inaccurate outputs, data security and confidentiality risks, over-reliance, bias, lack of transparency, accountability gaps, and inappropriate use.

Why are they significant in finance specifically?

Because accuracy, confidentiality, accountability, the significance of decisions, and regulation — the things central to finance — are exactly what AI risks can threaten if not managed.

How do I manage AI risks?

Verify outputs, protect data, avoid over-reliance, be alert to bias, retain accountability, use AI only where appropriate, follow governance and guidance, and stay informed.

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