Karsten Wenzlaff, Advisor
August 26th, 2025
Mar 19, 2026 | NCFA Feature | AI Finance Policy

On Jan 27 2026, the UK Financial Conduct Authority launched the Mills Review into the long term impact of AI on retail financial services to examine how AI could reshape consumers, firms, markets, and regulation through to 2030. NCFA flagged the review earlier in NCFA Weekly Fintech Intelligence Jan 24-30, 2026.
On Mar 4 2026, Innovate Finance submitted its response to the Mills Review, setting out where the UK fintech industry believes deployment will stall unless policy and infrastructure move faster. The paper cites Bank of England and FCA data showing 75% of firms now use AI, up from 58% in 2022. The issue is no longer whether AI adoption will happen. It is what still blocks firms from using AI inside live financial workflows at scale.
AI is clearly evolving from chatbot assistance to execution at scale. The submission describes AI agentic systems that can act on behalf of users. One example is an AI bot that handles everything from comparing mortgage deals to submitting the application and coordinating with conveyancers under user permission.
The value is no longer only in the model itself (ie. speed, quality, cost, expertise), but rather the full operational chain from customer permission to data access to execution to payment. That's why industry is focused on a stacked layer of tech solutions from Open Finance and Digital ID to payment access and rulebook friction to ensure AI can fully complete financial tasks.
The same logic applies to industry concerns over gatekeepers. As AI agents begin to initiate and route transactions, control moves to the layer that connects the agent to the payment method and the financial product. If that layer becomes concentrated, a small number of providers can influence access, routing, and competition.
The response uses real commercial examples and market data, highlighting that AI in finance is already underwriting, trading, core banking, and compliance.
The next phase isn't whether or not firms can build AI tools. It is whether regulation and infrastructure will allow them to use those tools in broader customer and transaction flows.
The stronger points made is that AI in finance won't scale on model quality alone. It will however scale on the stack around the model. That means smart data, Open Finance, Digital ID, fraud data sharing, wallet infrastructure, and payment access. Without those layers, AI stays stuck in narrow support roles. With them, it can move into lending, advice, payments, and automated execution.
That is why the response is more useful than another generic values and ethics based AI policy statement. It identifies where deployment slows, where control could become concentrated, and what has to move together if the UK wants AI to scale significantly inside financial services.
Canada is also building its next AI strategy. The federal government launched an AI Strategy Task Force in September 2025 as part of a 30 day national sprint, and later said it heard from more than 11,000 Canadians and 28 task force members. The Canadian process is broad. It is focused on national AI leadership, trust, safety, adoption, and public interest.
That broad approach is already raising execution questions. NCFA covered this earlier in its analysis of Canada’s AI strategy and capital flight risk, which argued that deployment, investment, and commercialization need clearer direction.
The UK industry response to the Mills Review is more targeted. It focuses on what is blocking AI deployment inside financial services today. Open Finance, Digital ID, payment access, wallets, third party model assurance, and rulebook friction sit at the center of that response.
Canada is still discussing the national direction of AI while UK fintech industry is already laying out what has to change for AI to work inside live financial workflows. The lesson for Canada is straightforward. AI policy cannot move on its own. Open Finance, Digital ID, wallet policy, payments modernization, and data access frameworks need to move with it or adoption in regulated finance will stay limited.
There is also a market structure lesson. If agent led payments grow, whoever controls the interface between the agent, the wallet, and the payment rail can control distribution. Policymakers who want competition and innovation to hold need to keep that layer open.
The industry response to the Mills Review is not just a call for clearer AI rules. It argues that the next barrier sits outside the model. Data access, identity, payments, and regulatory clarity now decide whether AI in finance stays at the support layer or moves into execution. The firms and jurisdictions that solve those bottlenecks will have the advantage.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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Mar 18, 2026 | NCFA Fintech Market Insight | Payments And Consumer Finance And Tax

On Mar 17 2026, H&R Block Canada revealed tipping survey results putting new numbers behind a growing consumer reaction to tip prompts at checkout. Two thirds of Canadians or 67% say Canada should abolish tipping culture. Another 93% say they feel annoyed when a card machine prompts for a tip in places where tipping was not previously expected, and 89% say tipping is out of hand and is applied to goods and services they do not think warrant tipping.
This backlash isn't just frustration. It's now changing behaviour and pushing customers away.
The survey also connects tipping culture to tax and compliance.
H&R Block’s 2025 survey found 84% of Canadians know tips are taxable income, but 47% assume people are not declaring all tips. The evolution from paying/receiving cash tips to digital tips changes how income shows up for tax purposes, especially when tips flow through employers and platform operators.
Digital tipping changes the paper trail. When tips move through a card terminal or POS system and the business pays them out through payroll, the tip can show up like other income on a paycheque, with deductions such as tax, EI, or CPP applied before the employee receives it and then reflected on tax slips. That is different from cash tips left on a table, where the worker has to track and report them. Gig work is different again. Even when an app collects tips and passes them on, gig workers are often treated as self employed, so they still have to report the full amount themselves at tax time.
This is a payments design problem that's now hitting brand trust. The tip prompt is part of the checkout experience, and the checkout experience is increasingly built and configured through payment processors, point of sale providers, and embedded finance stacks. When consumers feel pressured, they blame the merchant, but they also blame the payment flow. The numbers show that tip prompts can create real revenue risk for merchants if 41% of customers are willing to avoid tip pushing businesses.
For fintechs selling point of sale and payment tools, this is an opening to compete on trust and customer experience. Firms that give merchants better controls, clearer disclosure, and safer defaults can reduce backlash while still supporting gratuities where they make sense.
Fintechs that serve gig platforms (or merchants) can help by making tip reporting clearer in worker dashboards and by separating tip flows in a way that matches how income is treated.
Merchants will tune tip prompts more carefully because customer resentment is measurable. Payment platforms will face more pressure to treat tip design as a trust issue, not a digital cash lever. Regulators and tax authorities will face more questions about consistency and clarity as tipping moves further into digital rails.
If 67% of Canadians want tipping abolished and 41% avoid tip pushing businesses, do payment platforms start competing on tip prompt design the same way they compete on fees and checkout conversion?
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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Mar 5, 2026 | NCFA Market Insight | AI And The Future Of Work

Image: Labour market impacts of AI: New measure, early evidence (Anthropic Mar 2026)
On March 5 2026, new Anthropic artificial intelligence labour market impact research | download 17 page PDF offers a more grounded way to think about AI and jobs. Most AI labour studies ask what large language models could do in theory. This one asks what workers actually do with AI now. That sounds like a small change, but it matters. Financial institutions, fintechs, and policymakers need to know where real workflow change starts, not just where capability headlines point.
The paper introduces a new measure called observed exposure. It combines occupational task data, Claude usage data, and earlier research on which tasks language models can theoretically handle. The approach tries to separate technical possibility from real use. That makes this study potentially more useful than other broad forecasts about AI replacing jobs. To be clear, at this point the research doesn't claim mass displacement has arrived. It looks instead for early pressure points that may show up before unemployment spikes.
This report matters because it focuses on real work patterns. The authors use the US O*NET task database, Anthropic Economic Index usage data, and earlier task level exposure estimates to build their measure. They also give more weight to automated and work related uses than to lighter forms of assistance. That helps the study track where AI starts to move from drafting help into actual production work.
That said, the research has real limits, and those limits matter. The usage data comes from Claude, not from the full AI economy. A bank using Microsoft, Google, OpenAI, or internal tools may show a different pattern. The measure also tracks task exposure, not direct job loss. And the authors make clear that adoption still lags capability because of legal controls, software requirements, human review, and workflow friction. That caution strengthens the paper rather than weakening it. It keeps the analysis honest.
The most striking findings is the size of the gap between capability and real usage. In STEM (ie. computer and math) occupations, earlier work suggests language models could theoretically touch 94% of tasks. Anthropic’s observed measure puts current Claude coverage in that category at just 33%. In other words, the technology frontier sits much further ahead than the adoption frontier.
That gap matters for fintech and finance because it points to where the real bottleneck sits. The next productivity jump might not come from a bigger, better, faster or smarter model alone. It might come from firms that redesign workflows, tighten controls, connect tools to internal systems, and build trust in output quality. Which operators can close the adoption gap faster than peers.
The report finds that computer programmers rank as the most exposed occupation, with 74.5% coverage. Customer service representatives follow at 70.1%, and data entry keyers come next at 67.1%. Digital, repeatable, text heavy work moves first.
What stands out for NCFA readers is that this isn't just software engineers. Financial analysts are also among the most exposed occupations in the paper’s wider discussion. That should get the attention of banks, insurers, wealth platforms, lenders, and compliance teams. A lot of value in finance comes from summarizing information, checking documents, explaining options, processing forms, and moving data from one system to another. Those are exactly the kinds of tasks that AI enters early.
Workers in the most exposed occupations earn 47% more on average than workers in the unexposed group. People with graduate degrees make up 17.4% of the most exposed group, compared with 4.5% of the unexposed group.
Early pressure is showing up in better paid, more educated, office based roles. In practice, that means AI may alter the work of analysts, developers, researchers, service teams, and operations professionals before it touches many frontline physical jobs. For financial institutions, this points to a management challenge as much as a technology one. Firms need to rethink role design, supervision, training, and quality control inside knowledge work functions.
The research does not find a growing rise in unemployment for workers in the most exposed occupations since late 2022. That is an important result because it pushes back on louder claims that AI already causes wide labour market damage.
But the report does find an early warning sign. For workers aged 22 to 25, job finding rates into highly exposed occupations fall by about 14% compared with 2022 levels. The authors stress that this result is only barely statistically significant and open to other interpretations. So something to watch and track.
This is how labour market change often starts. Not with mass layoffs. Not with an obvious cliff. It starts when firms stop hiring as many junior people because AI now handles part of the routine work those hires once learned on. That's important for banking, fintech, consulting, and other white collar sectors that depend on apprenticeship style career ladders. If entry points narrow, firms may save money in the short run while weakening their future talent pipeline.
Firms should watch three things closely to better anticipate where the real gap may open between leaders and laggards:
For fintech builders, the market needs tools that help institutions safely plug AI into live work. Audit trails, review controls, workflow routing, structured data extraction, policy checking, and role based permissions. Companies that solve those problems help close the distance between AI capability and actual business use and adoption.
Anthropic’s research is quite useful because it shows where real adoption starts, where the biggest gaps remain, and where the cracks may start to appear and proliferate.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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March 5, 2026 | NCFA Advocacy | Data Governance

Sent by email:
Dear Minister
Power of Data
We (the undersigned – data driven tech and policy experts) very much support the letter of 4 Feb 2026 to you from CCPA – https://www.policyalternatives.ca/news-research/open-letter-to-the-honourable-melanie-joly-minister-responsible-for-statistics-canada/.
We add to that letter the following points:
1. At a time when we need more data, not less, to support evidence-based decision making and community engagement in Canada, the staffing and other cuts already started at StatsCan are misguided. Even if the cuts will “have a ‘low’ or ‘limited’ impact on existing service levels” (a position which is contestable), we echo concerns about the long-term impact on data collection, statistical reliability, and public trust in government institutions.
We ask StatsCan to outline how core programs, release schedules, and quality standards will be maintained. How do we reconcile the cuts with the Digital Research Infrastructure Strategy - https://ised-isde.canada.ca/site/ised/en/programs-and-initiatives/digital-research-infrastructure? Clarifying how “modernization” will offset reductions would strengthen confidence in the transition.
2. Our need for data is magnified by the attacks on data collection in the US, keeping in mind that in the past we have relied on much of that data. The attacks show how quickly statistical capacity can erode and how difficult it is to rebuild.
3. StatsCan plays an important coordinating role in maintaining statistical standards. Although StatsCan is not necessarily the body that should be collecting all the data we need in Canada, we suggest that StatsCan should be the body to oversee an inventory of what Canada does collect (or should be collecting) and to consult on and publish best practices for collection and governance. However, the cuts will clearly constrain an expanded governance role for StatsCan for the foreseeable future.
To provide some examples of data that is sorely needed:
(a) commercialization from Canadian universities, along the lines of the UKRI spinout registry (https://www.ukri.org/news/world-leading-register-of-uk-university-spin-outs-published); *
(b) data on emerging tech commercialization for defence (https://www.nato-pa.int/document/2024-dual-use-technologies-report-baldwin-051-esc and https://www.cigionline.org/publications/intellectual-property-is-economic-and-national-security/); and
(c) data on the outcomes of research spending.
4. Under the World Bank’s Statistical Performance Indicators, Canada’s statistical system ranks highly – https://www.worldbank.org/en/programs/statistical-performance-indicators. While we do not doubt that reform of StatsCan is needed in an increasingly tech-driven economy, wholesale cuts are not the way to do it. Expertise will be lost, collaborative connections across organizations will be lost, mistakes will be made, there will be loss of morale, and direct costs of “redundancy” will be high, when strong statistical capacity is even more essential to support productivity and competitiveness.
5. The timing could not be worse. We are facing enormous challenges, and Canada’s need for reliable data is increasing as the economy evolves. To provide but one example, Canada is increasing defence spending under a new defence industrial strategy and engaging in “nation-building” projects. As noted in the Institute for Research in Public Policy report (https://irpp.org/research-studies/how-industrial-policy-can-strengthen-canada/), these projects must be “accompanied by rigorous evaluation and good governance practices” which can only be effective when Canadian institutions, including StatsCan, collect high quality data and use it to connect action to outcomes.
6. Rebuild or shred? (‘The Doom Loop’ and the future of the global order – https://www.youtube.com/watch?v=6ULm87aidxM). This is a moment for careful planning to ensure institutional capacity is preserved and to plan for rebuilding, not shredding.
Respectfully
Signed
Kyle Briggs - https://www.linkedin.com/in/kyle-briggs/
David Durand – https://www.linkedin.com/in/daviddurandavocat/
Craig Asano, CEO National Crowdfunding & Fintech Assn of Canada - https://ncfacanada.org/
Robin Ford, Robin Ford Consulting - https://www.linkedin.com/in/robinericaford/
Peter Morand, Past President of the Natural Sciences and Engineering Research Council of Canada (NSERC)
Patrick Leblond, CN-Paul M. Tellier Chair on Business and Public Policy, University of Ottawa
José Carlos Marques, Associate Professor, Telfer School of Management, University of Ottawa
* While Canada invests billions in research, we translate very little of the value created into long-term economic and social benefit for Canadians. StatsCan recently attempted to survey Canadian universities on their commercialization activities but was unsuccessful. StatsCan removed the report from the website following complaints that the data was incomplete.
In contrast, the UK recently created a “spin-out register” of all startups commercializing IP created during publicly funded research (https://www.ukri.org/blog/university-spin-out-register-a-step-change-in-insights-for-all/). This register is already providing valuable insights that are helping UK policy makers make better funding decisions.
Canada’s world-class research institutions could contribute far more to Canada’s economy and economic security (https://www.cigionline.org/publications/intellectual-property-is-economic-and-national-security/), but without high-quality data, we struggle to identify and fix the problems.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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