Karsten Wenzlaff, Advisor
August 26th, 2025
May 7, 2026 | NCFA Fintech Market Activity | Capital Markets And Funding, Payments And Money Movement, Financial Inclusion And Consumer Protection

On May 7, 2026, Spendsafe announced a non binding letter of intent with 1587815 B.C. Ltd. for a proposed reverse takeover that could list Spendsafe on the TSX Venture Exchange, subject to exchange approval and other closing conditions. This isn't an IPO. It is an early public listing transaction that still needs due diligence, a definitive agreement, and corporate, regulatory, and TSXV approvals.
Important to note that a letter of intent doesn't complete a listing. It gives the market a proposed structure and a reason to watch and evaluate. For Spendsafe, the company is trying to turn youth financial education into a regulated payments product, not a standalone lesson app.
Spendsafe launched in December 2025 combines a Mastercard enabled prepaid card, parent controls, and AI enabled coaching for children and teens aged 6 to 18. Peoples Trust Company acts as issuer and Berkeley Payment Solutions acts as program manager. That gives the platform a payments stack behind the learning experience. The product's promise is turning everyday transactions into teachable moments.
That is where the model gets more interesting than another allowance card. Financial literacy often fails when it stays abstract. A youth financial education platform with card, parent dashboard, and coaching layer can connect spending, saving, chores, and money habits to real behaviour.
Smaller fintechs still need capital market access, but the IPO bar remains high. A proposed reverse takeover (RTO) can give a growth company a public listing route via merger without a traditional offering process. Public investors still need proof of product demand, disciplined governance, clear disclosure, and a credible use of capital.
For a youth finance platform, trust carries extra weight. Parents need control. Young users need safe access. Partners need compliance confidence. Regulators will care about privacy, marketing, payment oversight, and how AI coaching interacts with children and teens. A public market structure can help only if it brings better disclosure and stronger accountability.
Spendsafe also says the proposed listing could support product investment, partner integrations, and broader North American growth goals. The company isn't just raising attention around an app. It's trying to build a payments and education category that depends on distribution partners, measurable outcomes, and evidence that the product improves how families handle money.
Prior to any listing closing, Spendsafe still has to prove that young users engage, parents stay involved, partners see value, and the education layer produces results worth measuring. Public markets can fund growth, but they also expose weak assumptions fast. That’s healthy if the company can show real adoption and clean governance.
Payments infrastructure can open the door, but trust keeps it open. Can a TSXV public listing structure help Spendsafe turn youth payments, AI coaching, and financial education into a trusted Canadian growth category?
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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May 7, 2026

The same mapping platform can be the right answer for one team and the wrong answer for another, even inside the same building. The reason is that business mapping is not one job. It is six or seven different jobs that happen to share an underlying technology layer. The platform that handles a sales territory rebalance is not necessarily the one that handles a delivery route optimization, and the one that handles delivery routing is not necessarily the one that handles retail site selection.
This roundup walks through the seven mapping use cases that show up most often in business reviews and identifies which platform actually wins each one. The differences come down to how each platform approaches data, geography, and the analytical work that follows the first map.
Sales territory planning is the work of dividing accounts among representatives so that each one has a balanced book of business. The mathematical problem underneath it is allocation, not visualization, even though the visualization is what most platforms sell.
Maptive wins this use case for the typical mid-market sales operations team. The platform’s territory automation tools draw balanced regions from account location, account count, revenue contribution, and travel distance simultaneously, which is the actual problem most teams face. The output is a set of territories the manager can adjust by hand without losing the balance constraint.
Salesforce Maps wins this use case for organizations already standardized on Salesforce. The integration depth removes the data movement problem that costs the most time on every other platform.
Field service and delivery routing is the work of ordering a day’s stops to minimize drive time. The technology underneath is route optimization, which is a separate computational problem from territory design.
Mapline wins this use case at the small-team level because of the entry pricing and the operational focus of the platform. Route optimization is built into the core product without an upgrade path.
Maptive wins this use case at the mid-market level because the route optimization tool sits inside the same platform that handles territory and visualization, which removes a tool transition that field service managers find friction-heavy. Reported route optimization gains across deployments average 22 percent.
For very large delivery operations with a dedicated logistics function, dedicated route optimization platforms outside this roundup remain the standard.
Retail location strategy is the work of deciding where to open the next store, where to close an underperforming one, and how to weight a portfolio against competitor presence and demographic patterns. The technology underneath is spatial analysis layered onto demographic data.
Esri ArcGIS Business Analyst wins this use case at the enterprise level because of the depth of the demographic and consumer spending data that comes inside the platform. The analytical capability has no peer in this category.
Maptive wins this use case at the mid-market level. Demographic overlays, drive-time radius analysis, and customer mapping combine inside one interface at a fraction of the enterprise platform cost. A regional retail chain evaluating five potential locations does not need the full Esri ecosystem to run a competent comparative analysis.
Real estate market analysis covers commercial site selection, residential market evaluation, and portfolio-level analysis of holdings.
Maptive wins this use case for the practical real estate professional who needs visualization, demographic overlays, drive-time radius, and competitor mapping in one place without specialist training. The analytical depth matches the work most real estate teams actually do, and the boundary-allocation principles that Bloomberg’s reporting on the art of retail site selection describes apply equally to portfolio-level real estate work.
For real estate investment trusts and large brokerage networks running portfolio-level analysis with custom data models, Esri ArcGIS extensions become the answer at the enterprise tier.
Marketing and customer segmentation is the work of grouping customers by location, behavior, and demographic profile to inform campaign targeting.
Maptive wins this use case because customer relationship management connectors pull existing segmentation work directly into the mapping interface. Heat mapping, density analysis, and demographic overlays then layer the location intelligence on top of the segmentation that already exists in the customer database, which avoids the duplicate segmentation effort that plagues most marketing mapping projects.
For organizations with embedded business intelligence platforms and dedicated analytics teams, the existing tools usually cover this work without a separate mapping platform purchase.
Strategic planning that requires demographic depth at the level of consumer spending power, household composition, and market share by trade area is the use case where most casual mapping platforms fall short.
Esri ArcGIS Business Analyst wins this use case at the enterprise tier because of the proprietary demographic and consumer datasets that ship with the platform. The depth has no equivalent in the category, and the platform sits at the analytical end of the Geographic Information System spectrum that distinguishes specialist tools from general-purpose business mapping.
Maptive wins the next tier down. Demographic overlays cover the most common analytical needs without the enterprise platform investment, the consultant time, or the multi-week training ramp.
Multi-location franchise operations cover the work of mapping franchisee locations, comparing performance across markets, and evaluating expansion territory.
Maptive wins this use case because the platform handles spreadsheet uploads from franchise reporting systems without preprocessing, supports up to one hundred thousand mapped points per project, and produces shareable interactive maps for franchisor and franchisee distribution. CNBC coverage of Aldi’s record store expansion confirms this pattern across operational work involving distributed teams.
For franchise organizations with small footprints and tight budgets, Mapline covers the same work at lower entry cost with less analytical depth.
A consistent pattern emerges across the seven use cases above. The platform that wins at the entry tier is rarely the one that wins at the mid-market or enterprise tier. Maptive appears in the mid-market answer for six of the seven use cases. Esri appears in the enterprise answer for two. Salesforce Maps wins one specific case that depends on a specific software footprint. Mapline wins at the small-team operational tier.
The reason is structural. Mid-market business mapping work shares an analytical floor that purpose-built business mapping platforms can hit without specialist staffing, and Maptive sits at the broadest version of that floor. Enterprise work asks for specialist tools because the analytical depth required outruns what a general-purpose platform can carry. Small-team operational work asks for low entry cost and tight focus on routing and territory, which Mapline provides.
A team trying to pick one platform without knowing the use case usually picks wrong. A team that maps the use case to the platform first usually picks right. Recent coverage of innovative retail analytics companies shows how the underlying technology investment has shaped the platform tier structure across the category.
The trial offerings across the platforms in this roundup cover the practical question buyers should be asking. The platform that fits the work the team actually does is the one to choose, not the one that wins the use case the team thinks it does in the abstract.
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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May 6, 2026 | NCFA Feature | Artificial Intelligence And Data

On May 5, 2026, Anthropic introduced finance agent templates for work that financial teams already manage every day. The list covers five agent templates and five workflow control templates all ready to go. This isn't just another AI product update and points to import changes to how financial services will operate in the near future. It also confirms that AI once again is leaving the loose prompt box and entering into controlled workflow systems.
These systems keep work inside permissioned data rules, use approved tools, review evidence, and provide risk teams a record that they can inspect and follow-up on. Regulated financial fintechs and financial institutions need these controlled AI agents inside defined workflows along with human review before output reaches a client file, compliance record, valuation, trade document, or board package.
The first wave of generative AI in finance looked like a personal productivity tool. Staff used chat assistants to summarize documents, draft emails, explain code, build first cut memos, and prepare research notes. That helped save some workers a lot of time, but it kept AI at the edge of the operating model. Now there's a return on intelligence in finance applications.
Anthropic’s new finance agents look capable of handling work on a more serious level. Each template combines task instructions, governed data connectors, and subagents for specific jobs such as peer company review, checking valuation methods, or reviewing source material. Teams can also adapt the agents to their own modelling conventions, risk policies, approval flows, and data access rules.
A governed agent can follow a checklist, call a tool, update a model, prepare a file, and hand the work to a reviewer. It can also create a record inside Claude Console. An audit section that doesn't auto correct the output by itself but makes the work easier to inspect. Model access is becoming common. Controlled execution is harder to obtain.
For operators, the useful question is where can an agent reduce manual drag without taking final judgment away from people. The measurable benefit should come from workflow metrics, not AI hype. Anthropic’s primary source gives one hard implementation claim. Teams can put Claude on finance work in days rather than months.
1. Pitch Builder A human banker builds a pitchbook by gathering company data, picking peers, checking comparables, drafting a story, and turning numbers into slides. An agent can run that process as a controlled sequence. It can pull approved data, prepare peer company comparisons, draft pages, and carry figures into a deck. The banker still decides which story is credible. The agent cuts the assembly work and leaves a clearer trail of sources and assumptions.
2. Meeting Preparer A human relationship manager often prepares by searching email, notes, filings, news, and prior client material. That process depends on memory and time. An agent can assemble a brief from connected sources, organize recent events, flag open issues, and keep the context ready for the meeting. The constraint is conduct risk. Firms need approved sources, stale data warnings, and a clear line between internal preparation and client ready advice.
3. Earnings Reviewer A human analyst reads filings, transcripts, guidance changes, and prior models to find what changed. An agent can do the first pass faster. It can compare current results with previous periods, update a draft model, flag changed language, and highlight items tied to an investment thesis. The analyst still decides what's important.
4. Model Builder A human analyst builds and updates models by entering figures, linking sheets, checking formulas, and adjusting assumptions. An agent can pull data from filings and feeds, create a first draft model, update assumptions, and help test formula consistency. That can save time, but it also raises the control bar. Firms need version control, formula review, source tagging, and named ownership before model output supports pricing, credit, valuation, or investment decisions.
5. Market Researcher A human researcher scans news, filings, broker research, sector reports, and internal notes to decide which facts matter. An agent can monitor connected sources, group findings by issuer or sector, and surface items for credit, risk, or investment review. The value is less search time and a better first cut of the evidence people need to judge.
6. Valuation Reviewer A human reviewer checks valuation work by testing inputs, peers, methods, policy thresholds, and judgment calls. An agent can run a structured first pass against approved comparisons, methodology rules, and company standards. It can flag gaps or inconsistencies before a reviewer signs off. That helps private markets, credit teams, fund administrators, and auditors, but the firm still has to control the inputs. In valuation, speed without discipline can multiply risk.
7. General Ledger Reconciler A human finance team reconciles accounts by matching records, finding breaks, explaining differences, and routing exceptions. An agent can compare account records, identify mismatches, prepare exception notes, and support net asset value calculations against books of record. The practical gain is cleaner exception handling. Reviewers still need the break list, explanations, approvals, and audit trail.
8. Month End Closer A human close team runs checklists, prepares entries, confirms balances, and packages reports under deadline pressure. An agent can run the checklist, prepare draft journal entries, assemble support, and produce close reports for review. That helps speed and consistency. Finance leaders still need approval evidence, segregation of duties, and a clean record of changes before final sign off.
9. Statement Auditor A human reviewer checks financial statements for consistency, completeness, formula issues, disclosure gaps, and unexplained changes. An agent can run those checks across statements and supporting files, then package exceptions before external review. The value is earlier detection and better reports. Audit judgment stays with people.
10. KYC Screener A human compliance analyst gathers documents, checks entity details, reviews risk flags, and escalates unclear cases. An agent can assemble entity files, compare source documents, identify missing information, and prepare escalation packages for compliance review. The strategic value is a cleaner file, fewer manual searches, better evidence capture, and faster escalation when risk is unclear.
On Apr 30, 2026, APRA called for a step change in AI risk management and governance across banks, insurers, and superannuation trustees. APRA warned that AI use is growing faster than governance, risk management, assurance, and operational resilience practices.
It also raised concerns about concentration risk, weak contingency planning, fragmented assurance, and reduced transparency when AI features come embedded within larger software platforms.
The FCA is testing similar issues in live environments. On Apr 21, 2026, the FCA named firms in its second AI Live Testing cohort, with use cases that include agentic payments, anti money laundering detection, credit score insights, KYC, and investment support. Testing runs through the end of 2026, with an evaluation report expected in Q1 2027.
Buyers won't only ask if the tool works. They'll ask what evidence proves it works, where humans review it, how errors surface, how permissions operate, and how the firm can stop the workflow when risk changes.
Financial institutions should treat finance agents as workflow infrastructure:
For banks, controlled scale should start where process discipline already exists. Good candidates include KYC reviews, credit memo preparation, internal research, model checking, finance close support, and audit readiness. These workflows already have owners, policies, and reviewer structures. That makes them better candidates than open ended client advice or autonomous transaction decisions.
For wealth firms, the strongest use cases sit in client preparation, research support, portfolio review notes, and compliance ready documentation. The danger is blurred accountability. A meeting brief can become advice in practice if staff reuse it without review. Wealth firms need templates, source labels, approval gates, and retention rules that fit suitability, disclosure, and conduct obligations.
For capital markets platforms and private market operators, agents can improve diligence speed. They can search data rooms, compare issuer materials, prepare investor questions, review disclosure consistency, and draft internal summaries. The platform must show where each fact came from and keep investment judgment with people.
For regtech vendors, the opening is clear. Build around review evidence, role based permissions, source traceability, escalation records, model monitoring, and shutoff controls. Don’t sell a generic AI layer. Sell the control fabric that lets financial firms use agents without losing accountability.
For investors, the better diligence question is where AI enters the workflow, what data it can touch, who reviews its output, and what record proves the process worked. AI adoption without operational evidence isn't a moat. It's a future remediation cost.
Small and mid sized financial institutions face a practical capacity gap. Many do not have deep AI engineering, data governance, risk, and integration teams. Anthropic’s May 4 announcement of a new enterprise AI services company with Blackstone, Hellman & Friedman, and Goldman Sachs speaks to that constraint. Anthropic said companies from community banks to mid sized manufacturers and regional health systems can benefit from AI, but lack the in house resources to build and run frontier deployments.
AI agents in finance don't need more use cases. Startups shouldn't copy bank scale infrastructure too early, and banks shouldn't treat agentic AI like another desktop tool. The right balance is to start with narrow workflows, measure the time saved, add controls as risk rises, and stop before governance costs outrun the value.
But once an agent touches regulated records, client decisions, and audit files, cheap experimentation ends. The real cost isn't only the model. It's all the other infrastructure from data access, permissions, monitoring, review gates, and vendor oversight that make work usable in finance.
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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May 6, 2026

Ontario's regulated online casino market processes billions of dollars a year. Behind every deposit and withdrawal sits a stack of fintech infrastructure that rarely gets discussed outside payment-industry circles: account-to-account rails, payment facilitators, KYC verification layers, AML monitoring, and bank-connectivity protocols.
This article is not a gambling guide. It uses Ontario iGaming as a case study to show how Canadian payment methods, PSPs, and risk controls work in a live, high-volume digital environment.
Few Canadian verticals compress so many fintech challenges into a single transaction flow. An online casino deposit requires instant consumer authentication, real-time bank connectivity, merchant-risk assessment, and regulatory compliance — all within seconds.
A consumer-facing guide to casinos that support Gigadat illustrates this compression well: users see a simple cashier screen with payment options, while behind it sits a multi-layered processing chain involving banks, facilitators, compliance checks, and settlement queues.
The scale of this market reinforces its relevance for payment professionals. According to iGaming Ontario's 2024–25 annual report, the regulated market recorded $82.7 billion in total wagers and $2.9 billion in total gaming revenue across roughly 50 active operators.
Key takeaway for fintech readers: iGaming is not just a gambling story. It is one of the few Canadian digital verticals where instant payments, high-risk merchant classification, strict AML obligations, and consumer trust expectations collide in every single transaction.
Ontario online casinos generally rely on a handful of payment categories. The mix varies by operator, licensing conditions, and compliance setup, but the core options fall into recognizable groups.
Interac e-Transfer is the backbone of most Ontario casino cashier flows. According to Interac's FAQ, e-Transfer lets Canadians send money through online banking, with participating financial institutions handling the transfer through established secure banking procedures. Processing usually happens in minutes, though it can take up to 30 minutes depending on the bank or credit union.
For fintech professionals, the important distinction is this:
| What the consumer sees | What happens on the back end |
| "Pay with Interac e-Transfer" | Bank authenticates user, routes funds through Interac rails |
| Instant confirmation | Settlement may still be pending between institutions |
| Simple email or text notification | The money itself travels through secure banking channels, not via email |
Interac e-Transfer functions as a bank-account payment rail, not an e-wallet. That distinction matters for PSPs, compliance teams, and anyone building deposit flows for Canadian merchants.
Gigadat is one of several Canadian payment facilitators that sit between the consumer's bank and the merchant. Gigadat's Pay-Ins page describes its role around local online and mobile banking options, including Interac e-Transfer and Interac e-Transfer Request Money.
In practice, a facilitator like Gigadat can handle:
The consumer may never see Gigadat's name at all. Or, depending on how the operator integrates the service, Gigadat may appear alongside Interac branding in the cashier interface.
Beyond Interac and payment facilitators, Ontario casinos may accept:
Each method carries different implications for settlement speed, chargeback risk, fraud exposure, and compliance overhead.

Understanding Gigadat's role requires separating the pay-in (deposit) path from the payout (withdrawal) path. The two operate differently, and the user experience can diverge significantly.
When a user deposits funds, the facilitator connects the user's bank session to the merchant's receiving account. The process typically involves:
From the user's perspective, the deposit feels instant. From the merchant's perspective, there may be settlement delays depending on the banking chain involved.
Withdrawals follow a different logic. Gigadat's Pay-Outs page explains that Interac e-Transfer payouts can let merchants send money to consumers using an email address or mobile phone number rather than collecting bank-account details.
This distinction matters for two reasons:
A common misconception: "instant withdrawal" often refers to the speed of the payment rail after the merchant releases the funds — not to the total time from withdrawal request to money in the user's account.
Consumer payment guides often collapse back-end distinctions into a simple label such as "Gigadat" or "Interac." In reality, both names can appear in the same transaction: Interac as the consumer-facing rail, Gigadat as the facilitator managing the merchant side. This layered structure is standard in Canadian digital payments but rarely visible to end users.
Fast payment UX does not remove compliance obligations. If anything, the speed of account-to-account transfers increases the pressure on operators and PSPs to build robust monitoring systems.
The regulatory landscape for Canadian PSPs shifted significantly in 2025. The Bank of Canada announced that supervision under the Retail Payment Activities Act (RPAA) came into effect on September 8, 2025, with close to 1,500 PSPs under oversight for risk-management and safeguarding obligations.
What this means in practice:
| RPAA requirement | Relevance to iGaming payments |
| Operational risk management | PSPs processing casino transactions must demonstrate controls for fraud, outages, and settlement failures |
| Safeguarding of funds | User deposits in transit must be protected, not commingled |
| Incident reporting | PSPs must report material disruptions to the Bank of Canada |
For fintech founders and investors, the RPAA framework changes the compliance baseline for any Canadian payment service — not just those serving iGaming.
On the merchant side, FINTRAC's casino guidance outlines how casino-related entities are treated under Canada's proceeds-of-crime and terrorist-financing legislation. Entities conducting and managing gaming activities carry specific reporting responsibilities.
Key obligations in this context generally include:
These requirements exist independently of the payment method used. Whether a user deposits via Interac, card, or bank transfer, the casino's AML obligations remain the same.
A deposit can arrive in seconds. A withdrawal may take days. The gap is almost never about the payment rail itself. It typically reflects:
This distinction is critical for anyone building or evaluating payment products: the rail is only one layer in the total transaction experience.

Ontario's iGaming market is a stress test for Canadian payment infrastructure. The lessons extend well beyond gambling.
Consumer trust depends on familiar rails. Interac e-Transfer succeeds in casino cashiers for the same reason it succeeds everywhere else in Canada: users recognize it, trust it, and know how it works through their own bank. Any fintech building a consumer-facing payment flow in Canada should consider how much of this familiarity it can leverage.
The pay-in/payout asymmetry is universal. Deposits tend to be instant; withdrawals tend to be slower. This pattern repeats across marketplaces, gig-economy platforms, insurance payouts, and lending products. The iGaming vertical simply makes the friction more visible because users expect fast returns.
Compliance is now a product feature, not just a cost centre. Under the RPAA supervision environment, PSPs that can demonstrate robust risk management may gain a competitive advantage over those still treating compliance as an afterthought.
For fintech founders: iGaming payments reveal the tension between speed and safety more clearly than almost any other Canadian digital vertical. The operators who handle it well offer a template for high-risk merchant processing in other sectors.
While this article focuses on infrastructure, the underlying payment lessons apply to anyone using digital payment methods in Canada — not only in casinos.
Before trusting any online payment flow, consider checking:
Ontario's iGaming market matters to fintech professionals not because of the casino content, but because of what it reveals about the state of Canadian payment infrastructure.
Account-to-account payments work. Interac e-Transfer has become the default consumer expectation for instant domestic transfers. Payment facilitators like Gigadat demonstrate how intermediaries can bridge bank rails and merchant platforms without requiring users to share sensitive financial details. The RPAA now holds PSPs to formal supervisory standards. And AML obligations ensure that fast rails do not bypass necessary safeguards.
For anyone building, investing in, or regulating Canadian fintech products, the iGaming payment stack is a compact, high-volume example of where Canadian digital payments stand today — and where they are heading next.
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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