As of 2024, AI in the finance market stood at $38.36 billion — and it's expected to reach $190.33 billion by 2030.
According to the Organization for Economic Co-operation and Development, the use of AI, including machine learning and generative AI for finance is growing rapidly, offering opportunities to boost efficiency and create value. However, its use in financial markets can increase risks and create new challenges for the global economic system.

Discover the benefits and downsides that AI brings to the world of finance.
AI for Finance: Overview
Recent advances in AI, especially generative AI, are transforming finance by improving accuracy and efficiency in areas like fraud detection, credit decisions, risk management, and portfolio management.
The OECD emphasizes that AI understanding and literacy across all organizational roles — not just experts — are essential for effective governance and responsible use.
The following graph shows a survey of various financial organizations and how they use AI:
source: OECD report, AI in Finance
The graph highlights that AI adoption in finance is primarily driven by customer-focused priorities, with the top use cases being customer relations, process automation, and fraud detection.
This suggests that institutions are leveraging AI not just for operational efficiency, but to meet growing expectations for personalized, secure, and responsive financial services.
Quiz
What is the main reason financial companies are heavily investing in AI?
The Pros of Using AI for Finance
Security: AI spots suspicious behavior and can stop fraud before it happens.
Speed and accuracy: It makes decisions in seconds that would take humans hours or days and can handle data without human error.
Personalization: AI gives financial advice, offers, and products that actually fit people’s lives.
Risk and prediction: AI looks at past trends and market data to help predict risks and potential investments.
Trading: AI can buy or sell at just the right time using smart algorithms.
Flexibility: AI tools can work from anywhere and adjust to different needs or systems.
How AI for Finance is Used
This TikTok describes 6 ways that AI is a "game changer" in finance in the following ways:
Fraud detection in real time.
Hyper-personalisation. AI tailored to the individual anlalyzing how you spend, save and invest.
Smarter credit scoring using not just credit but behaviour and habits.
Algorithmic trading where AI reacts to the markets in milliseconds.
Predictive analytics to inform what will happen next.
Coversational AI to support customers 24/7.
The Cons of Using AI for Finance
Interestingly, some of the advantages, if used differently or taken too far, can be disadvantages.
Trust: People prefer talking to real humans over robots.
Security and fraud: AI systems can be hacked or tricked.
Bias: Since AI learns from human-made data, it can make unfair or biased decisions.
Cost: Building and running AI is expensive.
Strategy: AI is great with numbers but can’t think big or plan like a human can.
Rules and regulations: There aren't clear rules yet for how AI for finance should be used, which could cause legal problems in the future.
Case Study: Consider the Balance
Choosing the best way to use AI for finance involves finding the right balance between automation and human judgment. Effective human-AI collaboration combines AI’s ability to analyze data and generate insights with human expertise to deliver personalized, high-quality financial services.
Look at these four individuals working in the financial field and decide who is using AI for finance in the best way.
Jason
Uses AI for all trading and customer reports.
Relies on AI to fix mistakes.
In favor of full automation.
Aisha
Uses AI to find investments.
Avoids AI for customer use due to fear of risk and privacy issues.
Manually checks everything.
Maria
Uses AI for fraud detection, fast data processing, and personalized offers.
Reviews AI results and keeps humans involved in final decisions.
Understands AI risks, follows rules, and combines them with expert human decision-making.
Tyler
Uses AI mostly to save money and cut staff.
Depends on AI for both advice and customer service.
Relies on little human support and interaction.
Quiz
Who is using AI in the best way?
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