How will AI Affect the Banking System and Financial Markets?

Riaan Srivastava, Whitney M Young, Sophomore, Fall 2025

AI is increasingly integrated into our day-to-day lives and will have a huge impact on the financial world and the banking system. Putting this in perspective, author Midhat Tilawat states, "By 2025, AI is expected to [have saved] banks $200 to $340 billion and influence $450 billion in revenue, with generative AI investments reaching $1.68 billion" (Tilawat, 2025). This isn't the only positive for banks, though. An Accenture cloud rotation analysis has estimated that "fast-tracked gen AI implementation is already delivering an average 29% increase in pre-tax profit" (Brunier, 2025). This statistic truly shows how much AI has already improved since its implementation in some banking systems.

Industry experts also have something to say. Manish Kumar, an expert in Analytics, explained that "with AI, there would be much better fraud detection, vastly improved services and newer products at cheaper prices, but the security risks are also going to multiply significantly, so I see a completely new future of banking." His perspective underlines both the opportunities and the risks that banks need to balance while adopting AI.

Nick Smith, a day trader with over 20 years of experience, echoed this view by underlining the use of human judgment coupled with technology.“AI predicting models will be very commonly used in stock markets in the future, but with everyone having access to it, human intellect and instinct will need to be combined with AI to be able to be successful in the future.” His insight reveals that although AI could boost predictive power in a way, it can never replace human decision-making.

Though AI is showing many promising results, there are also downsides. Without a proper framework and governance, AI has the ability to become risky and unstable. It is wise to carefully use AI, as improper use could also lead to massive losses that could cripple many systems. With more companies moving toward AI tools, these technologies are playing a growing role in financial operations. For example, AI can improve efficiency in fraud detection, automate customer service interactions, evaluate credit risk, and personalize financial services and products. However, with increased reliance on algorithms alone comes concerns about bias, weaknesses in security, and regulatory challenges. Understanding both the potential and the pitfalls of AI is very important as the financial world continues to evolve.