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.
NEWS:
Agencies now have access to a new artificial intelligence tool that has been test driven by the General Services Administration for the last eight months. Federal News Network, August 15, 2025. Through the USAi platform, agencies can take advantage of capabilities that include chat-based AI, code generation and document summarization. “We started with 10 users, and then we moved to 100 users, and then 1,000 users, and eventually rolled it out to all employees across GSA,” said David Shive, GSA’s chief information officer, in an interview with Federal News Network. “The business portfolio of GSA is very broad, and they started to apply this thing across those broad business domains. They started to do things like writing code that would satisfy some code development needs that they had completed in hours, not days, weeks or months. They started doing data analytics across multiple data sets, that would normally take days and weeks, and they were doing it in hours.”
GenAI Rewires Investment Operations Across Alternatives. Traders Magazine, August 14, 2025. Asset managers in the alternatives space are increasingly overwhelmed by fragmented, unstructured data flowing in from multiple accounting systems, according to Laurent Louvrier, VP of Product, Artificial Intelligence at Confluence Technologies. As the industry turns to AI-driven solutions to modernize legacy infrastructure and meet growing reporting demands, the focus, according to Louvrier, is not on full automation but on using GenAI to augment human review and build faster, more reliable data pipelines with “precision over blind automation”. According to Louvrier, at the heart of the AI transformation are three major trends that are reshaping how financial institutions approach data and operations. “First, the breakthrough in unstructured data processing: GenAI now handles PDFs, documents, emails, research reports, and other content as seamlessly as traditional structured datasets,” he told Traders Magazine. This alone addresses one of the most pressing challenges in financial services—making sense of high volumes of text-heavy content, he said.
AI is already impacting the labor market, starting with young tech workers, Goldman economist says, CNBC, August 5, 2025.
- Changes to the American labor market brought on by the arrival of generative AI are already showing up in employment data, according to a Goldman Sachs economist.
- There are signs of a hiring pullback in the technology sector, hitting younger employees there the hardest, according to Joseph Briggs, senior global economist of Goldman’s research division.
- Unemployment rates among tech workers between 20 and 30 years old jumped by 3 percentage points since the start of this year, Briggs said.
AI Is Coming for the Consultants. Inside McKinsey, ‘This Is Existential.’ Wall Street Journal, If AI can analyze information, crunch data and deliver a slick PowerPoint deck within seconds, how does the biggest name in consulting stay. The shape of the firm is also changing: McKinsey has reduced its head count, partly to correct a pandemic hiring spree, and rolled out roughly 12,000 AI agents. These bots now assist consultants in building PowerPoint decks, taking notes and summing up interviews and research documents for clients. Though the firm’s leaders are adamant McKinsey isn’t looking to reduce the size of its workforce because of AI, the size of teams is changing. Traditionally, a strategy project might have required a project leader, four consultants and a partner. Today, it might need a leader and two or three consultants—alongside a few AI agents and access to “deep research” capabilities.
Are AI Agents the Future of Business? Salesforce Is Betting $8 Billion on It Wall Street Journal, July 25, 2025 [podcast and transcript – no fee] Informatica isn’t a household name, but it plays a crucial role in helping companies like Toyota and Unilever manage and organize vast amounts of data. As artificial intelligence becomes more powerful, that data is like a gold mine. Customer relationship software company Salesforce recently struck a multibillion-dollar deal to acquire Informatica. On the latest episode of the Bold Names podcast, Informatica CEO Amit Walia speaks to WSJ’s Christopher Mims and Tim Higgins about why his company is worth $8 billion to Salesforce’s AI ambitions.
How Emerging Tech Will Transform Digital Banking Experiences Over The Next Decade. Forrester. Aurelie L’Hostis, Principal Analyst. Buying a car is a major and often stressful purchase. To improve this experience, Capital One introduced Chat Concierge, an AI agent designed to simplify car buying. Unlike typical chatbots, this conversational agent uses multiple specialized AI agents to understand prompts, create and validate action plans, and execute tasks based on buyer preferences. Chat Concierge was built to be able to compare vehicles, estimate trade-in values, and schedule test drives in one conversation. This type of innovation marks a new era in digital banking where AI agents take action, paving the way for more agentic experiences in our lives.
Digital Banking Is Poised For A Revolutionary Transformation Over The Next Decade – In my new report, The Future Of Digital Experiences In Banking, I explore how banks, fintechs, and big tech firms will leverage both maturing and emerging technologies to redefine digital banking experiences, ultimately reshaping the financial landscape. So what’s on the horizon?
GOVERNMENT DOCUMENTS:
Advances in AI will boost productivity, living standards over time. Federal Reserve Bank of Dallas. Mark A. Wynne and Lillian Derr. June 24, 2025. Artificial intelligence (AI), like many technologies before it, offers the potential to improve people’s living standards. Such advances can be approximated by changes in gross domestic product (GDP) per capita over time—the rate of change in the amount of output per person. Chart 1 shows GDP per capita from 1870 to 2024 along with scenarios, some of them extreme, depicting what could happen to living standards between now and 2050.
NGOs/IGOs – PAPERS:
Financial stability implications of artificial intelligence – Bank for International Settlement – Executive Summary. FSI Executive Summaries | 26 June 2025. PDF full text – The growing use of artificial intelligence (AI) by financial institutions is attracting closer regulatory scrutiny, including from a financial stability perspective. This expansion is driven by supply side factors, such as advances in large language models (LLMs), deep learning techniques, access to more unstructured data sources and increasing computational power, as well as demand side factors such as opportunities to reduce costs and the desire to stay competitive. Against this backdrop, the Financial Stability Board (FSB) report The Financial Stability Implications of Artificial Intelligence, published in November 2024, provides of stocktake of industry and regulatory/supervisory AI use cases and identifies potential implications for financial stability. Drivers of AI use cases in the financial sector. The report identified supply and demand side factors (summarised in the diagram and table below), noting that the former currently play a bigger role due to recent technological advancements.
The AI supply chain. BIS Papers | No 154 | 18 March 2025. by Leonardo Gambacorta and Vatsala Shreet.i PDF full text .The rapid advancement of artificial intelligence (AI) relies on a complex supply chain comprising five key layers: hardware, cloud infrastructure, training data, foundation models and AI applications. This paper examines the market structure of each layer and highlights the economic forces shaping them: rapid technological change, high fixed costs, economies of scale, network effects and, in some cases, strategic behaviour by dominant firms. We also highlight the expanding influence of big tech companies across the AI supply chain. We discuss the challenges for consumer choice, innovation, operational resilience, cyber security and financial stability.
Algorithmic Coercion with Faster Pricing. Working Paper 34070. DOI 10.3386/w34070 Issue Date Revision Date We examine a model in which one firm uses a pricing algorithm that enables faster pricing and multi-period commitment. We characterize a coercive equilibrium in which the algorithmic firm maximizes its profits subject to the incentive compatibility constraint of its rival. By adopting an algorithm that enables faster pricing and (imperfect) commitment, a firm can unilaterally induce substantially higher equilibrium prices even when its rival maximizes short-run profits and cannot collude. The algorithmic firm can earn profits that exceed its share of collusive profits, and coercive equilibrium outcomes can be worse for consumers than collusive outcomes. We use simulations to show how coercion arises rapidly when the algorithmic firm’s rival uses a simple learning process to set prices. Finally, we examine the implications of algorithm technology for platform design.