AI in Finance and Banking – May 31, 2024

This semi-monthly column highlights news, government reports, NGO/IGO papers, industry white papers, academic papers and speeches on the subject of AI’s fast paced impact on the banking and finance sectors. The chronological links provided are to the primary sources, and as available, indicate links to alternate free versions.


MSN, May 31, 2024. Mastercard’s AI system is helping banks keep fraudsters in check — and it could save millions of dollars

  • Mastercard, an international card-payment-services company, interacts with banks worldwide.
  • The company has used AI to try to identify when customers may be about to be defrauded.
  • This article is part of “CXO AI Playbook” — straight talk from business leaders on how they’re testing and using AI.

Business Insider, May 30, 2024. AI mania is just ‘typical bubble hype’ like the crypto craze, says top economist Paul Romer. The breathless buzz around artificial intelligence is similar to the rabid excitement that surrounded digital assets such as dogecoin and NFTs in recent years, a top economist warned. “There was this solid consensus only a couple years ago that cryptocurrencies were going to change everything, and then suddenly that consensus just goes away,” Paul Romer told Bloomberg TV this week. “Nobody even asks, ‘Gee, why were we so confident and then it blew up?'” he added. The Nobel Prize winner, former World Bank chief economist, and Boston College professor drew a parallel between the grand claims and rank speculation of that period and the ongoing AI craze. “Right now there’s way too much confidence about the future trajectory of AI,” Romer said. “When people project this forward I think they’re at risk of making a very serious mistake.” May 30, 2024. Swift and Global Banks Launch AI Pilots to Tackle Cross-Border Payments Fraud. Swift has today announced two AI-based experiments in collaboration with its member banks, to explore how the technology could assist in combatting cross-border payments fraud and save the industry billions in fraud-related costs. In the first pilot, Swift is enhancing its existing Payment Controls service – which helps financial institutions detect anomalies that could be indicative of fraud – by using an AI model that will create a more nuanced and accurate picture of potential fraud activity, using historical patterns of activity on the Swift network. Swift will work with Payment Controls customers to refine the enhancement, and the test will use the customers’ own live traffic data – giving the findings real world applicability. In a separate experiment, Swift has convened 10 leading financial institutions to test how it can use advanced AI technology to analyse anonymously-shared data from different sources, in a way that will strengthen the global financial ecosystem. AI’s capability for confidential data sharing could be a game-changer for the industry. The tests could lead to the wider use of information sharing in fraud detection, building on its success in assessing cybersecurity threats. The group, which includes leading banks from around the world including BNY Mellon, Deutsche Bank, DNB, HSBC, Intesa Sanpaolo and Standard Bank, will test the use of secure data collaboration and federated learning technologies. It will leverage a secure infrastructure that will enable financial institutions to exchange relevant information with strong privacy-preserving controls. Swift’s AI anomaly detection model will then be able to gather insights and identify potential fraud patterns from a much richer dataset. Fraud cost the financial industry USD 485 billion in 2023 alone1. AI has a strong role to play in reducing these costs and, at the same time, tackling the issue will significantly help the industry achieve the G20’s goal of increasing the speed of cross-border payments. Swift is uniquely placed to spearhead industry efforts against fraud due to its role as a trusted entity at the heart of the financial ecosystem, and because of the breadth and reach of the data that travels across its network.

American Banker, May 30, 2024. What’s on bankers’ wish lists for generative AI?

MSN, May 30, 2024. Banks could lose $40 billion from fraud with the help of AI, Deloitte predicts. As the banking sector continues to funnel resources into building up its artificial intelligence capabilities and offerings, scammers are leveraging the same technology to carry out fraud. U.S. banking losses from fraud could total $40 billion by 2027, up from $12.3 billion in 2023 — a massive sum enabled by widespread scams powered by generative AI, Deloitte said in its 2024 Financial Services Industry Predictions published Thursday. Generative AI uses data to create original content, like text, images, music, audio, and videos. Using the technology, bad actors can carry out mass fraud ranging from email and phone “phishing” scams, to using AI deepfake audios and videos to impersonate both clients and banks. The Deloitte Center for Financial Services estimated that generative AI email fraud losses alone could total approximately $11.5 billion in just four years in the case of “aggressive” adoption. One of the biggest risk factors is the potential for criminals to get their hands on advanced technologies for cheap, according to Deloitte, which found that sites on the so-called dark web are selling scamming software for as little as $20. This “democratization” of malicious software gives any bad actor the basic tools to carry out fraud, and is already making existing fraud-prevention tactics less effective, the report said. “The way in which gen AI has grown so rapidly over the last few years, and even tools that might have detected this three, four months ago, tend to be obsolete right now,” said Satish Lalchand, a principal in Deloitte’s transactions and business analytics unit. “So it’s a rapid catch up process that’s taking place.”

Reuters via MSN, May 30, 2024. AI’s use in finance may need new rules, ECB says. FRANKFURT (Reuters) – The use of artificial intelligence in finance is still in its infancy but it needs to be monitored and possibly regulated to prevent harm to consumers and ensure the proper functioning of markets, the European Central Bank said on Wednesday. The ECB saw a number of opportunities from the use of generative AI by banks and other financial institutions, such as superior processing of information, more efficient customer service and even a greater ability to spot cyberthreats. But it also warned about risks including herding behaviour, over-reliance on a limited numbers of providers and more sophisticated cyberattacks. “Therefore, the implementation of AI across the financial system needs to be closely monitored as the technology evolves,” the ECB said in an article published as part of its regular Financial Stability Review. “Additionally, regulatory initiatives may need to be considered if market failures become apparent that cannot be tackled by the current prudential framework.” The European Union has formulated the world’s first artificial intelligence rules, which will force general-purpose and high-risk AI systems to comply with specific transparency obligations and EU copyright laws. So far, however, the ECB said the adoption of such systems by European financial companies was “in the early stages”. “Market contacts indicate that euro area financial institutions may be slower to adopt generative AI, given the range of previously discussed risks (and) also considering potential reputational risks,” the ECB said.

Business Insider, May 24, 2024. JPMorgan is making a big bet on AI. Here’s how its private bankers are using it. JPMorgan is testing a generative AI “copilot” within its private bank, a move that is already saving advisors a couple of hours a day. The AI tool aims to make advisors faster, smarter, and eventually, be rid of all the tedious operational work, Karen Donnelly, who leads the digital tech team for JPMorgan’s US private bank, told Business Insider. It will save advisors time with manual tasks, like prepping for client meetings, tracking down nuggets of information during client calls in real-time, or putting together follow-up emails with the next steps for clients. More than that, it can suggest investment opportunities for advisors to flag to clients, like buying more of one stock in a client portfolio that’s performing well. If a client mentioned in an email they’re interested in healthcare, the AI could suggest inviting the client to an upcoming industry conference. Some advisors have told Donnelly it’s saving them a couple of hours a day, she told BI.

Banking on AI, The Business Journals, May 22, 2024. Will banking’s increasing turn toward AI level the playing field or widen the gap between big and small banks? Artificial intelligence technologies are increasingly integral to the world we live in, and banks need to deploy these technologies at scale to remain relevant. Success requires a holistic transformation spanning multiple layers of the organization.

Forbes, May 24, 2024. GenAI Empowers Retail Banking – Maximize Potential, Dodge Pitfalls!  Banking leaders are excited about the potential of generative artificial intelligence (GenAI) to reshape the customer experience and optimize operations. A McKinsey survey finds that GenAI could add between $200 billion and $340 billion in annual value, boosting revenues by 2.8% to 4.7%. Retail banking is the second most profitable sector in the banking industry, generating $54 billion in new value, closely following corporate banking which generates $56 billion. “Retail banks are transforming quickly to maintain competitiveness,” says Rajat Gupta, Chief Digital Officer at Xebia, a digital transformation and IT consulting services company. “Leaders and teams are developing GenAI strategies that are far-reaching in scope. Whereas 2023 was the year of the pilot, 2024 is the year of scaling new GenAI models across banking businesses.” “However, as highly regulated institutions, banks have special considerations,” Gupta continues. “They must design frameworks with governance and guardrails that protect consumer data privacy and security. No one wants to be the poster child for AI model breaches and GDPR fines.”


Bank of England, May 21, 2024. Balancing the productivity opportunities of financial technology and AI against the potential risks − speech by Randall S. Kroszne. Recent developments in technology and artificial intelligence (AI) provide huge potential for innovation and productivity growth. But they also create new financial stability risks. In this speech, Randy will outline the distinction between fundamentally disruptive versus more incremental innovation and the different regulatory challenges with dealing with these two types of change. He will also discuss the importance of the Financial Policy Committee and Financial Market Infrastructure Committee thinking about these issues in the context of both their primary and secondary objectives. 


IMF, May 30, 2024. Gita Gopinath: Crisis Amplifier? How to Prevent AI from Worsening the Next Economic Downturn. AI has the power to change our lives and the global economy. We have the power to shape that change for the better. We are hearing about some of the extraordinary ways Generative Artificial Intelligence could benefit our societies, including helping us live healthier lives and accelerating scientific breakthroughs. Many experts also believe the technology could provide significant economic benefits, for example by providing a serious boost to productivity. This could help lift the global economy at a time when the growth outlook for the medium term is the weakest in decades. This said, many also agree that AI’s promise comes with considerable uncertainty and significant risks. To date, most warnings have focused on security, privacy, misinformation, and ethical concerns. Taking an economic perspective, I would like to highlight a different sort of AI-related risk, one that has received much less attention. That is the risk that AI could exacerbate economic crises. The world economy will see another downturn—that much is certain. Today I will describe how the widespread use of AI could turn an ordinary downturn into a deep and prolonged economic crisis by causing large-scale disruptions in labor markets, in financial markets, and in supply chains. I will also discuss what policy actions—taken now—can help mitigate some of these downside risks.

World Bank. Measuring Development 2024: AI, the Next Generation. Foundational models like large language models (LLMs) have recently commanded widespread public attention—and caution—given their transformational potential for both our economy and society. Naturally, questions loom about how these AI innovations will impact the global development research and policy landscape. If used properly by the right actors, these tools might unlock enormous troves of data and create new opportunities to improve lives around the world. The World Bank’s Development Impact (DIME) department and Development Data Group (DECDG), the Center for Effective Global Action (CEGA), and the development community at the University of Chicago are excited to explore this topic at our tenth annual Measuring Development (MeasureDev) Conference, “AI, The Next Generation.”


Council of the EU and the European Council, May 21, 2024. Artificial intelligence (AI) act: Council gives final green light to the first worldwide rules on AI. Today the Council approved a ground-breaking law aiming to harmonise rules on artificial intelligence, the so-called artificial intelligence act. The flagship legislation follows a ‘risk-based’ approach, which means the higher the risk to cause harm to society, the stricter the rules. It is the first of its kind in the world and can set a global standard for AI regulation.  The new law aims to foster the development and uptake of safe and trustworthy AI systems across the EU’s single market by both private and public actors. At the same time, it aims to ensure respect of fundamental rights of EU citizens and stimulate investment and innovation on artificial intelligence in Europe. The AI act applies only to areas within EU law and provides exemptions such as for systems used exclusively for military and defence as well as for research purposes.

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