Karsten Wenzlaff, Advisor
August 26th, 2025
Karsten Wenzlaff is a Crowdfunding and Fintech Expert from Germany. He is Secretary-General of Digit[...]
Category Archives: Venture Funding and Building
UK FCA Palantir Trial Puts Regulator Data At Risk
March 23, 2026 | NCFA Insight | AI Governance And Data Sovereignty
Sensitive Regulator Data Meets Foreign AI Access
On March 22, 2026, the Guardian reported that UK Financial Conduct Authority has hired US firm Palantir for a three month trial worth more than £30,000 a week to analyze its intelligence data lake. The reported scope includes highly sensitive material tied to fraud, money laundering, insider trading, case files, suspected wrongdoing reports, and consumer complaints. It's a significant AI governance and privacy risk given that the FCA regulates around 42,000 businesses across the UK's financial ecosystem.
Palantir is a US based data and analytics company that builds software platforms used by governments, intelligence agencies, and financial institutions to organize and analyze large, sensitive datasets. Its systems combine data integration with artificial intelligence and machine learning tools, which allows users to run complex analysis across entire data environments. That capability makes it effective for regulatory and investigative work, and also places it at the centre of ongoing concerns about data access, oversight, and reliance on external vendors in critical public systems.
See: Mills Review Response Targets AI Execution Barriers
The FCA has stated that Palantir acts only as a processor, the data stays hosted in the UK, the data cannot be used to train Palantir systems, encryption keys for the most sensitive files stay with the FCA, and the data must be destroyed at the end of the contract. These are all good safeguards but that doesn't end the debate.
The real question is whether a regulator should give a foreign AI operator working access to one of its most sensitive data environments.
Foreign AI Dependence Raises The Stakes
The FCA wants better tools to detect financial crime across a very large supervisory perimeter. However, the concern is that once a foreign vendor obtains access to a highly sensitive operating environment, the public risk grows beyond just legal ownership of the data. What happens if controls fail beyond what the contract itself governs?
If a system ingests more than expected, if metadata creates a wider intelligence layer than planned, if privileges become too powerful, or if future use expands beyond the original trial, the exposure can widen even when formal safeguards remain in place. While none of this proves failure it does highlight why sensitive AI contracts and said deployments need much closer scrutiny than standard software procurement.
See: Canada Risks Falling Behind as UK Lands AI Megadeals
The trial is short, the weekly cost is disclosed in reporting, the data environment is sensitive, and the FCA says it has placed strict limits on processor role, hosting, training use, encryption control, and deletion. A second report on the FCA Planatir deal indicates the trial is designed to test whether advanced analytics an improve fraud detection, AML/KYC procedures, and insider training within the scope of firms the FCA supervised. But most already concur that AI, if given enough data, can perform small miracles compared to current data tools.
So the harder policy question becomes are the current safeguards enough when the downside of failure is so high, and the data risk in question is a primary financial services regulator, and not a low sensitivity pilot?
Many jurisdictions now rely on a small number of leading foreign AI and cloud firms to quickly integrate, operate, and scale advanced systems. Once workflows, analytics, procurement, and staff capability start to rest on a handful of outside platforms, exiting becomes more difficult due to dependence.
A country can keep data local and still lose practical control if key capability depends on foreign firms for models, compute, software layers, and operational support. This is why the question is bigger than privacy alone. It reaches into resilience, sovereignty, and the future of digital public infrastructure.
Europe And Canada Know This Debate
Europe is addressing this problem with both law and capacity. The EU AI Act already sets binding rules for higher risk AI use, while the EU’s wider strategy ties AI policy to competitiveness and technological sovereignty. The question in Europe is no longer whether to regulate AI. It is how to enforce those rules while building enough domestic capacity to avoid overdependence on foreign providers.
See: Gilles Brassard Turing Award Puts Quantum Security In Focus
Canada isn't yet at Europe’s stage. Ottawa still leans on privacy law, sector rules, and evolving AI policy rather than a fully enacted economy wide AI framework. It is progressing more directly on capability, though. The Canadian Sovereign AI Compute Strategy makes clear that domestic control over compute and data infrastructure is a matter of national security and economic resilience issue, not only an industry growth objective.
That concern is already visible in Canadian data. In Canada AI Strategy Confronts Capital Flight, federal consultation inputs point to risks around sovereign capital, procurement, domestic IP retention, and keeping more AI value inside Canada. Also, the acceleration of AI deployments is exposing AI Governance Gaps that many legal experts have flagged.
Takeaway
The FCA Planatir contact creates at least five questions Canadian policymakers should ask early.
- Is the use case sensitive enough that outside operational access should be tightly limited?
- Are processor and subprocessor rights narrow and auditable?
- Can the system be replaced without major lock in?
- Are impact assessments public and meaningful?
- Does domestic capacity exist for the most sensitive layers?
The AI race isn't just about who deploys and adopts first. It's also about who keeps control over sensitive data, institutional leverage, and critical digital infrastructure while deploying.
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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How Visible Rules Build Trust Faster Than Feature Bloat
March 23, 2026
Image: Pexels/Towfiqu barbhuiya
Most people say they want more features, but what they usually reward is a system they can read. Trust rarely begins with maximum capability. It begins with knowing what the product is doing, what choices are available, and what happens after each action. That matters even more when a product handles money. A clean structure, a visible rule, and feedback that arrives right after the action can build more confidence than a long list of extras that only appear useful on paper.
Researchers increasingly describe digital trust in similar terms. In an open-access survey, transparency is defined as open and clear information about how a service functions, alongside auditability and traceability, which is another way of saying users trust systems they can inspect, rather than merely admire from a distance. That idea helps explain why simpler, more legible products often feel more credible than feature-heavy ones that demand constant interpretation. It also reframes transparency as a working property of the product, not a slogan added after launch.
Visible Rules and Live Feedback
One of the clearest ways to see this principle is inside rule-based games, where trust does not come from vague promises. It comes from stable mechanics, familiar options, and immediate feedback. A practical example is when online players play blackjack with bitcoin. Many sites list multiple versions, including classic blackjack, European blackjack, multi-hand blackjack, and live dealer tables, but the core objective stays steady: make decisions within a known structure and see the outcome without delay.
That consistency matters. When the rule space stays readable, people spend less energy decoding the environment and more energy understanding cause and effect. Seen that way, trust grows because the system behaves the same way twice, then 10 times, then 50 times. If you want to play blackjack with bitcoin after learning the basics, the value is not novelty. It is the chance to observe how confidence forms when actions are bounded, options are clear, and each result connects cleanly to the choice that came before it.
A short video on how memory limits in gaming shaped level design in the past carries the same idea forward because early console designers had so little memory that every tile, sprite, sound, and obstacle had to justify its place. The result was not just smaller worlds. It was clearer communication. Players learned one rule, then saw it repeated and remixed until the system felt readable. That is still a useful model for digital products now. Constraint often builds confidence because it strips away decorative noise and leaves the user with a structure they can understand.
Why Legibility Beats Density
This is where many digital products get the balance wrong. Teams assume trust comes from abundance, so they keep adding tabs, modes, settings, prompts, badges, and layered explanations. Some of those additions may be useful later, but they often arrive before the base logic is clear. The user then has to interpret the product before they can use it. That is a costly first impression. It also creates a subtle mismatch between what the interface promises and what the user can confidently predict, which is often where doubt begins.
Legibility works differently. It reduces the mental workload. It lets people answer a few quiet questions almost immediately: What can I do here? What happens if I do it? What changed because I acted?
When those questions become easy to answer, the product starts to feel honest. It is not trying to wow the user. It is showing its logic through behavior. That honesty compounds over time because repeated clarity is easier to remember than occasional brilliance.
That same theme shows up in broader discussions of transparency in digital entertainment and finance-adjacent systems, where clearer signals and measurable parameters are increasingly treated as part of the experience rather than a technical afterthought.
Trust Grows When Systems Explain Themselves
Visible rules do not mean shallow systems. They mean systems that reveal their logic early enough for users to form a stable mental model. Once that model is in place, depth feels earned instead of confusing. More features can still matter, but only after the foundation is clear. Otherwise, added capability behaves like noise. A product does not need to expose everything at once. It needs to make each next decision understandable enough that the user wants to continue.
See: Good Money Trust Innovation And Canada’s Payments Future
That is why transparent rule sets often earn confidence faster than feature bloat. They reduce doubt at the exact moment doubt is highest. They tell users, in effect, this is how the system works, this is what your options mean, and this is how outcomes connect to inputs. In a crowded market, that kind of clarity is not cosmetic. It is operational. And it is increasingly supported by empirical work showing that greater recommendation-system transparency can raise consumer trust by improving perceived effectiveness and lowering discomfort.
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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How AI is Transforming the Future of Cleaning Industry
March 23, 2026
Introduction
Artificial Intelligence (AI) is transforming the cleaning industry by making it faster, smarter, and more efficient. Traditional cleaning methods that once relied heavily on manual effort are now evolving with automation, smart data, and intelligent systems. From robotic vacuum cleaners that operate independently to AI-powered tools that optimize cleaning schedules and detect high-need areas in real time, cleaning is becoming more precise and results-driven.
As the demand for convenient and effective solutions grows, both homeowners and businesses are shifting toward AI-driven cleaning approaches. While AI improves efficiency and reduces manual effort, human expertise still remains essential for deeper attention, judgment, and handling complex cleaning tasks. The most effective approach combines AI-driven tools with professional cleaning expertise of leading cleaning companies like Mesh Maids to get the highest standards of cleanliness.
In this guide, you will learn how AI works in the cleaning industry, its most practical use cases, and how you can use these innovations to achieve more efficient and effective cleaning outcomes.
How AI Works in the Cleaning Industry
Artificial Intelligence (AI) in the cleaning industry refers to the use of advanced technologies, machine learning algorithms, and automated systems to make cleaning processes more efficient, accurate, and consistent. Instead of relying only on manual effort, AI systems analyze data, identify patterns, and make decisions with minimal human involvement.
These systems continuously collect information from the environment. Over time, they learn from past cleaning activities and adapt to changing conditions. This allows them to improve performance and deliver more accurate results.
For example, AI can:
- Detect high-traffic areas that require frequent cleaning
- Adjust cleaning schedules automatically
- Optimize resource usage like water and electricity
This creates a more proactive and intelligent approach to maintaining cleanliness.
Best Use Cases of AI in the Cleaning Industry
AI is already being used in practical and impactful ways across homes and commercial spaces. Here are some of the most effective applications:
1. Smart Robotic Cleaning
One of the most common uses of AI in cleaning is robotic cleaners. These machines can vacuum, mop, and sanitize spaces without constant human supervision. They use sensors and mapping technology to navigate rooms, avoid obstacles, and clean efficiently.
2. Automated Cleaning Schedules
AI systems can create and manage cleaning schedules based on real-time data. For example, high-traffic areas can be cleaned more frequently, while low-use spaces are cleaned only when necessary. This helps in saving time, effort, and resources.
3. Predictive Maintenance of Cleaning Equipment
AI monitors cleaning equipment and predicts when maintenance is required. This reduces downtime, prevents unexpected failures, and ensures smooth operations.
4. Quality Control and Inspection
AI tools can assess cleaning quality using sensors and data analysis. This ensures consistent standards, especially in commercial environments where hygiene compliance is critical.
5. Personalized Cleaning Solutions
AI learns user preferences over time and adapts cleaning routines accordingly. Whether it's focusing more on kitchens, carpets, or bathrooms, cleaning becomes more customized.
6. Energy and Resource Optimization
AI reduces unnecessary usage of water, electricity, and cleaning supplies by optimizing when and how cleaning is performed.
7. Hygiene Monitoring
In places like hospitals, offices, and public spaces, AI plays a crucial role in maintaining hygiene. It can track high-touch areas, monitor cleanliness levels, and ensure proper sanitization. This helps reduce the spread of germs and creates safer environments.
8. Data-Driven Decision Making
Cleaning companies use AI insights to improve operations, optimize workforce allocation, and enhance service quality.
AI is transforming the cleaning industry by turning traditional methods into smarter, more efficient processes.
Best AI Tools for Home Cleaning
AI-powered tools are making home cleaning more convenient and efficient. Here are some of the most useful options:
Smart Robotic Vacuum Cleaners
These devices use intelligent mapping to clean your home efficiently. They can be scheduled through mobile apps and operate independently, making them ideal for daily maintenance.
AI-Powered Robot Mops
Robot mops handle wet cleaning with precision. They adjust water usage, detect floor types, and avoid carpets, delivering consistent results.
Smart Home Cleaning Assistants
These systems allow you to control cleaning tasks through apps or voice commands. You can schedule cleaning, monitor progress, and customize preferences easily.
Automated Air Purifiers
AI-enabled air purifiers monitor air quality and adjust performance in real time, helping to maintain a healthier indoor environment.
Smart Trash Bins
They are equipped with motion sensors and odor control, these bins improve hygiene and make waste management easier.
UV Sanitization Devices
These devices use ultraviolet light to eliminate bacteria and viruses from surfaces, enhancing hygiene without chemicals.
Smart Cleaning Apps and Platforms
AI-powered apps help manage cleaning routines, track tasks, and create personalized schedules based on your habits.
How to Choose the Right AI Cleaning Tools
If you’re selecting AI tools for your home, consider the following factors:
- Home Size: Larger homes may need advanced mapping features
- Floor Type: Choose tools compatible with your flooring
- Budget: Start with essential tools and upgrade gradually
- Cleaning Needs: Focus on high-priority areas like floors or air quality
Pro Tip: Start with a robotic vacuum or mop, then expand your setup over time for a complete smart cleaning system.
How AI Improves Cleaning Efficiency
AI significantly enhances cleaning efficiency by reducing manual effort and improving accuracy.
Faster Cleaning
AI-powered machines can cover large areas quickly while maintaining high performance, increasing overall productivity.
Consistent Results
AI eliminates inconsistency by following predefined standards. This ensures:
- Uniform cleaning across all areas
- No missed spots
- Reliable results every time
Reduced Human Error
AI relies on data and logic rather than guesswork, minimizing errors and improving accuracy.
Cost Optimization
Although AI tools require an initial investment, they reduce long-term costs by:
- Lowering labor requirements
- Minimizing resource usage
- Increasing productivity
Challenges and Limitations of AI in the Cleaning Industry
While Artificial Intelligence offers many advantages in the cleaning industry, it also comes with certain challenges. Understanding these limitations is important for you to make informed decisions and use AI effectively.
High Initial Investment
AI-powered cleaning tools and systems often require a significant upfront cost. Advanced equipment like robotic cleaners, smart sensors, and data-driven software can be expensive. Although these costs may reduce over time, the initial investment can be a barrier.
Dependence on Technology
AI systems rely heavily on technology to function properly. Any technical issue, software glitch, or system failure can disrupt cleaning operations. This means regular maintenance and updates are necessary to ensure smooth performance.
Limited Judgement
While AI is efficient, it lacks human intuition and judgment. Certain cleaning tasks require attention to detail, decision-making, and adaptability that only experienced professionals can provide. AI may not always handle complex or delicate cleaning situations effectively.
Data Privacy Concerns
AI systems often collect and process data from homes or workplaces, such as usage patterns and environmental information. This can raise concerns about data privacy and security, especially if the information is not properly managed or protected.
Training and Adaptation
Implementing AI requires proper training and adjustment. The cleaning team needs to understand how to use AI tools effectively, which may take time and effort. Without proper training, the benefits of AI may not be fully realized.
Not Suitable for All Environments
AI-powered cleaning systems may not perform well in every setting. Complex layouts, cluttered spaces, or areas requiring detailed manual work can limit the effectiveness of automated tools.
While AI brings innovation and efficiency to the cleaning industry, it is not a complete replacement for human effort. The best results often come from combining AI technology with professional expertise to achieve a balanced and effective cleaning approach.
Why You Still Need Professional Cleaning Services Despite AI
AI has changed the way we clean—but it hasn’t changed what true cleanliness requires. Smart devices can maintain your space, but they don’t understand it.
Cleaning is not just about removing visible dust—it’s about knowing what to clean, how to clean it, and when it needs deeper attention. AI follows patterns, but professionals analyze the environment. Professional cleaning services like Mesh Maids notice buildup before it becomes a problem. With professional expertise they treat different surfaces with the right methods.
See: CES 2026 Shows How Global Platforms Set AI Terms
With Mesh Maids, you’re not just getting a cleaner home—you’re getting a thoughtful, detail-driven approach with expertise. From tackling neglected areas to maintaining a spotless space, our team brings a level of care that goes beyond automation.
Conclusion
Artificial Intelligence is reshaping the cleaning industry in a practical and meaningful way. From smarter tools and automated systems to data-driven decisions, AI is helping in making cleaning faster, more efficient, and more consistent.
This means you will get a cleaner and healthier living space with less time spent on daily chores. It also opens the door to better service delivery, improved productivity, and stronger customer satisfaction for professional cleaning companies.
As AI continues to evolve, its role in the cleaning industry will only grow stronger. The key is to use this technology wisely—combining it with human expertise to achieve the best possible results. In the end, AI is not just changing how cleaning is done; it is setting a new standard for what clean truly means.
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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US AI Framework Targets To Limit State Rule
Mar 23, 2026 | NCFA Insight | AI Policy And Regulation
Washington Signal One National Approach to AI
On Mar 20 2026, the White House released a national AI policy framework and legislative recommendations that asks Congress to build a single federal approach to AI and limit conflicting state laws. Washington looks to reduce regulatory fragmentation before state level AI rules harden into a patchwork. The framework isn't law but a blueprint for Congress to show where U.S. AI policy is heading and what type of rules the White House thinks are needed to support large scale use of artificial intelligence across the economy.
Federal Preemption Sits At The Center
The document argues that state by state AI rules can impose uneven burdens on firms trying to build and deploy AI systems nationally. The White House position is that Congress should set the main framework and stop conflicting state rules from slowing deployment. At this point, it's less about creating a new AI regulator and more about stopping fifty different rulebooks from becoming the default U.S. model.
The framework highlights six areas: child protection, energy and electricity costs, intellectual property, free expression, public education and workforce readiness, and maintaining U.S. leadership in AI.
Policymakers want to lower friction for deployment while demonstrating that safety and public concerns are still being addressed. It's a delicate balance because it tells the market what the White House sees as the main tradeoff. The focus is not on building a heavy new AI rule set, but rather on enabling scale, lowering infrastructure bottlenecks, and avoiding fragmented oversight.
See: Pro Human AI Declaration Gains Backing Across Sectors
AI is already proliferating across lending, fraud detection, compliance, payments, customer operations, and model driven decisioning. A patchwork of state by state compliance would raise cost, slow deployment, and make national rollout harder for both incumbents and startups.
A single federal framework wouldn't solve every issue. Questions around accountability, model assurance, liability, and sector specific supervision would still remain. But it would remove a major barrier by making it easier to roll out AI across the United States.
How This Differs From The UK And Canada
The U.S. approach is mainly about fragmentation. The White House wants one national frame instead of competing state level rules.
The UK conversation is more operational. The FCA’s Mills Review asks how AI could impact retail financial services through 2030 and beyond. Industry responses focus more directly on deployment barriers inside finance, including data access, Digital ID, payments infrastructure, and rulebook friction.
Canada is taking a broader path. The federal government’s AI strategy process gathered input from more than 11,000 Canadians and 28 task force members, with stronger emphasis on trust, safety, responsible adoption, and national direction. NCFA has already flagged the execution risk in this approach in its analysis of Canada’s AI strategy and capital flight risk.
The difference is important. The U.S. is trying to stop fragmentation. The UK is pressing on execution barriers. Canada is still nuturing national direction. Each approach points to a different policy priority and will result in a different speed of deployment and potential competitive advantage (or disadvantage).
See: AI Ethics, State Power, And The Fight Over RedLines
Jurisdictions that reduce friction and create usable operating environments will attract more investment, deployment, and talent. Jurisdictions that let regulatory complexity pile up will throttle adoption even when the technology is ready.
Takeaway
The White House's AI policy framework makes the federal direction clearer. The U.S. is trying to stop state level fragmentation before it becomes the default AI regime. It's important for fintechs and financial services because the level of scale, cost, and deployment speed depends heavily on whether one federal rulebook replaces fifty competing ones.
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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NCFA Weekly Fintech Intelligence Mar 14-20, 2026
March 20, 2026 | NCFA Fintech Whisperer Weekly Intelligence | Digital Assets Blockchain And Tokenization, Capital Markets And Market Infrastructure, Regulation And Policy, Payments And Market Infrastructure
Image: Freepik
This live weekly NCFA intelligence page tracks financial technology developments that significantly affect how fintechs build, sell, raise capital, and operate under scrutiny. Coverage prioritizes Canada and includes global events that directly influence competitive conditions, market access, and execution realities across fintech sectors. This page will be updated throughout the week with market movers in a live format and then each week we'll close the prior week's contents in prep for the upcoming week, and continue on a rolling basis. (Missed prior week's Fintech Whisperer? (December 6-12, 2025, December 13-19, 2025, January 1-9, 2026, January 10-16, 2026, January 17-23, 2026, January 24-30, 2026, January 31-February 6, 2026, February 7-13, 2026, February 14-20, 2026, February 21-27, 2026, February 28-March 6, 2026, March 7-13, 2026).
Weekly Fintech Market Intelligence Mar 14 - 20, 2026
Digital Assets
CIRO Adds Newton Crypto Ltd. As A New Member
Mar 20, 2026, Canada
- CIRO publishes a member bulletin that lists Newton Crypto Ltd. as a new member.
- The bulletin provides formal notice that Newton has received CIRO membership.
- This expands the set of firms operating under CIRO oversight in the Canadian crypto dealer landscape.
This adds a new regulated counterparty node for banks, payment partners, and fintech vendors that use CIRO membership as a gating factor for onboarding, integrations, and supervised operating scope.
Apex And Coinbase Launch Tokenized Bitcoin Fund On Base
Mar 19, 2026, Global
- Apex Group and Coinbase Asset Management launched a tokenized share class of a Bitcoin yield fund on Base.
- The structure uses ERC-3643 with identity and eligibility rules enforced at the token level.
- Investor onboarding runs through a Tokeny portal, and token records remain aligned with the fund’s NAV.
- The product is offered to institutional and accredited investors.
This puts fund distribution onchain with rules built into the asset. Transfers can enforce who can hold and trade without separate manual checks. That changes how funds issue, manage investors, and handle transfers. It points to tokenized fund infrastructure moving into live use, not pilots.
CIRO Tests Lower Margin For Stablecoin Inventory At Three Platforms
Mar 19, 2026, Canada
- CIRO approved three InnovateSafe applications to test reduced margin rates for firm inventory positions in certain fiat backed stablecoins.
- The test applies to NDAX, Shakepay, and Wealthsimple Investments.
- CIRO says the pilot uses a tiered margin approach with enhanced controls, monitoring, reporting, and conservative concentration limits.
- The test applies only to firm inventory positions and will run for one year unless modified, suspended, or terminated earlier.
This affects crypto trading platforms, market makers, treasury teams, and regulators watching stablecoin market structure in Canada. Lower margin on eligible inventory can improve capital efficiency and balance sheet use, but only inside a tighter control framework. It means regulated treatment of stablecoins is moving deeper into prudential design, not just disclosure and registration.
S&P 500 Licensed For Perpetual Trading On Hyperliquid
Mar 18, 2026, United States
- S&P Dow Jones Indices licensed the S&P 500 to Trade[XYZ] for what it describes as the first officially licensed perpetual derivative tied to the benchmark.
- The product launches on Hyperliquid and gives eligible non US investors 24/7 access to leveraged long or short exposure without fixed expiry.
- S&P says the move extends the S&P 500 liquidity ecosystem on chain, putting a core equity benchmark onto a crypto native trading venue.
- The structure follows crypto perpetual markets while using S&P index data, linking traditional benchmark exposure to on chain trading rails.
A core global index now trades outside exchange hours. Price formation can start on crypto venues before futures markets reopen, which puts pressure on where liquidity shows up first. If activity builds on chain, traditional venues risk reacting instead of leading. For brokerages, exchanges, and market infrastructure providers, this is not theoretical. Firms need to decide whether to support 24/7 access, how to manage risk when markets never close, and how to compete with venues that remove time and geographic limits.
SEC And CFTC Publish Crypto Asset Interpretation
Mar 17, 2026, United States
- The SEC published an Interpretive Release on how federal securities laws apply to certain crypto assets and crypto asset transactions, and the CFTC joined the interpretation.
- The release sets out a token taxonomy covering digital commodities, digital collectibles, digital tools, stablecoins, and digital securities.
- The SEC says the interpretation explains how a non security crypto asset may become subject to, and later cease to be subject to, an investment contract.
- The release also addresses airdrops, protocol mining, protocol staking, and the wrapping of a non security crypto asset. The SEC also published a fact sheet summarizing the interpretation.
Crypto issuers, exchanges, custodians, brokers, investors, and token builders now have a clearer US reference point for token design, disclosures, and jurisdiction planning. The practical implication is significant. Firms exposed to staking, airdrops, wrapped assets, stablecoins, or token distribution models can reassess compliance, product structure, and market access strategy with more precision across SEC and CFTC lines.
Banking
US Banking Agencies Move To Modernize Capital Rules
Mar 19, 2026, United States
- The Federal Reserve, FDIC, and OCC requested comment on three proposals to modernize the regulatory capital framework for banks of all sizes.
- The agencies say the proposals would streamline capital requirements and better align regulatory capital with risk.
- The stated goal is to maintain the safety and soundness of the banking system while updating the capital framework.
This is for banks, lenders, treasury teams, and fintechs that rely on bank balance sheets and bank distribution. Capital rules affect lending capacity, pricing, and risk appetite. A lighter or more targeted framework can change how banks allocate capital and where they are willing to compete.
Close Brothers Speeds Cost Cuts And AI Rollout As Banking Pressure Builds
Mar 17, 2026, United Kingdom
- Close Brothers says it is accelerating its cost program, with annualized savings of about £25 million in FY 2026 and £60 million by the end of FY 2027.
- The bank says the program includes outsourcing, offshoring, reducing office space, and increasing the use of AI and automation.
- Reuters reports the plan includes about 600 job cuts by 2027, roughly 20% of staff.
- Close Brothers reported a statutory pre tax operating loss of £65.5 million for the half year and increased its motor finance commission provision to £300 million.
Banks facing margin pressure, conduct costs, and weak returns are under more pressure to lower their operating base faster. The practical implication for lenders, fintechs, and banking vendors is that AI and automation are moving from pilot projects into cost and staffing decisions. Firms that can automate servicing, operations, and control workflows without weakening customer outcomes or compliance will be in a stronger position.
Regulation And Policy
FCA Updates Regulatory Priorities Reports And Replaces Portfolio Letters
Mar 19, 2026, United Kingdom
- The FCA states it is introducing 9 annual Regulatory Priorities reports to replace portfolio letters.
- The page shows publication dates across sectors including wholesale markets dated Mar 19, 2026, and a payments report dated March 2026.
- The FCA notes it does not publish a cryptoasset sector priorities report because a new UK cryptoasset regime is scheduled for October 2027.
This gives UK facing fintechs and suppliers a cleaner map of where supervisors focus and where firms should spend compliance and product time. Payments, retail banking, consumer finance, and wholesale market firms can now align internal control roadmaps to sector specific priorities instead of broad portfolio letters, which tightens how boards and senior managers justify investment decisions.
Canada Flags Weak Procurement Competition And Paths To Improve Access
Mar 17, 2026, Canada
- A federal report from the Office of the Procurement Ombud examines two issues that weaken competition: procurements that receive only one bid and solicitations that are cancelled before award.
- Across 17 procurement practice reviews from 2018 to 2023, only one bid was received in 53 of 180 open processes and 106 of 303 limited competitive processes.
- The report points to restrictive criteria, misaligned evaluation methods, complex rules, and poorly defined requirements as key causes that limit supplier participation.
- Recommendations include better requirement design, stronger justification for cancellations, potential payment of bid costs, and broader use of anti collusion certification.
Federal procurement remains difficult for new entrants to access, with complexity and restrictive design favouring repeat suppliers. At the same time, the report outlines clear changes that could open participation, improve competition, and expand access for fintech, govtech, and smaller vendors seeking to sell into government.
Payments And Market Infrastructure
China Expands Bank Access To Digital Yuan
Mar 20, 2026, China
- Reuters reports China plans to add 12 more banks to its digital yuan program, on top of the 10 banks already authorized.
- The new group is expected to include joint-stock and city commercial banks such as Shanghai Pudong Development Bank, China Everbright Bank, and Bank of Ningbo.
- Reuters says digital yuan transactions reached a cumulative 16.7 trillion yuan as of last November, versus 128 trillion yuan in total payments transacted in 2025 alone. The report says China continues to pair e-CNY expansion with a ban on stablecoins and broader crackdown on virtual currencies.
China is widening the distribution base for state digital money inside the banking system. Analysts see the bigger role in cross-border settlement and in building a payments channel that's outside dollar-based infrastructure such as SWIFT. China is pushing public digital money deeper into bank distribution while closing space for private stablecoin models.
Payments Canada Approves Meridian As First New Provincial Credit Union Member
Mar 19, 2026, Canada
- Meridian Credit Union (Ontario's largest credit union) becomes a Payments Canada member as the first credit union to obtain membership following expanded eligibility requirements.
- The approval ties to expanded membership eligibility under amendments to the Canadian Payments Act.
- In January 2026, Payments Canada Admitted Five New Payment Service Providers, including Wise Payments Canada, Float, KOHO, Paramount Commerce, and Brim Financial.
This expands direct access for credit unions that want to build or buy modern payment capabilities. Credit unions, processors, and fintech partners can now plan for real system participation, not just eligibility on paper.
Thunes Connects Stablecoin Payouts To Banks Through Swift
Mar 17, 2026, Global
- Thunes says banks can now send payouts to stablecoin wallets through existing Swift connectivity.
- The company says this opens access for the 11,500 institutions on the Swift network to more than 500 million stablecoin wallets worldwide.
- The service supports USDC and USDT and enables real-time payouts in more than 140 countries.
- Thunes says the rollout requires no additional integration and builds on its Pay-to-Stablecoin-Wallets product launched in October 2025.
This is for banks, cross-border payment firms, remittance providers, treasury teams, and stablecoin infrastructure players. Stablecoin payouts are moving closer to standard bank payment flows instead of sitting outside them as a separate integration project. That lowers friction for bank adoption and puts more pressure on legacy cross-border payout models.
Mastercard Acquires BVNK To Connect Fiat And Stablecoin Rails
Mar 17, 2026, Global
- Mastercard agreed to acquire stablecoin infrastructure firm BVNK to connect on chain payments with its global payments network.
- The company pointed to about $350B in digital currency payment volume in 2025 as demand grows for hybrid fiat and stablecoin settlement.
- The deal focuses on cross border payments, payouts, and enterprise treasury use cases that combine bank rails with digital asset settlement.
Mastercard is building direct control over how funds move between bank accounts and stablecoin systems. That changes routing, pricing, and who captures value in cross border and treasury flows. For fintechs, payment products will increasingly need to support both fiat and digital settlement paths in the same workflow. For banks, this puts more pressure on correspondent banking and other legacy cross border revenue lines.
Capital Markets And Funding
CIRO Launches Disgorgement Distribution Program To Return Funds To Harmed Investors
Mar 19, 2026, Canada
- Effective date is April 1, 2026.
- The program enables distribution of funds collected under disgorgement orders to investors financially harmed by registrant misconduct.
- Administrative Bulletin 26 0062 sets out program scope and the claims based process, with supporting policy and procedures in appendices program policy and procedures.
This changes how investor harm connects to enforcement outcomes. Dealers, registrants, and their vendors now need tighter client records and cleaner evidence trails because the process depends on what harmed investors can prove and what firms can produce quickly and accurately when claims arrive.
CSA Adopts Semi Annual Reporting Pilot For Venture Issers
Mar 19, 2026, Canada
- The CSA allows eligible TSXV and CSE issuers to report financials semi annually instead of quarterly on a voluntary basis.
- The pilot removes first and third quarter reporting requirements under National Instrument 51-102 for participating issuers.
- The CSA states the goal is to reduce compliance burden while maintaining investor protection.
- The results will inform future rule changes for broader adoption.
This lowers reporting cost and workload for smaller public companies. It changes how often new financial data enters the market. Investors and data platforms will have less frequent updates. For issuers, this improves the economics of staying public. If adopted more widely, it moves Canada toward a lighter reporting model for venture markets.
EU Industry Calls For Changes To DLT Pilot Regime
Mar 19, 2026, European Union
- An industry group coordinated by the European Digital Finance Association submitted an open letter to the European Commission calling for changes to the EU DLT Pilot Regime.
- The letter highlights constraints limiting scale, including participation thresholds, asset scope limits, and operational frictions between DLT and traditional market infrastructure.
- The proposal calls for expanded scope, interoperability requirements, and clearer regulatory treatment to support tokenized securities markets.
Industry participants are pushing to remove limits that keep tokenized market infrastructure in pilot mode. That pressure targets how quickly the EU can move from controlled testing toward scalable digital asset markets.
SEC Approves Nasdaq Rule For Tokenized Securities Trading
Mar 18, 2026, United States
- The SEC approved a Nasdaq rule change to enable trading of securities on the exchange in tokenized form during DTC’s tokenization pilot.
- Eligible participants can trade tokenized versions of certain equity securities and exchange traded products, including Russell 1000 securities and ETFs that track major indices such as the S&P 500 and Nasdaq 100.
- Tokenized shares will trade on the same order book as traditional shares, with the same execution priority, the same trading symbol and CUSIP, and the same shareholder rights and privileges.
- Nasdaq says existing order types, routing strategies, connectivity, surveillance, fee schedules, and T+1 settlement will continue to apply, with tokenization handled through post trade instructions to DTC.
Tokenized securities into the core of exchange trading. They will trade the same way as regular shares, on the same book, with the same symbol and rules. No separate venue, no parallel system. It removes a major barrier with tokenization now aligned with the same clearing, settlement, and surveillance systems as the rest of the market.
Upstart Secures A $1B Forward Flow Loan Purchase Commitment
Mar 17, 2026, United States
- Eltura Capital Management, Aperture Investors, and co investors agree to purchase up to $1B of consumer loans originated through the Upstart platform.
- The agreement runs for 12 months and builds on an existing relationship.
- View the release. Upstart Forward flow announcement
A forward flow commitment supports predictable loan takeout capacity, which can stabilize origination volume when bank balance sheets tighten or pricing changes.
SEC Prepares Proposal To End Quarterly Reporting Requirement
Mar 16, 2026, United States
- The SEC is preparing a proposal that would remove the requirement for public companies to report earnings every quarter.
- The change would allow companies to report financial results every six months instead of every 90 days.
- The proposal has not been formally released and the SEC has not issued an official statement.
- The report is based on coverage by the Wall Street Journal and confirmed by Reuters.
Public companies, investors, analysts, and fintech platforms that rely on earnings data will face longer gaps between official disclosures. Less frequent reporting reduces the flow of standardized financial data into the market. Firms that can generate alternative data, continuous signals, and independent performance insight will have an advantage as reliance on scheduled earnings reports declines.
PhonePe Pauses IPO As Market Volatility Hits Fintech Exit Timing
Mar 16, 2026, India
- Reuters reports Walmart backed PhonePe paused its IPO plans on Mar 16 as geopolitical tensions and market volatility hit investor sentiment.
- Reuters says the Indian fintech had targeted a valuation of about $9 billion to $10.5 billion.
- In a company statement carried by local market coverage, CEO Sameer Nigam said PhonePe remains committed to a public listing in India and will resume the process when global capital markets stabilize.
When one of India's largest fintech payments company pauses an IPO, it tells founders, investors, and late stage boards that the public market window remains fragile. That affects valuation expectations, liquidity planning, and timing for other fintech listings.
Conclusion
NCFA offers various curated resources to help founders and investors stay current on developments that impact fintech markets, subscribe to NCFA weekly newsletter updates, view a rundown of current fintech news and insights, or dive into the latest fintech industry research.
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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Gilles Brassard Turing Award Puts Quantum Security In Focus
Mar 20, 2026 | NCFA Market Activity | Quantum Security And Digital Finance
Image: Pixabay/geralt
Quantum Standards and Timelines Now Drive Financial Security Changes
On Mar 18, 2026, the 2025 ACM A.M. Turing Award recognized Gilles Brassard and Charles H. Bennett for foundational work in quantum information science, including the development of quantum cryptography. The award carries a $1 million prize and marks one of the highest global honours in computing.
See: Google’s Willow Quantum Chip Breakthrough
Brassard’s work established early methods for secure communication using quantum mechanics, a field now directly tied to the future of encryption. While he didn't develop today’s post quantum standards, his research helped define how information can be secured against quantum-enabled attacks. That body of work went from advanced research to execution in August 2024 when NIST finalized the first post quantum cryptography standards for encryption and digital signatures used across financial systems.
As ACM President Yannis Ioannidis stated:
“Their work is an important foundation for the field of quantum computing and has fundamentally changed how we process, transmit, and secure information.”
Post Quantum Cryptography Enters Implementation
Post quantum cryptography (PQC) refers to new encryption methods designed to remain secure even if future quantum computers can break today’s widely used systems today, such as RSA and elliptic curve cryptography that currently protect payments, digital identity, secure messaging, APIs, and financial data.
On Aug 13, 2024, NIST finalized three post quantum cryptography standards and announced that organizations should begin transitioning to them as soon as possible. NIST states these standards support encryption and digital signatures used to secure electronic information, including financial transactions and sensitive data.
NIST also states that no one knows exactly when a cryptographically relevant quantum computer will arrive, but some experts estimate it could be possible in less than 10 years. That uncertainty increases the risk because encrypted data can be collected today and targeted for future decryption under the harvest now, decrypt later threat model.
Canada has already set execution timelines. The Canadian roadmap for post quantum cryptography migration requires departments to begin planning in April 2026, report progress annually, transition high priority systems by the end of 2031, and complete remaining migration by the end of 2035. Canada’s national strategy for quantum communication and cryptography states that advances in quantum computing could undermine current encryption and threaten digital systems and data security.
What It Means for Fintechs
For financial services, encryption now affects what gets built and what gets bought. Payments, identity, onboarding, APIs, messaging, custody, and long term data all rely on encryption that may need to be replaced or upgraded.
Quantum also reaches into blockchain based finance like stablecoins, tokenized deposits, wallet infrastructure, custody controls, and smart contract connected payment flows all depend on digital signatures and key management. NCFA’s earlier coverage of quantum safe stablecoins points to a market approaching US$250 billion and highlights how quantum safe controls are already being added to stablecoin settlement systems.
See: Photonic $180M Financing Puts Quantum In Focus in 2026
Buyers are starting to ask direct questions. Where is encryption used in the product. Which parts rely on current standards. What is the plan to upgrade. These questions and decisions are part of core financial workflows now and show up across payments messaging, identity systems, API access, document signing, custody, and stored data.
Vendors that can clearly show where encryption sits in their systems and how they plan to upgrade it will have an advantage as requirements tighten.
In Conclusion
NIST standards are finalized and Canada has set migration timelines starting in April 2026, with high priority systems due by the end of 2031 and full migration by the end of 2035. That puts a clock on encryption used across payments, identity, APIs, messaging, custody, and long term data.
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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Mills Review Response Targets AI Execution Barriers
Mar 19, 2026 | NCFA Feature | AI Finance Policy
UK Industry Sets Clear AI Policy Priorities
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.
What The Industry Is Asking For
- Keep AI regulation principles based and outcomes focused. The point is to avoid rigid rules that will age badly as models and tools change.
- Give firms clearer examples of good and poor practice. High level principles are not enough when firms need to deploy AI in regulated settings.
- Clarify assurance requirements for third party AI tools and for senior managers responsible for them. Most firms will not build every model in house, so external model use needs a clearer control standard.
- Review the rulebook and remove blockers in high value AI use cases. The paper points to debt advice, affordability in lending, agentic payments, and wallets.
- Prevent gatekeepers from controlling access to models, data, or agents, especially in payments. If a small number of providers control that layer, they can control distribution.
- Move Open Finance, digital assets, and Digital ID forward at the same pace. AI in finance depends on trusted data, verified identity, and usable infrastructure.
- Back this with a strategy to make the UK the world leader in AI adoption in financial services by 2030.
Why These Asks Matter
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.
See: Pro Human AI Declaration Gains Backing Across Sectors
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.
- One embedded finance platform says it's facilitated more than £7 billion in SME revenue worldwide and is twice as likely to approve financing for female-owned businesses compared with the UK average.
- A core banking technology provider says it was last valued at $2.7 billion and employs more than 500 people globally.
- The submission also notes that algorithmic trading accounts for roughly 60% to 75% of activity across major U.S., European, and Asian markets.
- It adds that the RegTech market could reach $88 billion by 2032.
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.
See: India’s AI Declaration Pulls In BRICS And Western Powers
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.
Why This Matters For Canada
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.
See: Google Signs EU AI Code Despite Competition Warnings
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.
Takeaway
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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