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:

The Dangerous Illusion Of Explainable AI In Modern Finance, Forbes. January 28, 2026. Finance has always rested on a simple moral contract. When decisions affect people’s money, homes and futures, someone must be able to explain why those decisions were made. That principle once lived in credit committees, underwriting manuals and human judgment. Today, it’s being handed to machines. To make that shift feel safe, the industry has wrapped AI in the language of transparency. Banks tell regulators that their models are explainable. Vendors sell dashboards that promise insight. Boards are assured that nothing essential is hidden. The message is that advanced AI and accountability can coexist. In practice, this promise no longer holds. The systems driving modern finance aren’t linear scorecards or rule-based engines. They’re deep neural networks, ensemble models and continuously learning systems trained on thousands of interacting variables. These machines don’t reason in steps that resemble human logic. They detect statistical patterns across vast data landscapes that have no simple causal story attached to them. What’s called explainable AI is an attempt to make this machinery appear legible. A secondary model is trained to imitate the primary one and then asked to generate feature attributions or importance scores. These outputs are turned into reports that look like reasons, but they aren’t. They’re approximations of correlations inside a system that has no concept of why. This matters because financial decisions rarely come from a single model. A mortgage, a credit limit or a fraud alert emerges from a network of engines assessing income stability, spending behavior, credit history, transaction risk and portfolio exposure. Each is trained on different data and optimized for different objectives. Their outputs combine into a final judgment that no individual can truly reconstruct, even if every piece were interpretable on its own. Yet the industry presents it as if it were. Regulators are shown model cards, fairness metrics and compliance narratives that offer a clean story of control. These artifacts aren’t fabrications, but they aren’t the truth, either. They describe how an approximation behaves, not how the system actually operates at scale. Inside large financial institutions, this gap is quietly understood. Model developers know that explainability tools are fragile. They change when models are retrained. They drift as data shifts. They give different answers depending on how the question is framed…

Companies including Palantir and Deloitte have collectively reaped more than $22bn from contracts linked to Donald Trump’s immigration crackdown. Financial Times, January 29, 2026. The “surprisingly resilient” global economy is at risk of being disrupted by a sharp reversal in the AI boom, the IMF warned on Monday, as world leaders prepared for talks in the Swiss resort of Davos. Risks to global economic expansion were “tilted to the downside”, the fund said in an update to its World Economic Outlook, arguing that growth was reliant on a narrow range of drivers, notably the US technology sector and the associated equity boom. Nonetheless, it predicted US growth would strongly outpace the rest of the G7 this year, forecasting an expansion of 2.4 per cent in 2026 and 2 per cent in 2027. Tech investment had surged to its highest share of US economic output since 2001, helping drive growth, the IMF found. “There is a risk of a correction, a market correction, if expectations about AI gains in productivity and profitability are not realised,” said Pierre-Olivier Gourinchas, IMF chief economist. “We’re not yet at the levels of market frothiness, if you want, that we saw in the dotcom period,” he added. “But nevertheless there are reasons to be somewhat concerned.” Donald Trump will travel to the Swiss resort of Davos this week for the World Economic Forum. The gathering is expected to mingle bullish assessments of US AI investments with anxiety about stock market valuations and threats to institutions, including the US Federal Reserve and Nato. The discussions are set to be dominated by the US president’s threat of hitting European countries with 10 per cent tariffs unless they agree to support him acquiring Greenland. The IMF outlook found that global economic expansion had been firmer than expected despite Trump-induced trade tensions and a widening array of geopolitical hazards. The fund boosted its outlook for 2026 global growth from 3.1 per cent to 3.3 per cent, with only a slight slowdown in 2027 to 3.2 per cent. A renewed escalation in the trade conflict could again unsettle growth prospects, however, the IMF cautioned. “Trade tensions could flare up, prolonging uncertainty and weighing more heavily on activity.” China will expand 4.5 per cent in 2026, an increase of 0.3 percentage points from the IMF’s October projections, followed by 4 per cent growth in 2027, according to the outlook. Among the G7 nations, Canada will have the second-strongest expansion this year after the US at 1.6 per cent. Canadian growth is forecast to pick up to 1.9 per cent in 2027. The IMF left its UK forecasts for 2026 and 2027 unchanged, with growth of 1.3 per cent this year and 1.5 per cent in 2027. German GDP will expand by 1.1 per cent this year and 1.5 per cent next, the IMF said. Global growth, the IMF said, was founded on the “narrow base” of an AI investment boom in the US. If expectations of AI-driven productivity advances proved overly optimistic, there was a risk of a “sharp drop” in investment and associated stock market reversal, the IMF warned.

The FCA has launched a review into the implications of advanced AI on consumers, retail financial markets and regulators. UK financial Conduct Authority, January 27, 2026. The Review will be led by Sheldon Mills and builds on the FCA’s existing work on AI. This includes its AI Discussion Paper, AI Sprint, and AI Lab including AI Live Testing and its groundbreaking Supercharged Sandbox supported by NVIDIA. AI is already embedded across financial services. Rapid advances in generative, agentic and emerging forms of AI mean the next phase of change could be profound, having the power to reshape markets, change the way firms compete and how consumers use retail financial services. Sheldon Mills said: ‘AI is already shaping financial services, but its longer-term effects may be more far-reaching. This review will consider how emerging uses of AI could influence consumers, markets and firms, looking towards 2030 and beyond. ‘By taking a forward-looking view, the review will help the FCA continue to support innovation while promoting the safe and trusted adoption of AI in retail financial services.’

The FCA is seeking views on 4 interrelated themes:

1. How AI could evolve in the future, including the development of more autonomous and agentic systems.
2. How these developments could affect markets and firms, including changes to competition and market structure and UK competitiveness.
3. The impact on consumers, including how consumers will be influenced by AI but also influence financial markets through new expectations.
4. How financial regulators may need to evolve to continue ensuring that retail financial markets work well.

While wholesale markets and broader societal impacts are out of scope, the Review recognises that developments in these areas may indirectly influence retail financial services and will be considered where relevant. The FCA is also separately doing extensive work on the impact of AI in wholesale markets, in particular through our live testing partnership. Feedback will shape a series of recommendations to be reported to the FCA Board in summer 2026, informing how the FCA can guide and respond to AI-driven transformation. This will culminate in an external publication..

1. The engagement paper sets out the scope of the review and invites views from stakeholders including firms, consumer groups, tech providers and academics on 4 key themes.
2. The FCA’s approach to artificial intelligence is grounded in its principles-based regulatory framework, including the Consumer Duty. This ensures outcomes-focused regulation that supports innovation while safeguarding consumers.
3. The FCA launched its AI Lab in 2024 to deepen understanding of AI technologies and their implications for financial services. The Lab works with industry, academia, and other regulators to explore responsible AI adoption.
4. This work forms part of the FCA’s wider commitment to leading thinking globally on the responsible adoption of advanced technologies in financial services, and to ensuring that the UK remains a trusted, competitive and resilient financial centre in the age of AI.
5. The FCA does not plan to introduce AI-specific regulation. It will continue to rely on its existing, principles-based regulatory framework while considering how regulators need to evolve as AI becomes more embedded in financial services.
6. Find out more information about the FCA.

Why BlackRock’s Larry Fink wants the entire financial system on ‘one common blockchain‘, DL News. January 22, 2026. Tokenisation will reduce fees and democratise finance, according to BlackRock CEO Larry Fink. Updating the financial system to run on blockchain technology is “necessary,” and promises to slash fees and boost accessibility for investors. That’s the case BlackRock CEO Larry Fink made while speaking on a World Economic Forum panel in Davos, Switzerland on Wednesday alongside Citadel CEO Ken Griffin and European Central Bank President Christine Lagarde. Tokenisation is the process of converting ownership rights of assets like real estate, stocks, or bonds into digital tokens on a blockchain. Proponents argue doing so will speed up finance, reduce costs and provide more accountability. “We would be reducing fees, we would do more democratisation,” Fink said. “[If] we have one common blockchain, we could reduce corruption.” For Wall Street titans like BlackRock, tokenisation presents a huge opportunity. Much of the core underlying software the global financial system runs on is between 40 and 60 years old. Because of this, it is often clunky and slow, and depends on costly intermediaries. Updating it to a blockchain-based system could make those who pioneer the change a lot of money. BlackRock isn’t the only one who’s bullish on blockchains. “Blockchain is the future for traditional banking,” said Sergio Ermotti, CEO of UBS, at the World Economic Forum earlier this week. “You will see a convergence.” The head of the world’s largest wealth manager just said blockchain’s convergence with traditional banking is inevitable. Ripple and Boston Consulting Group predict blockchain tokenisation will swell into a $19 trillion industry by 2033, while asset manager Grayscale forecasts a thousand-fold growth of tokenised assets, pushing their combined value to $35 trillion by 2030.

CONFERENCES:

Digital Economics and AI Tutorial, Spring 2026, Alfred P. Sloane Foundation and second link for this conference – DATE February 12-13, 2026 (US Pacific Time)