Benefits of AI in Banking

Artificial intelligence (AI) is rapidly gaining traction in the banking and finance sector, with generative AI (GenAI) emerging as a transformative force. Financial institutions are increasingly adopting AI technologies to automate processes, cut operational costs, and boost overall productivity, according to Sameer Gupta, North America Financial Services Organization Advanced Analytics Leader at EY.

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While traditional machine learning (ML) techniques are commonly used for fraud detection, loan approvals, and personalized marketing, banks are now advancing to incorporate more sophisticated technologies, including ML, natural language processing (NLP), and GenAI. Gupta notes that EY is observing a growing trend of banks using ML to enhance credit approvals, improve fraud detection, and refine marketing strategies, leading to greater efficiency and better decision-making.

A recent survey by Gartner’s Jasleen Kaur Sindhu reveals that 58% of banking CIOs have either deployed or plan to deploy AI initiatives in 2024, with this number expected to rise to 77% by 2025. “This indicates not only the growing importance of AI but also its fundamental role in shaping how banks operate and deliver value to their customers,” Sindhu said. “AI is becoming essential to the success of banking institutions.”

Here are five key benefits of AI applications in banking:

Customer Experience: AI technologies, particularly GenAI, are enhancing customer service by improving document processing and creating new content. For example, GenAI can summarize customer complaints from recorded conversations, providing valuable insights into customer service and operational efficiency. Banks are also using GenAI to equip front-line staff with tools that improve product knowledge and customer interaction. Chatbots, like Bank of America’s Erica, have become crucial in offering 24/7 customer support, handling over two billion interactions since 2018.
Fraud Detection and Regulatory Compliance: AI, including GenAI, is increasingly used for fraud detection and regulatory compliance. AI can analyze data in real-time to identify unusual patterns and emerging threats. However, the rise of GenAI also presents risks, such as the potential for criminals to use AI-generated content for fraudulent activities, potentially increasing U.S. fraud losses to $40 billion by 2027, as reported by Deloitte. Despite these challenges, AI improves the accuracy of fraud detection and speeds up compliance processes.
Internal Business Operations: GenAI is automating various internal processes in banks, from data extraction to incident resolution, enhancing productivity by allowing staff to focus on strategic tasks. Banks are prioritizing internal use cases and addressing questions about AI risk management, cost-effectiveness, and ROI as they scale their GenAI efforts.
Product Innovation: GenAI is driving innovation in banking by enabling new customer segments and business models. For instance, Erste Bank’s Financial Health Prototype offers financial advice and product comparisons, democratizing financial guidance that was previously accessible only to premium clients. AI-powered robo-advisors also provide affordable, scalable financial advice, improving customer acquisition and sales.
Lending: AI is enhancing the lending process through tools like Bankwell Bank’s Cascading AI’s Casca conversational assistant, which supports small business owners in navigating loan applications. This AI assistant has improved lead quality significantly, demonstrating the potential of AI to streamline lending and enhance transparency.

Despite the benefits, concerns about AI in banking persist, particularly regarding data privacy, bias, and ethics. AI can inadvertently extract personal information and raise privacy issues. Regulatory challenges and the potential for AI systems to perpetuate biases are also major concerns. As AI technology evolves, banks are investing in robust governance frameworks, continuous monitoring, and adherence to ethical standards to address these risks.

Looking ahead, AI is expected to revolutionize banking by delivering personalized services, enhancing customer interactions, and driving productivity. Deloitte forecasts that GenAI could boost productivity by up to 35% in the top 14 global investment banks, generating significant additional revenue per employee by 2026.