President Joe Biden issued a new executive order on artificial intelligence on Monday, making it the first of a kind to require new safety assessments, equity and civil rights guidance, and research on AI's impact on the labor market. The order is divided into eight sections, which include creating new safety and security standards for AI, protecting consumer privacy, and many others.

The announcement comes as financial firms and banks have started to adopt AI-based systems to not only make day-to-day activities easier for staffers, but also make better informed, safer, and profitable loan and credit decisions. However, generative AI also faces some challenges in the financial space, mainly highlighting how to assess the risks and how the risks can be minimized.

How Is AI Helpful For Banks?

Fraud detection is one field where AI can be highly supportive as it scans large amounts of data and in very little time detects any unusual patterns. Anti-money laundering efforts will also be enhanced by deploying AI into regular banking functions. It can also be used to develop chatbots to provide an enhanced customer experience, especially when onboarding new customers or vendors.

Nevertheless, the emergence of sophisticated and cutting-edge tools presents a challenge, as they provide highly skilled fraudsters with subtle and elusive methods to commit fraud, siphoning funds from bank clients.

What Are The Banks Doing?

A KPMG study, cited by AmericanBanker, surveyed 56 U.S. financial services executives from institutions with over $1 billion in revenue. The findings showed that 76% of these executives view fraud detection as a primary use for AI. Additionally, over two-thirds believe that compliance and risk management will be among the top applications.

Around 66% of respondents say that generative AI will also likely be used to power more sophisticated consumer-facing chatbots.

Major banks like JPMorgan Chase (JPM  ), Wells Fargo (WFC  ), Bank of America (BAC  ), and Goldman Sachs (GS  ) have rolled out many AI-powered programs.

JPMorgan Chase has started using large language models to detect fraud, through pattern examination in emails for signs of compromise, among other uses. Goldman Sachs is using generative AI to assist software engineers in code development.

Chief Information Officer Marco Argenti at Goldman Sachs said that a superhuman developer could be 30% to 40% more productive than normal human efforts, while JPM is looking to generate $1.5 billion through an AI initiative by the 2023 end, as reported by American Banker.

A recent S&P Global Market Intelligence report indicates that only eight publicly traded banks mentioned using AI and/or machine learning during conference calls and company presentations in Q3 of 2023. Meanwhile, ChatGPT has been garnering attention since Q1 2022, with banks referencing it more frequently, even before its rise in popularity.

While cybersecurity, fraud detection, and virtual assistants were the common mentions of banks' usage of AI, banks like JPMorgan also highlighted the more than 300 AI use cases in production for its asset management division to develop trading strategies and hedge equity portfolios.

The report highlights that smaller banks also use AI like Live Oak Bancshares (LOB  ), FVCBankcorp (FVCB  ), First Horizon (FHN  ), and Discover Financial Services (DFS  ).

Another leading adopter of AI, Citigroup (C  ) recently announced that 40,000 coders of the company will be granted access to Generative AI to make staffers more efficient.