AI in Finance and Banking, February 17, 2025

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.

PAPERS:

AI and Women’s Employment in Europe. Stefania Albanesi, António Dias da Silva, Juan F. Jimeno, Ana Lamo & Alena Wabitsch. Working Paper 33451. DOI 10.3386/w33451. Issue Date February 2025. We examine the link between the diffusion of artificial intelligence (AI) enabled technologies and changes in the female employment share in 16 European countries over the period 2011-2019. Using data for occupations at the 3-digit level, we find that on average female employment shares increased in occupations more exposed to AI. Countries with high initial female labor force participation and higher initial female relative education show a stronger positive association. While there exists heterogeneity across countries, almost all show a positive relation between changes in female employment shares within occupations and exposure to AI-enabled automation.

Noguer I Alonso, Miquel, Large Language Models in Finance: Reasoning (December 08, 2024). Available at SSRN: https://ssrn.com/abstract=5048316 or http://dx.doi.org/10.2139/ssrn.5048316  – Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing but face significant challenges in complex financial reasoning tasks that require multi-step logical inference, domain-specific knowledge, and adherence to regulatory frameworks. This paper provides a comprehensive survey and extension of advanced techniques for enhancing LLMs’ reasoning capabilities, including neuro-symbolic integration, hierarchical reasoning, Chain-of-Thought prompting, ReAct frameworks, and retrieval-augmented generation. We present detailed finance specific implementations and use cases, including portfolio optimization under dynamic constraints, scenario-based stress testing, regulatory compliance analysis, and credit risk assessment, demonstrating how these techniques enable more transparent, reliable, and efficient decision-making. Our framework specifically addresses key challenges in scalability, interpretability, and bias mitigation, while advancing new directions for cognitively-inspired architectures, seamless neuro-symbolic pipelines, and continuous learning systems that adapt to evolving market conditions and regulatory requirements.
Ozili, Peterson K, Digital Innovations for Increasing Financial Inclusion: CBDC, Cryptocurrency, Embedded finance, Artificial Intelligence, WaaS, Fintech, Bigtech, and DeFi (August 28, 2024). Impact of Artificial Intelligence on Society, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4939348 or http://dx.doi.org/10.2139/ssrn.4939348
Digital innovations are emerging to solve known problems using new digital tools or technologies. Digital innovations also have wide application for financial inclusion. Private sector agents are using digital innovations to increase financial inclusion in remarkable ways. This chapter explores the recent digital innovations that are changing the financial inclusion landscape toward digital financial inclusion. The study used the discourse analysis methodology. It was found that digital innovations, such as central bank digital currency (CBDC), cryptocurrency, embedded finance, artificial intelligence, wallet as a service (WaaS), Fintech, Bigtech, and decentralized finance (DeFi), are helping to accelerate digital financial inclusion in many parts of the world. Each of these digital innovations serve a specific purpose, and they contribute to accelerating digital financial inclusion in unique ways, even though they all pose some risks that can be mitigated with careful and purposeful.

CONFERENCES:

AI in Finance Summit New York, April 15-16, 2025 – Explore exclusive insights and advanced technical use cases presented by AI experts and data scientists from the Banking, Financial Services, and Insurance sectors,

INDUSTRY:

2025 Global Outlook for Banking and Financial Markets. IBM Institute for Business Value. What banks will win and lose in the age of AI? This report offers the data and strategies needed to create long-term success in a global marketplace. As we enter 2025, the banking sector faces a critical juncture, balancing a unique confluence of new challenges and opportunities that will define its evolution over the next decade. Over the past 15 years, the aftershocks of the 2008 Global Financial Crisis, ever-tightening regulatory pressures, low interest rates, and fierce market competition have hampered banks’ competitiveness. This convergence has created an environment where profitability is under pressure, cost-to-income ratios are elevated, and price-to-book ratios remain strained. The stage is set for a showdown: banks able to adapt will thrive, while others risk being left further behind. Yet, in the midst of these challenges, one undeniable trend is emerging as the game changer: artificial intelligence. AI is rapidly becoming the foundation of banking strategies, redesigning operational transformation and the reinvention of business models in the pursuit of healthier financial outcomes while addressing risk and compliance requirements. The 2025 Global Outlook for Banking and Financial Markets offers key insights into these pivotal shifts and provides the framework for strategic action that can elevate financial performance in this rapidly changing landscape. For banking leaders, this is more than just a guide—it is a call to action.

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Posted in: AI in Banking and Finance, Cryptocurrency, Economy, Financial System
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