This semi-monthly column highlights news, government documents, NGO/IGO papers, conferences, industry white papers and reports, academic papers and speeches, and central bank actions 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.
NEWS:
More than 200 Lloyds bank bosses to receive artificial intelligence training. Computer Weekly, March 26, 2025. Lloyds Banking Group is training 200 of its senior leaders to ensure the organisation can get the most out of artificial intelligence (AI) technology. The bank is working with training provider Cambridge Spark on the programme, which will embed AI skills in the leadership ranks. Participants of the programme will receive training in an 80-hour programme, known as Leading with AI, delivered by Cambridge Spark alongside experts from Cambridge University. Ron van Kemenade, chief operating officer at Lloyds Banking Group, said: “AI is a game-changer for financial services, and we’re investing to enhance our services with cutting-edge technology. The programme with Cambridge Spark will empower our business leaders to further innovate with AI and drive commercial excellence using this transformative technology. “Our approach to AI is based on integrating it deeply throughout every aspect of our business rather than limiting it to a centralised technical team. We’re building on our existing expertise to develop the most AI-capable leadership team in banking.” Lloyds Bank has also made investments in AI training beyond senior leaders with a Data & AI Academy, GenAI Masterclasses and a Data & AI Summer School available to all its employees. It has worked with Cambridge Spark before on a graduate bootcamp focused on practical industry skills for emerging data scientists and data engineers.
PAPERS/REPORTS:
Why, what, and how financial services firms can be AI-First. HFS. March 25, 2025. Thank you GenAI for kicking the door open to help banking and financial services (BFS) enterprises bring AI out of back-office oblivion. GenAI served as the catalyst to get AI back in the boardroom, and not a moment too soon, as the advance of AI technologies such as agentic AI is far exceeding the ability of established BFS firms to meaningfully assess, adopt, and apply AI in strategically meaningful ways. And by “strategically meaningful,” we mean doing more than hitting the low-hanging fruit lever of productivity with a side of potential cost savings. There is a massive opportunity for BFS enterprises to become AI-First leading with AI and automation to gain efficiencies, create new value, and drive competitive advantage rather than continuing to lead with people and manual processes. HFS Research, in partnership with Infosys, set out to better understand how financial institutions around the globe are addressing the burgeoning AI opportunity. We surveyed 505 BFS leaders across major geographies to better understand why, what, and how BFS firms can be AI-First:
- The WHY–why are BFS firms investing in AI?
- The WHAT–what’s being invested in and executed to make AI strategies real?
- The HOW–how can BFS firms overcome roadblocks to unlock value?
The sample included an intentional mix of IT and business leaders across banks and capital markets firms. We complemented the survey with detailed drill-down interviews with BFS leaders to road-test our analysis and develop pointed recommendations for AI success across the C-Suite–the “so what.” The report includes a case study on Citizens Bank’s AI journey to showcase a tangible example of BFS progress towards being AI-First. The study reveals that BFS enterprises are all in on a formalized and funded embrace of AI. However, they risk failure if they don’t drive global, enterprise-wide AI strategies that contemplate more than people-centric bottom-line gains. To unlock the AI-First opportunity, BFS firms must recognize that their AI strategy IS their business strategy, with C-suite leadership driving clarity of purpose.
EUROMONEY. March 24, 2025. AI in Banking. In this report, we offer an unrivalled deep look into how individual banking leaders are thinking about AI and how they are acting on it. How banks are deploying AI today and tomorrow The rapidly increasing power of generative artificial intelligence (gen AI) models is more than a passing fad, even if the full extent of its impact in financial services is yet unclear. Some banks are already experimenting with multiple AI agents, plugged into internal and external applications, to assess customers’ problems and even to solve them. In this report, we offer an unrivalled deep look into how individual banking leaders are thinking about AI and how they are acting on it. How are they leveraging the technology? And which are the most successful and forward-looking initiatives in gen and agentic AI? We held more than 30 in-depth conversations with those in charge of implementing gen and agentic AI at top global banks, and in many tech-leading national banks. We also spoke to banking-focused AI professionals at LLM vendors, and smaller AI-focused fintech firms.
Cui, Zheyuan and Demirer, Mert and Jaffe, Sonia and Musolff, Leon and Peng, Sida and Salz, Tobias, The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers (February 10, 2025). Available at SSRN: https://ssrn.com/abstract=4945566 or http://dx.doi.org/10.2139/ssrn.4945566 – This study evaluates the impact of generative AI on software developer productivity via randomized controlled trials at Microsoft, Accenture, and an anonymous Fortune 100 company. These field experiments, run by the companies as part of their ordinary course of business, provided a random subset of developers with access to an AI-based coding assistant suggesting intelligent code completions. Though each experiment is noisy, when data is combined across three experiments and 4,867 developers, our analysis reveals a 26.08% increase (SE: 10.3%) in completed tasks among developers using the AI tool. Notably, less experienced developers had higher adoption rates and greater productivity gains.
Predicting financial market stress with machine learning. BIS Working Papers | No 1250 | 17 March 2025 by Iñaki Aldasoro, Peter Hördahl, Andreas Schrimpf and Sonya Zhu. Understanding and predicting financial market stress is crucial for maintaining economic stability. Episodes of market stress can disrupt credit availability, influence asset prices and hinder economic growth. Traditional measures of financial conditions, such as financial stress indices (FSIs) and financial conditions indices (FCIs), often fail to distinguish between general market sentiment and specific vulnerabilities, reducing their predictive power. In our paper, we explore the potential of machine learning to provide more accurate and timely predictions of financial market stress, focusing on key US markets.
How Much Should We Spend to Reduce A.I.’s Existential Risk? NBER Working Paper 33602. DOI 10.3386/w33602. Issue Date During the Covid-19 pandemic, the United States effectively “spent” about 4 percent of GDP — via reduced economic activity — to address a mortality risk of roughly 0.3 percent. Many experts believe that catastrophic risks from advanced A.I. over the next decade are at least this large, suggesting that a comparable mitigation investment could be worthwhile. Existing lives are valued by policymakers at around $10 million each in the United States. To avoid a 1% mortality risk, this value implies a willingness to pay of $100,000 per person — more than 100% of per capita GDP. If the risk is realized over the next two decades, an annual investment of 5% of GDP toward mitigating catastrophic risk could be justified, depending on the effectiveness of such investment. This back-of-the-envelope intuition is supported by the model developed here. In the model, for most of the scenarios and parameter combinations considered, spending at least 1% of GDP annually to mitigate AI risk can be justified even without placing any value on the welfare of future generations.
NGO/IGOs
How Artificial Intelligence Can Boost Productivity in Latin America. IMF. March 20, 2025. Some countries risk missing out on the full economic benefits of AI, but more formal jobs and expanded digital access can help.
Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity IMF. February 21, 2025. Cucio, Micholo; Hennig, Tristan This paper combines labor force survey microdata with measures of occupational AI exposure and complementarity to examine the potential impact of recent advancements in AI on the Philippine labor market. We find that around one third of workers are highly exposed to AI with around sixty percent of those also rated highly complementary, indicating potential productivity gains. College-educated, young, urban, female, and well-paid workers in the services sector are most exposed. Business process outsourcing (BPO) is identified as the sector with the highest proportion of jobs at risk of displacement. Addressing regulatory gaps, infrastructure needs, and workforce reskilling is crucial to maximize benefits and mitigate negative impacts.