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:
FCA sets out plans to help build mortgage market of the future. Financial Conduct Authority (FCA), December 15, 2025. First-time buyers and the self-employed could get a step-up onto the housing ladder, under new plans from the FCA. Its priorities for reforms to the mortgage market also include helping homeowners unlock housing wealth for a more comfortable later life. The FCA will focus on 4 areas:
- First-time buyers & underserved consumers: Simplifying mortgage rules to allow more flexible products that reflect different working patterns and income levels at different stages of life.
- Later-life lending: Reviewing retirement interest-only requirements to make them more accessible. Exploring ways to improve advice to help people confidently plan for later life. Conducting a focused market study to ensure the lifetime mortgage market can meet the changing needs of future customers.
- Innovation & disclosure: Encouraging the use of data and technology, such as AI, to help brokers give better and faster advice while keeping a human touch. Looking at ways to make advertising and disclosure rules simpler, so consumers can understand information online more easily.
- Protecting vulnerable consumers: Working with partners to support people affected by financial abuse and help those using a mortgage to manage or consolidate debt.
How AI Is Changing M&A — Without Losing What Makes These Deals Work. Entrepreneur. December 15, 2025.
Key Takeaways
- Artificial intelligence is transforming M&A, allowing for rapid data analysis and strategic insights, outpacing traditional methods.
- AI automates parts of the acquisition process, from identifying targets to due diligence, significantly reducing time and enhancing decision-making.
- Despite AI’s impact, successful M&A still relies on the human touch for experience-based instincts and relationship management.
‘Stop sticking your heads in the sand’: JPMorgan CEO Jamie Dimon warns AI will eliminate jobs. bt business, December 15, 2025. This is not the first time the JPMorgan Chase CEO has sounded the alarm on AI’s impact. In November 2025, Dimon predicted that artificial intelligence could eventually allow people in developed economies to work far fewer hours — perhaps just three and a half days a week — within the next 20 to 40 years.
Agentic AI in Finance and Accounting: The Stuff Actually Working Right Now, Tech Bullion, December 12, 2026. Look, I’m going to be honest here. I get pitched on finance technology constantly. Every vendor says their thing is revolutionary. Most of it isn’t. But agentic AI in finance and accounting? This is actually different. This is the first time in years I’ve seen something that genuinely changes how accounting departments operate. The problem is nobody’s really talking about what’s actually happening in real accounting departments. They’re talking about the theory. They’re talking about what’s possible. But the actual implementations? The real problems they’re solving? That’s where it gets interesting.
The 5 Ps Of Digital Finance Architecture. Forbes, December 11, 2025. For years, organizations have invested heavily in digital transformation—ERP upgrades, automation tools, analytics platforms—yet finance functions still wrestle with familiar pain points from fragmented data and manual reconciliations to slow closes and reactive compliance. The problem isn’t technology; it’s architecture. In the age of cloud, AI and real-time data, finance needs a design language that connects systems, people and purpose. After leading multiple SAP S/4HANA cloud and public-sector transformation programs, I’ve distilled the principles that consistently determined success. I call them the five Ps of digital finance architecture: purpose, platform, process, people and performance.
A top economist warns that AI borrowing dwarfs Y2K-era debt and poses a risk to the financial system. Business Insider. December 11, 2025.
- Mark Zandi is worried that AI companies’ borrowing spree could be a risk to financial markets.
- Top tech firms have been on a borrowing spree this year as they aim to win the AI arms race.
- The level of borrowing eclipses what was seen in the dot-com era, Zandi says
Trump signs executive order to block state AI regulations. AP, December 11. 2025. President Donald Trump signed an executive order Thursday aimed at blocking states from crafting their own regulations for artificial intelligence, saying the burgeoning industry is at risk of being stifled by a patchwork of onerous rules while in a battle with Chinese competitors for supremacy. Members of Congress from both parties, as well as civil liberties and consumer rights groups, have pushed for more regulations on AI, saying there is not enough oversight for the powerful technology. But Trump told reporters in the Oval Office that “there’s only going to be one winner” as nations race to dominate artificial intelligence, and China’s central government gives its companies a single place to go for government approvals. “We have the big investment coming, but if they had to get 50 different approvals from 50 different states, you can forget it because it’s impossible to do,” Trump said.
UK banks turn to AI for fraud prevention and to improve services [no paywall]. Tools help detect organised crime, automate lending checks and deliver personalised financial offerings. Financial Times, FT.com. December 3, 2025. Britain’s big banks are using artificial intelligence to crack down on people trafficking, personalise customer investment choices and overhaul call centres. The latest wave of generative AI models are allowing lenders to go beyond traditional machine learning techniques, which have long been used to identify potential cases of fraud and assess credit risks. Santander has developed an AI model trained to identify suspicious patterns of behaviour in accounts which could point to instances of people trafficking. According to Jas Narang, Santander UK’s chief transformation, data and AI officer, banks have historically been slow to identify this sort of organised crime from customer data. “It has been a little bit hit and miss for all banks in the past,” he says. “And more importantly, it’s not always been timely — it has been analysis [coming after] the event by which time criminals have moved on.” However last year, the bank built an AI tool which was trained to pick up on certain “tells” that could indicate people trafficking — such as money being deposited into the account from several different locations within a few minutes of each other. Narang added the difference between traditional machine learning, which is used to analyse vast reams of data, and generative AI, is that the latter can make judgments in a more timely manner. “The difference between what was happening previously and now is the timeliness. It’s picking up stuff whilst criminal activity is being perpetuated. So you can literally pick it up on the day.” Since the rollout of the tool last year, the technology has allowed Santander to generate hundreds of leads indicating trafficking, which the lender then passed on to the authorities for further investigation.
Firms harness AI tools in search for competitive edge. [no paywall] Financial Times. FT.com, December 3, 2025. Technology use ranges from trawling mass data sets during audits to drafting consulting documents in minutes. Within weeks of Donald Trump’s “liberation day” in April and the ensuing widespread panic after the sweeping escalation of the US president’s trade policy, KPMG had a tariff calculation model ready that it says saved its clients “hundreds of millions of dollars”. The Big Four firm was “first to market” with the model, according to Stephen Chase, KPMG’s global head of AI and digital innovation, a feat he says would have been impossible without sustained investment in AI technology for over a decade. Being first to advise has become the new competitive edge for accounting and consulting firms as they push out AI across their businesses, particularly for large legacy firms competing with nimble AI-native start-ups. From trawling mass data sets during audits to find high-risk transactions to drafting consulting documents in minutes, the technology is expected to reorganise how professional services firms work. Soon after, Chase adds, KPMG snatched an audit bid from the jaws of a rival firm by showing off its AI capabilities to the client. “They were going to go with one of our competitors,” he says. The rival firm had planned to send the customary “army of people” to manage the major task of transitioning the audit, but KPMG showed the client their AI audit platform, Clara, which the firm says can consume the same volume of information faster, with fewer people. “They went from sceptical to KPMG client,” he adds. For smaller accounting firms, AI is proving just as helpful. Nearly half of UK firms with turnover up to £500mn reported at least a small rise in productivity from using AI, equivalent to reclaiming almost half a 40-hour week, a study by Xero and the Centre for Economics and Business Research found.
REGULATORY – UK
The FCA regulates financial services firms in the UK, setting standards for firms to meet and holding them to account if they don’t.
Financial Conduct Authority (FCA) Mortgage Rule Review Feedback statement and Roadmap for 2026. The FCA’s 5-year strategy published earlier this year, aims to deepen trust, rebalance risk, support growth and improve lives. As part of this work, the FCA is reviewing mortgage rules to consider how to update its mortgage framework to support consumers in accessing the market…In June 2025, our Discussion Paper (DP25/2) launched a public conversation. It considered areas where changes may be needed to support sustainable home ownership and economic growth, and where increased flexibility could allow firms to tailor their product offerings to consumers’ evolving needs. We have listened to stakeholders and respondents to the DP, and to feedback from July 2024’s Consumer Duty Call for Input. We believe there are several areas where we can act to widen access, support growth and improve lives. This Feedback Statement (FS25/6) sets out our response to feedback following DP25/2 and action we will take as part of a longer-term plan to modernise our mortgage rules.
Who this is for – This paper will primarily interest:
- Mortgage lenders and administrators, including later life and equity release firms.
- Home purchase providers and administrators.
- Mortgage intermediaries.
- Trade bodies representing mortgage lenders and intermediaries.
- Consumer groups and organisations.
- Consumers who own, or want to own, their home with a mortgage, or who want to release equity from their home for later life.
IMF WORKING PAPERS:
GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies. December 5, 2025.
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in nowcasting across simulation and six country cases, traditional econometric models tend to outperform ML algorithms. Among the ML algorithms, linear ML algorithm – Lasso and Elastic Net – perform best in nowcasting, even surpassing traditional econometric models in cases of long GDP data and rich high-frequency indicators. Among the traditional econometric models, the Bridge and Dynamic Factor deliver the strongest empirical results, while Three-Pass Regression Filter performs well in our simulation. Due to the relatively short length of GDP series, complex and non-linear ML algorithms are prone to overfitting, which compromises their out-of-sample performance.