1 Jun 2026

Saris raising $28.8M on a promise to automate 70% of lending tasks is a number designed to get CFOs excited and get procurement moving. In my experience, that figure tells you almost nothing useful.

The critical question for any UK lender evaluating agentic workflow tools is not what percentage of tasks can be automated, but which tasks. Automating 70% of low-stakes document sorting is a different proposition entirely from automating any meaningful portion of credit decisioning, affordability assessment, or complaint handling. The distinction matters enormously under Consumer Duty, where firms are accountable for outcomes regardless of whether a human or an algorithm produced them.

The framing of "workflow automation rather than standalone copilots" is actually the interesting signal here. The market is shifting away from AI tools that sit alongside people and toward AI systems embedded in the process itself. That is a governance step-change that most UK consumer finance firms are not ready for.

• Agentic systems acting within lending workflows need audit trails that satisfy the FCA, not just internal stakeholders.
• Integration with existing infrastructure sounds appealing until you remember that most lender back-offices run on systems that were not built to expose reliable, clean data to an AI layer.

The 35% cost reduction claim is the other number worth scrutinising. Cost reduction in lending operations often means headcount reduction, and in a regulated environment that carries real risk. When something goes wrong in an automated workflow, and it will, you need people who understand the process well enough to diagnose the failure. Firms that cut too deep before their AI systems are genuinely proven will find that out the hard way.

The question UK technology leaders should be sitting with is this: are we buying genuine operational improvement, or are we buying a set of numbers that look good in a board presentation while the hard governance work gets deferred?

TD Bank cutting mortgage pre-adjudication from 15 hours to three minutes is not a headline about Canada. It is a benchmark that every UK lending operations director should be sitting with right now.

The interesting thing here is not the speed itself. Faster decisioning is an obvious goal. What matters is where the time went. Pre-adjudication is the unglamorous middle layer of mortgage processing, the bit where underwriters chase documents, check income, cross-reference affordability rules, and make preliminary calls before a formal decision. That work is cognitive, repetitive, and expensive. If agentic AI is genuinely compressing 15 hours of that into three minutes, then the cost model for mortgage origination just broke open.

UK lenders are not standing still on AI, but most deployments I see are at the edges: chatbots handling inbound queries, fraud scoring, document OCR. The core decisioning workflow, the thing that actually determines whether a customer gets a mortgage and how quickly, remains largely human-gated. That gap is going to start looking very uncomfortable very quickly.

There is also a regulatory dimension worth taking seriously. The FCA's Consumer Duty requires firms to deliver good outcomes, and speed of decision is increasingly part of that. A customer waiting two weeks for a mortgage decision while their lender's competitor turns it around in hours is not a neutral experience. It is a measurable harm by another name.

TD is talking about $500 million in annual cost savings alongside equivalent revenue uplift. UK institutions will rightly note that scale matters, and TD operates at a different order of magnitude. But the underlying economics of agentic AI in lending do not require TD's headcount to work. The question UK technology leaders should be asking is not whether this applies to them. It is how many origination cycles they can afford to lose before it becomes urgent.

Goldman's forecast of a 24-fold increase in token consumption by 2030 is getting a lot of attention, mostly framed as good news for the hyperscalers. The margin inflection story is compelling if you're a Goldman equity analyst covering Nvidia. For those of us building credit infrastructure in the UK, the interesting question is different: who actually captures the value as AI agents become the dominant mode of interaction?

The hyperscalers will do fine. Falling compute costs improve their economics, and the report makes a reasonable case for that. But falling input costs don't automatically translate into margin for the firms consuming those services. We've seen this before with cloud. AWS pricing came down consistently for years, and yet most financial services firms didn't see their technology cost base shrink. The savings got reinvested into more capability, more complexity, more vendor dependency.

AI agents will follow the same pattern. As always-on autonomous agents become standard in loan origination, affordability assessment, and customer servicing, the cost-per-decision may fall. The total cost of running an AI-native operation probably won't, at least not initially, because the appetite for what you can now do expands to fill the available budget.

There's a regulatory dimension here that the Goldman report naturally ignores. UK consumer credit is governed by rules that assume a human can explain a decision. When your agents are processing applications, adjusting credit limits, or triggering collections activity autonomously, the FCA's Consumer Duty expectations don't pause to admire your margin inflection. Someone still has to own the outcome.

The firms that will actually benefit from the agentic wave are the ones that redesign their operating model around it now, not the ones that bolt agents onto existing workflows and hope the maths works out. That's a change management problem as much as a technology one.

The question worth sitting with: are you building for the world where AI reduces your cost to serve, or the world where it changes what serving a customer even means?

The framing from Visa and Mastercard deserves scrutiny. Both networks are describing agentic commerce as a transaction multiplier, which is true, but they're also the ones selling tokenization and fraud prevention services on top of those transactions. Their enthusiasm is structurally motivated.

That doesn't make the underlying trend wrong. AI agents that shop autonomously will genuinely create more payment events than humans do. A human books one flight. An agent might check, hold, compare, release, and rebook across three carriers before settling. Each touchpoint is potentially a transaction or an authorisation attempt. Volume goes up. So does the surface area for fraud.

The bit UK consumer finance leaders should sit with is what this does to credit decisions.

Today, a borrower applies for a loan. There's a moment of intent, a credit check, an offer, acceptance. Agentic commerce breaks that sequence. If an AI agent is authorised to spend on behalf of a consumer, the question of who made the credit decision, and when, becomes genuinely complicated. Was it the consumer when they set the agent's budget parameters? Was it the lender who extended the credit line the agent is drawing on? Regulation hasn't caught up with this.

The FCA's consumer duty framework is built around the idea that firms understand the needs of the person they're serving. When that person is an algorithm acting on behalf of a person, the duty of understanding gets murky fast.

Standards for agentic payments are still being developed, as both networks acknowledge. UK lenders and brokers should be in those conversations, not waiting for the card schemes to define the rails and then adapting to whatever gets built. The firms that shape how agent-initiated credit works will have a meaningful advantage over those who inherit someone else's architecture.

AI-generated video for social media sounds like a marketing department problem. For anyone running consumer credit products in the UK, it is actually a regulatory one.

The FCA's Consumer Duty requires that financial promotions are fair, clear, and not misleading. That standard already trips up human copywriters with time to think. An AI video tool that blends app interfaces with real-world footage, optimised for engagement rather than accuracy, is a different kind of risk entirely. The gap between 'looks professional' and 'meets FCA financial promotion standards' is wide, and these tools sit firmly on the wrong side of it.

The deeper issue is speed. These generators are built to collapse production time. A marketing team can go from brief to published social content in an hour. Your compliance review process almost certainly cannot move that fast. That mismatch is where problems enter the world.

Two things that technology leaders in consumer finance should be thinking about:

• Whether your financial promotion sign-off process has any controls that account for AI-generated content, or whether it still assumes a human wrote a script and another human reviewed it
• Whether your brand guidelines actually prohibit or permit synthetic footage of your product interfaces, given how easily a generated video could misrepresent a loan journey or a rate

None of this means the tools are useless. For brand awareness content that stays well away from regulated claims, there is genuine efficiency here. A short video showing the texture of a brand, without quoting rates or implying outcomes, sits in safer territory.

But the consumer credit sector has a specific problem: almost everything we communicate touches on a financial decision. The line between brand content and a financial promotion blurs very quickly when your product is a loan.

The question I would put to any marketing or technology leader considering these tools is straightforward. Who in your organisation is accountable for a compliance failure in an AI-generated video that published at 9pm on a Friday?

The headline writes itself as a crypto milestone, but that framing misses what actually matters here. SoFi becoming the first US national bank to issue a stablecoin on a public blockchain is interesting for about five minutes. What's interesting for much longer is the Galileo angle.

Galileo processes accounts for 160 million users across hundreds of fintechs. Embedding stablecoin settlement into that platform means SoFi doesn't need to convince consumers to change behaviour. It pushes the capability into the infrastructure that other companies already depend on. That's a completely different growth model to launching a wallet and hoping people download it.

The Mastercard integration compounds this. Settlement rails that connect stablecoin balances to a global card network remove the last objection that stablecoins are only useful inside closed ecosystems. You can hold a dollar-denominated token and spend it anywhere Mastercard is accepted. The friction that killed previous consumer crypto products was the off-ramp. SoFi has effectively buried the on-ramp and off-ramp inside products people already use.

For UK consumer finance leaders, the regulatory question is the obvious blocker. The FCA's approach to stablecoins under the Financial Services and Markets Act 2023 regime is still being shaped, and no UK bank is close to attempting this. But the strategic lesson doesn't require regulatory equivalence to be useful right now:

• Distribution infrastructure is the moat, not the token itself
• Whoever controls the middleware layer controls the adoption curve
• Settlement speed improvements don't need consumer education if they're invisible

The UK payments sector has CHAPS, Faster Payments, and the New Payments Architecture still being rolled out. Stablecoin settlement isn't displacing those in the near term. But if a large UK fintech embedded programmable settlement into its BaaS offering the way Galileo just has, the competitive pressure on legacy processors would be immediate.

The question worth sitting with is whether any UK institution has the combination of banking licence, middleware scale, and regulatory appetite to make the equivalent move, or whether we watch this unfold in the US for another three years before anyone here takes it seriously.