Karsten Wenzlaff, Advisor
August 26th, 2025
Aug 6, 2026 | NCFA Insight | Artificial Intelligence And Data, Risk Compliance And Regtech, Capital Markets And Market Infrastructure

On July 29, 2026, a shareholder filed a Rackspace securities complaint alleging that the cloud company failed to explain how its AI plans were affecting capacity, spending and revenue. The complaint says Rackspace reaffirmed its 2026 guidance in May, then cut expected annual revenue by US$150 million in July. It also alleges that resources moved away from the more profitable Private Cloud business while margins absorbed restructuring and AI investment.
Those claims haven't been proven, and the court hasn't decided whether Rackspace or its directors did anything wrong. The filing still raises a useful question. Once an AI plan changes how a company spends, allocates computing capacity or describes future results, the board needs a clear view of the economics behind it. Investors may need that view too.
Rackspace isn't an isolated case. Recent complaints against Oracle, Microsoft, ZoomInfo and Upstart use different facts, but each asks whether the company story kept pace with what was happening inside the business.
An Oracle shareholder complaint alleges that the company understated the financing pressure created by its AI infrastructure build. Oracle later projected US$50 billion of capital spending for fiscal 2026, US$15 billion above its September 2025 projection, while reporting more than US$10 billion of negative free cash flow. The complaint focuses on whether investors received enough information about the scale, financing and cash impact.
A Microsoft securities complaint focuses on a different pressure point. The plaintiffs allege that Microsoft overstated Copilot adoption and didn't adequately explain that AI products were competing with Azure customers for computing capacity. Microsoft reported US$72.4 billion of capital spending in the first half of its fiscal year, almost as much as it spent in the prior full year. The unresolved issue is whether product demand, available capacity and investor disclosure remained aligned as the build accelerated.
ZoomInfo adds the risk of AI weakening the business that funds the transition. Its June 2026 complaint alleges that customers were using internal AI tools and moving away from seat-based subscriptions toward consumption pricing. The plaintiffs argue that management failed to explain how AI was changing demand for the existing model.
None of these cases proves misconduct. Shareholder complaints present company events through the plaintiff's theory, and a falling share price does not establish that earlier disclosure was misleading. The filings are interesting because they show where disputes are forming. Investors are asking what was spent, what reached customers, what revenue followed and what the rest of the business gave up.
A board cannot judge an AI strategy from product demos or spending totals alone. It needs to know what the money produced, such as more computing capacity, products in market, paying users, lower costs, higher revenue or better service.
Usage numbers can hide as much as they reveal. An enabled account may never use the product. An active user may not pay. Even paid adoption says little about retention, margins or the cost of serving that customer.
Savings claims need the same scrutiny. AI may reduce work in one team while increasing cloud costs, review time or customer complaints elsewhere. Early pilots do not need to make money immediately, but management should know what would justify further investment and what would cause it to pull back.
Boards also need to see what the AI plan is displacing. Computing capacity assigned to one product cannot serve another workload. Engineers moved to a new platform are no longer maintaining something else. A sales team promoting an AI add-on may spend less time selling the core product. Those choices may be reasonable, but the trade-offs should be clear before a profitable business starts carrying an open-ended investment.
Directors do not need to become model engineers but they do need enough operating information to test whether the plan is working. That includes supplier commitments, capacity constraints, effects on established products and a clear explanation when results fall short.
The SEC Investor Advisory Committee's AI disclosure recommendation follows the same logic. It calls on issuers to define what they mean by AI, explain how the board oversees it and disclose material effects on operations and customers. It also argues that companies can provide much of this information through existing disclosure requirements. The recommendation comes from an SEC advisory committee. It is not an SEC rule.
For banks and fintechs, weak AI performance can reach customers before it appears in an earnings release. A model may change who receives credit, how a transaction is flagged or what recommendation reaches an investor. It can also create more manual review, complaints and losses when performance moves in the wrong direction.
The Upstart securities complaint brings that issue into automated lending. Plaintiffs allege that a model update reacted too strongly to negative economic signals, reducing loan approvals and conversions while affecting revenue and guidance. The filing shows why boards need model performance connected to approval rates, customer outcomes and financial forecasts.
That connection becomes harder when a firm depends on an outside cloud, model or data provider. A vendor change can alter cost or performance. An outage can interrupt a regulated process. Concentration can leave the company without a workable alternative. NCFA's analysis of feedback loops behind AI failures shows how model output, human responses and operating data can reinforce an error before the full effect is visible.
The Financial Stability Board's 2026 consultation proposes 12 practices covering governance, the AI lifecycle, cyber risk and outside providers. It is not a binding international standard. In Canada, OSFI's Guideline E-23 on model risk takes effect on May 1, 2027 for federally regulated financial institutions. It expects clear ownership, model inventories, monitoring and communication to senior management and boards.
AI is already moving into governed financial workflows. Board reporting has to keep pace. Spending and adoption belong beside model exceptions, overrides, complaints and losses. Otherwise, financial results may arrive after the operating warning signs.
Canadian boards do not need an AI-specific statute before asking these questions. Under the Canada Business Corporations Act, directors of federal corporations must act honestly and in good faith and exercise the care, diligence and skill of a reasonably prudent person.
Canadian continuous-disclosure requirements separately require reporting issuers to publish financial statements, management's discussion and analysis, material-change reports and other prescribed information. The exact obligation depends on the issuer and the facts.
AI is already appearing in Canadian filings. The Ontario Securities Commission reviewed 225 companies in the S&P/TSX Composite and found that 72 issuers mentioned AI in 2024 annual management discussion and analysis. That is 32% of the sample. The OSC described the work as a proof of concept and did not assess whether any issuer's disclosure was adequate.
Simply mentioning AI more often will not make disclosure more useful. Investors need to know how much the company is spending, what is already in use, how customers are responding and what has changed since the last report. When AI affects capacity, margins, revenue or a regulated customer decision, a generic risk paragraph is not enough.
Canada may get more immediate value from clearer reporting on AI costs, live deployment, board oversight and business results. A separate AI disclosure rule is not the only option. Existing board duties and continuous-disclosure requirements already give companies a reason to make sure their public statements match what management is seeing inside the business.
Poor AI performance is not automatically a governance failure or securities violation. A board can approve a reasonable investment that does not work. Litigation can also overstate what directors could have known at the time. The difficult question is whether the company’s internal numbers had changed while its public story stayed the same.
When an AI plan changes spending, capacity or revenue, what should the board see before investors hear the same growth story again?
AI spending becomes a board issue when it is material to strategy, capital commitments, margins, capacity, customer outcomes or regulated operations.
No. The complaints contain allegations that have not been proven, and courts have not decided the merits. They identify the spending, adoption, capacity and business-model questions investors are asking.
The board should see enough financial, operating, customer and model-performance information to challenge the investment and recognize when results depart from the approved plan.
Canada does not have a single AI-specific securities disclosure rule for public issuers. Existing corporate duties and securities requirements can still apply when AI costs, risks or operating effects become material.
An AI model can affect credit, fraud controls, suitability, customer service and complaints before its full financial effect appears in company results.
This article is provided for informational purposes and does not constitute investment, financial or legal advice. Lawsuits discussed contain allegations that have not been proven in court. Recommendations, consultations and regulatory requirements may change.
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](http://www.ncfacanada.org)
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We're opening up more and more APIs to partners, fintech services, and client applications. The only question is whether we're confident these same APIs aren't opening up new paths for attackers.
Just a few years ago, a bank mostly dealt with its own systems. A customer would log into the app, check their balance, make a transfer. The whole journey stayed inside the perimeter of a single organization.
Today, one customer might simultaneously use a mobile banking app, a budgeting service, an accounting platform, a payment provider, and an AI assistant that analyzes their spending. All of these services exchange data through APIs - interfaces that let different systems talk to each other according to a set of established rules.
Open Banking isn't just a regulatory requirement or a new integration channel - it's a shift in the trust model itself. A bank used to be responsible for security within its own infrastructure. Now it hands off part of its data to dozens of external services, and those services, in turn, rely on the bank. The more participants in the ecosystem, the more points there are where trust is either reaffirmed or cracked, every single day.
Attackers are less and less interested in finding a weak spot inside any one bank. Today, hackers target the interaction between systems itself. The longer the chain - bank, fintech, payment hub, partner app - the more places there are for something to go wrong.
Common examples include:
An API can perform flawlessly on the functional side - fast, stable, no errors in the logs - and still carry a critical vulnerability. Functional correctness and cybersecurity don't always go together.
Banks and fintech companies generally don't neglect API security. They go through certifications, run automated scans, do code reviews and QA. But none of these tools answer the one question that matters most: can this specific API's logic be bypassed in a way its developer never anticipated? Scanning catches known vulnerability patterns; code review and QA confirm the code does what it was built to do. Neither one thinks like an attacker who isn't hunting for a bug in the code, but for a logical gap in how the API interacts with other systems.
That's why most attacks on financial APIs today aren't about technical mistakes - they're about logic: the sequence of actions, the boundaries of authority, the trust placed in data coming from the client. It's also why modern Cybersecurity Solutions for Fintech increasingly go beyond formal compliance with standards, testing real-world abuse scenarios at the points where multiple systems meet.

Here's a short checklist for reviewing every external API in your ecosystem:
If you don't have a confident answer to any of these, that's reason enough to look closer.
It's worth telling apart three things that often get lumped together. Vulnerability scanning looks for known vulnerabilities by signature, catching familiar vulnerability classes, common misconfigurations, and known dangerous patterns. Automated testing checks whether the code performs its intended functions correctly. Separate from both is API Penetration Testing (https://datami.ee/services/pentest/api-penetration-testing/) - manual testing in which a specialist plays the role of a real attacker: combining requests, tweaking parameters, hunting for unusual sequences of actions that a scanner, in most cases, won't flag as anomalous, because each individual request looks legitimate on its own.
It's also best if this kind of testing is handled by an external team. In-house specialists tend to know their own API inside and out - and that's precisely what makes it hard for them to spot an unconventional abuse scenario, since day-to-day work with a system's logic doesn't train you to look at it through the eyes of someone deliberately trying to break it. External specialists bring experience from other architectures and payment integrations, so they're more likely to catch the gaps a team had written off as unimportant.
A bank can offer the most convenient digital service and the best partner API on the market. But if even one partner or customer stops trusting the security of the data exchange, the benefits of Open Banking vanish almost instantly. Trust here isn't a bonus feature - it's the baseline condition, and without it the whole structure loses its meaning.
That's why investing in API protection in the financial sector isn't just about regulatory compliance - it's about sustaining trust across the whole ecosystem: between bank and fintech, fintech and customer, and customer and every new service they let into their 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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July 21, 2026 | NCFA Companies On The Move | Cybersecurity And Fraud, Identity Privacy And Data Governance, Artificial Intelligence And Data
Tailscale is a Toronto founded secure networking company built around WireGuard, identity controls and direct connections between devices. By July 2026, it was nearing 40,000 paid business clients and approximately 300 employees, according to BetaKit. Tailscale’s website separately reports 2.5 million active devices and 100,000 monthly active users.
The core business makes private networks easier to deploy and govern, while Aperture and Border0 take Tailscale into AI access and privileged infrastructure—two markets with bigger security budgets and much heavier competition. This profile looks at what customers are buying today, where the next leg of growth could come from and what the public evidence still can’t tell us.
The best public clues come from customers describing work they no longer have to do. Instacart reduced internal VPN support requests from about 10 each week to nearly zero, cut new user onboarding to less than one minute and reported no outages after deployment. Cribl grew from 18 to approximately 550 employees without hiring a dedicated networking team to administer access, while Corelight reports saving more than 1,000 hours annually and Positron estimates it saves an hour each time a prospect is onboarded.
These are selected Tailscale case studies, not audited results or a measure of what the average customer should expect. Still, they help explain how the product spreads: it removes the VPN tickets, slow onboarding and constant access administration that technical teams already dislike. A developer can start with one live problem, and if the network holds up, IT and security have a practical reason to standardize it, add controls and bring more of the company onto the same service.
Core Tailscale appears to be the product that pays today. It creates an encrypted private network among approved users, devices, servers and services, with identity based policy deciding what can connect. Developers can get started without rebuilding the company network; as use grows, IT and security can add centralized administration, device posture, logs and tighter access controls. Tailscale’s client, command line tool and relay server code are open source, but the hosted coordination server is proprietary. That coordination service distributes public keys and access rules, while customer traffic normally moves directly between endpoints or through encrypted relays. Tailscale Raises $230M To Power Identity-First Networking looked at why this model could pressure conventional VPN and firewall products.
The pricing supports the same bottom up motion. Tailscale currently lists a free Personal plan, Standard at US$8 per user per month, Premium at US$18 and custom Enterprise terms, with paid plans adding provisioning, device posture, administrative roles, network flow logs, regional routing and support. The cost of trying the product is low; the account becomes more valuable as more people, devices and company controls move onto it.
Revenue is the important missing number. Tailscale doesn’t publish it, and the outside estimates aren’t close enough to treat as fact. GetLatka puts 2025 revenue at US$45.2 million, although it says the figure is modelled and that management wasn’t interviewed. Northmetric estimates US$60.1 million in current annual recurring revenue with medium confidence, relying partly on an assumed 54,000 paying customers—well above BetaKit’s July 2026 report of nearly 40,000 paid business clients. Taken together, the estimates point to a company with real commercial scale, but they don’t establish Tailscale’s actual revenue.
Aperture is the move into AI access and cost control. Sitting between approved users or agents and AI model providers, it centralizes credentials while applying access rules, usage visibility and spending limits. That puts platform, security and AI infrastructure teams squarely in the buyer group. AI Agents Enter Governed Financial Workflows explains why permissions, approved tools and audit records matter once agents touch regulated work. Existing Tailscale networks could give Aperture a useful distribution advantage, but the product remains in beta and is currently available without extra cost during testing. Six users are included, with additional access handled through the company; usage, paid conversion and final pricing haven’t been published.
Border0 moves Tailscale into privileged infrastructure access. It governs sensitive connections to servers, databases, Kubernetes environments and internal applications, adding approval workflows, session recording and audit visibility. Those capabilities put Tailscale in front of security, compliance and operations buyers—not just the teams managing everyday network access. After acquiring Border0 in March 2026, Tailscale began connecting the product to its identity and networking layer, although the combined offering remains in beta. Adoption, revenue and final packaging haven’t been disclosed, so Border0 is best viewed as a credible expansion route rather than a proven second engine.
Tailscale now overlaps with secure networking, identity security, privileged access and AI gateways. Each move opens another budget, but it also brings the company up against much larger security platforms with broader bundles, established enterprise sales teams and far more acquisition firepower.
Large security platforms are buying identity. Palo Alto Networks completed its acquisition of CyberArk in February 2026, adding privileged access and identity security to a platform that already spans network, cloud and security operations. CrowdStrike agreed to acquire SGNL for continuous identity controls, while Zscaler agreed to acquire Symmetry Systems for data and AI access visibility. Buyers are clearly paying for identity and access control, but they may increasingly prefer to buy it inside a larger security contract.
SASE rivals have more capital and enterprise reach. Netskope’s September 2025 IPO raised approximately US$992 million and valued the company at about US$9.6 billion on a fully diluted basis. Netskope, Zscaler, Cloudflare and Palo Alto Networks can bundle network access with wider security products and sell through established enterprise teams. Tailscale’s counter is that technical users can adopt its product before a large security procurement begins, although that advantage could narrow as buyers consolidate more of their security spending with fewer vendors.
AI gateways are becoming a real product category. Cloudflare AI Gateway added real time spending limits and identity based controls in June 2026, while Kong sells governance for models, MCP servers and AI agents. Neo Raises US$100M To Control Enterprise AI Agents shows how quickly money and products are gathering around agent inventory, permissions and policy. Aperture approaches the same problem from inside a customer’s private network, which gives it an interesting opening; whether that opening lasts will depend on policy depth, auditability and model coverage.
Canadian financial institutions face clearer AI and vendor controls. OSFI’s July 2026 bulletin on generative and agentic AI connects AI use to existing expectations for technology risk, operational resilience and third party oversight. Its technology and cyber risk guideline and third party risk guideline make identity, logs, access policy and vendor diligence commercially relevant. OSFI And GRI Workshops Reveal What Regulated AI Needs found that weak identity, provider concentration and vendor oversight are already limiting adoption. Tailscale’s SOC 2 Type II status helps. CSA Cybersecurity Guidance For Registered Firms shows why firms will still need documented vendor diligence, access controls and current assurance reports.
Open source keeps the paid product honest. Tailscale identifies Headscale as an independent alternative to its proprietary coordination server, which means a capable technical team can self host that layer. The subscription therefore has to keep earning its place through reliability, administration, policy, support and company controls—not connectivity alone.
Easy adoption doesn’t remove enterprise budget friction. A Tailscale commissioned survey of 1,000 technology leaders found that 42% cited workflow or integration disruption when security upgrades were delayed, while one third cited an unclear business case. Customer results give Tailscale’s sales team concrete savings to work with, but a company wide deployment still needs an owner, a budget and proof that another security vendor can be retired or avoided.
Tailscale’s edge starts with how it gets in. A developer or infrastructure team can solve a live networking problem without waiting for a company wide migration; if the product works, IT and security can add policy, device controls, logs and support around a network that people are already using. Reported results from Instacart, Cribl, Corelight and Positron give that approach substance beyond the usual product pitch. It also places Tailscale across several areas in the NCFA Financial Innovation Map, including digital identity, cyber resilience, AI governance and enterprise infrastructure.
The next act is harder because Aperture and Border0 ask those customers to trust Tailscale with AI access and privileged infrastructure, where the budgets are larger and the incumbents are stronger. Nearly 40,000 paid business clients and 2.5 million active devices give Tailscale a meaningful starting point; what isn’t public yet is whether either product is creating meaningful new revenue.
The Company Intelligence Snapshot follows the funding, customer growth and product decisions that brought Tailscale to this point.
Tailscale was founded in 2019 to reduce the complexity of connecting people, devices and services across the internet. Its first generally available product combined WireGuard encryption, identity and direct connections without requiring companies to rebuild their existing networks.
TailscaleA Canadian founded secure networking company
LaunchGeneral availability arrived in April 2020
US$3M SeedLed by Heavybit with Uncork Capital and others
GlobalRemote teams, cloud infrastructure and personal networks
Developers FirstIndividuals and technical teams could start without enterprise deployment
Simpler VPNDirect encrypted connections reduced reliance on central VPN concentrators
Rather than begin with a top down security sale, Tailscale gave developers a faster way to connect private infrastructure and let working networks make the case for wider adoption.
Information notice: Private-company estimates are identified and attributed. Information may change after the stated update date. This content is provided for informational purposes only and does not constitute investment, financial or legal advice.
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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July 20, 2026 | NCFA Resource | Cybersecurity And Fraud, Risk Compliance And Regtech, Capital Markets And Market Infrastructure

On July 15, 2026, the Canadian Securities Administrators published new cybersecurity guidance for registered dealers, advisers, and investment fund managers (Download the 12 page PDF report). CSA Staff Notice 33-322 combines findings from a focused review of 73 firms with practical expectations for policies, employee training, risk assessments, third party oversight, and incident response.
The notice is most useful as a compliance review tool. Firms can compare their written controls, operating practices, and supporting records against the deficiencies and effective practices identified by securities regulators. The guidance is particularly relevant for smaller and medium sized firms that may not have dedicated cybersecurity teams.
The notice organizes cybersecurity readiness around five areas that regulators examined under section 11.1 of National Instrument 31-103:
The review found useful benchmarks. 8% of firms had no written cybersecurity policies, while 55% had policies that needed improvement. Twenty one per cent provided no employee cybersecurity training. Forty five per cent completed risk assessments that could have been stronger, and 12% had no documented assessment during the review period.
Third party oversight was one of the clearest weaknesses. All examined firms used service providers with access to systems or data, but 62% had no documentation or limited documentation supporting their cybersecurity oversight. The CSA expects firms to complete and document due diligence before onboarding a provider and repeat that review throughout the relationship.
The guidance identifies information firms should assess, including data storage, encryption, access controls, patch management, incident notification, subcontractors, operating jurisdictions, and shared responsibility in cloud environments. It also recommends maintaining a complete vendor register and reviewing current SOC 2 or similar reports where available.
Incident preparedness also receives detailed attention. Fifteen per cent of firms had no written incident response plan. Among firms with a plan, 53% needed stronger procedures and 63% should have tested their plans more regularly. The notice describes tabletop exercises and simulated attacks as practical ways to test whether people, processes, and technical controls work together during an incident.
The primary audience is firms registered as dealers, advisers, portfolio managers, investment fund managers, exempt market dealers, and restricted portfolio managers. Chief compliance officers, directors, technology leaders, privacy professionals, and internal audit teams can use the notice to organize a control review and identify missing documentation.
Boards and senior executives can also use it to test whether cybersecurity oversight is tied to clear responsibilities, regular reporting, and evidence that controls operate as intended. Written policies alone aren’t enough when actual practices, testing schedules, or access controls differ from the documented process.
Cybersecurity consultants, legal advisers, insurance providers, managed service providers, and software vendors can use the findings to better understand the records and evidence registered firms may need during a regulatory review.
The notice is strong because it combines regulatory expectations with observed deficiencies, percentages, effective practices, and practical takeaways. It covers both governance and technical controls, including multifactor authentication, encryption, backups, access rights, patching, email filtering, endpoint protection, and activity logging.
It also makes documentation a central requirement. Firms should be able to show when policies were reviewed, who completed training, how risks were assessed, what vendor due diligence occurred, and when incident plans or backup recovery procedures were tested.
The guidance does not create a complete technical cybersecurity standard, and it doesn’t replace obligations under privacy, securities, corporate, or other applicable laws. Expectations also vary with the firm’s size, operating complexity, client information, service provider reliance, and exposure to cyber risk.
Firms should therefore use the notice as a regulatory gap assessment and evidence checklist, then supplement it with appropriate legal advice, technical standards, testing, and controls suited to their operations.
CSA Staff Notice 33-322 (cybersecurity examination findings and guidance for registered firms)
CSA Staff Notice 33-321 (foundational 2017 cybersecurity and social media guidance)
NIST Cybersecurity Framework (risk management structure for identifying, protecting, detecting, responding, and recovering)
CIS Critical Security Controls (prioritized technical and operational safeguards)
Wealthsimple Confirms Breach Impacting Clients (third party exposure and incident response)
Proposed Class Action Targets Equifax Access Controls (access governance and third party permissions)
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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