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.
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.
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.
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