Karsten Wenzlaff, Advisor
August 26th, 2025
Aug 13, 2026

Artificial intelligence (AI) is rapidly becoming part of the day-to-day operations of Canadian financial advice firms. From automating administrative tasks and analyzing client portfolios to supporting investment research and improving client communications, AI has the potential to make advisors more efficient and help firms deliver a better client experience.
But as adoption accelerates, governance isn't always keeping pace.
Many firms are experimenting with AI tools before establishing clear policies around how those tools should be used, monitored, and supervised. That creates significant risk in an industry where investment advice is built on trust, accountability, and regulatory compliance.
Using AI without proper governance is a bit like prescribing medication without understanding the side effects or drug interactions. The technology may offer benefits, but without safeguards, oversight, and a clear understanding of the risks, unintended consequences can quickly outweigh the advantages.
For Canadian financial advisors, governance shouldn't be viewed as unnecessary bureaucracy. It's an essential part of responsible innovation.
Canada's financial regulatory environment already places significant responsibilities on advisors, and those obligations don't disappear simply because AI enters the picture. The Canadian Investment Regulatory Organization (CIRO), together with provincial securities regulators such as the Ontario Securities Commission (OSC) and the Canadian Securities Administrators (CSA), have made it clear that existing regulatory obligations continue to apply whenever technology influences regulated activities. Firms remain responsible for ensuring investor protection, fair dealing, appropriate supervision, cybersecurity, privacy, and sound governance, regardless of whether decisions are supported by artificial intelligence.
AI governance is no longer simply a future consideration. CIRO's 2026 Compliance Report identifies artificial intelligence and emerging technologies as areas of supervisory focus, signalling that firms should expect regulators to examine how AI systems are being used, what controls are in place, and whether appropriate oversight exists. The message is clear: firms remain accountable for the outcomes produced by the technology they choose to implement.
At its core, Canadian financial advisors continue to operate under well-established regulatory obligations. For most registered firms, this includes complying with Know Your Client (KYC), Know Your Product (KYP), and suitability requirements under the Client Focused Reforms. In certain advisory relationships, such as discretionary portfolio management, a fiduciary duty may also apply. Regardless of the business model, advisors are expected to understand the rationale behind every recommendation they provide and be able to explain why it is appropriate for each client. That expectation becomes much more challenging if an AI system produces recommendations that advisors cannot clearly explain, let alone defend or stress test.
Explainability is only one piece of the governance puzzle. Firms must also consider data privacy, cybersecurity, recordkeeping, model bias, third-party vendor oversight, and ongoing monitoring of AI systems. Regulators expect firms to demonstrate not only that technology delivers operational benefits, but also that associated risks are identified, documented, and actively managed.
History provides plenty of reasons for this scrutiny. AI systems used in other industries, such as HR, have produced biased hiring decisions, inaccurate healthcare recommendations, and flawed credit assessments due to inadequate oversight or unintended algorithmic behaviour. Financial advice firms cannot assume similar issues won't emerge within investment or wealth management applications.
Another emerging consideration is AI-generated investment commentary. Recent guidance from the CSA and CIRO reinforces that securities laws apply regardless of how investment recommendations are delivered. Whether commentary comes from a financial advisor, an online platform, or an AI-powered tool, firms remain responsible for ensuring communications comply with applicable registration, disclosure, and investor protection requirements. AI cannot be used to distance a firm from its regulatory responsibilities; introducing it does not reduce those responsibilities. If anything, it increases the need for governance.
Strong AI governance starts long before a new tool is deployed. Rather than allowing employees to independently adopt AI solutions across different departments, firms should first define exactly where AI will be used and where human expertise must remain central to the decision-making process. Administrative automation, document summarization, workflow management, and research support may represent lower-risk applications than suitability assessments, portfolio recommendations, or investment decisions that directly affect clients. Establishing clear use cases helps prevent AI from gradually expanding into areas where the risks may outweigh the benefits.
Governance also requires clear accountability. Every AI-enabled process should have an identified owner who is responsible for monitoring performance, addressing concerns, and escalating issues when necessary. Responsibility cannot rest with the software itself. Human accountability remains essential.
Transparency should be another guiding principle. Clients deserve to understand when AI contributes to services they receive, particularly if it influences recommendations, communications, or financial planning outputs. Transparency builds trust while helping clients better understand how technology supports, rather than replaces, professional judgment.
Bias testing is equally important because AI models learn from historical data, which can contain unintended biases. If left unchecked, algorithms may produce outcomes that disadvantage certain investor groups or reinforce patterns that conflict with principles of fairness and equal access. Regular testing allows firms to identify and correct these issues before they affect clients. The objective isn't simply to deploy AI; it's to deploy AI responsibly.
Creating governance policies is only the first step. Maintaining them requires ongoing operational discipline. There are some daily practices that could help firms in this aspect:
Proper documentation: Every meaningful AI-assisted recommendation or decision should be properly documented. Firms should be able to demonstrate how information was generated, how it was reviewed, and how the final recommendation was reached. Comprehensive documentation not only supports internal quality control but also prepares firms for future regulatory reviews.
Continuous monitoring: AI systems are not static. Performance can change over time as market conditions evolve, new data becomes available, or models begin exhibiting algorithmic drift. Regular reviews help ensure systems continue operating as intended while identifying unexpected behaviours before they become larger problems. Many firms may benefit from conducting quarterly governance reviews that assess model performance, review exceptions, evaluate client outcomes, and confirm compliance with internal policies.
Employee education: This should also remain a priority. Advisors need to understand both the strengths and limitations of AI. Training should focus not only on how to use new tools but also on recognizing situations where human judgment should override automated recommendations.
AI should not be treated as a set-and-go replacement for professional expertise. It should be used responsibly as a tool that enhances decision-making and quality investment advice while preserving the experience, judgment, and accountability that clients expect from trusted financial advisors.
AI will undoubtedly reshape financial advice in Canada, but technology alone won't determine which firms succeed. Governance will. Organizations should establish clear policies, maintain transparency, monitor performance, and preserve meaningful human oversight while using AI. Without adequate governance, firms may expose themselves to compliance failures, reputational damage, and increased regulatory scrutiny.
As AI capabilities continue to expand, firms should regularly ask themselves one important question: Could we clearly explain every AI-assisted recommendation to a client and, if necessary, to a regulator? If the answer is yes, governance is likely supporting innovation. If the answer is no, governance deserves attention before AI adoption moves any further.
Ultimately, responsible AI is not a roadblock to the adoption of innovation. It's about ensuring innovation strengthens the quality, integrity, and trust that define professional financial advice.
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Nadeem Kassam, Marnoa Private Wealth Counsel
Nadeem Kassam, CFA®, MBA
Chief Investment Strategist, Chief Operating Officer & Portfolio Manager at Marnoa Private Wealth Counsel
Nadeem is a Chief Investment Strategist and Portfolio Manager with 20+ years' experience across major global banks, including senior-level roles at RBC, Raymond James, CIBC, Deutsche Bank, and Citigroup. At Marnoa, he leads investment strategy and portfolio management with a focus on North American equities and is a frequent commentator in the media, including regular appearances on BNN Bloomberg.
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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August 13, 2026 | NCFA Insight | Artificial Intelligence And Data, Competition And Market Structure, Public Sector Policy And Industrial Strategy

On August 10, 2026, Meta published The Future Is For Everyone, Mark Zuckerberg's wide sweeping proposal for how superintelligence should fit into society.
The central idea is personal empowerment. Zuckerberg argues that advanced AI should give individuals more ability to create, learn, build businesses, improve their health and pursue their own goals rather than placing most of that intelligence under the control of governments, large institutions or a handful of AI companies.
Meta's vision imagines personal agents working continuously on a user's behalf, small teams building companies that once required much larger organizations, personalized tutors, faster scientific discovery and powerful creative tools available to billions of people.
Meta wants AI capability spread widely, while the compute, models, release decisions and government relationships needed to provide it remain concentrated among a handful of organizations.
Mark Zuckerberg, Founder and CEO, Meta:
“The defining questions of our age are who will have access to superintelligence and what will we direct it towards.”
One of Zuckerberg's strongest economic arguments is that AI's biggest contribution could come from helping people invent things rather than simply automating today's jobs.
Meta expects individuals to become capable of doing work that currently requires larger teams, more capital or specialized expertise. Zuckerberg predicts more small businesses, more experimentation and potentially more employment as people use AI to create products, services and jobs that don't exist today.
That is a different vision from a future where AI mainly replaces knowledge work. Meta argues that if personal agents increase people's capabilities quickly enough, workers can adapt and new demand can grow alongside automation.
For founders, that could change the economics of starting a company. Product development, research, design, marketing and operations could require fewer people and less initial capital. Small firms could reach meaningful scale much earlier.
Financial services will feel the same pressure. Meta already has AI that can plan work, connect with email and calendars and continue tasks after the user leaves. As agents gain access to financial information and connected services, permissions and accountability become part of the operating model, especially when an agent can act rather than simply advise.
The more unusual part of Zuckerberg's argument is about safety.
He rejects the idea that one centrally controlled superintelligence can be aligned to a single set of values that works for everyone. People disagree about politics, economics, culture and what makes a good life.
Meta's answer is to distribute powerful AI widely enough that people, businesses, governments and competing AI systems check one another.
It is essentially a balance of power argument. One person with vastly better legal, financial or cybersecurity intelligence could gain an enormous advantage. If many people have access to comparable capabilities, Meta argues that power becomes harder to monopolize. (There’s some irony here. Zuckerberg built his fortune by controlling access to data, distribution and network effects that others couldn’t easily replicate.)
That philosophy also influences Meta's approach to alignment. Personal agents should primarily help users pursue their own goals within legal and safety boundaries rather than enforce one company's view of what those goals should be.
Meta says it plans to build a private mode where even Meta can't access a user's information, and it intends to resume releasing some open models. It is also giving its independent board authority to approve safety criteria for model releases rather than leaving those decisions entirely with Zuckerberg or management.
Meta's existing algorithmic products are already under legal scrutiny, including a federal trial involving 29 U.S. states over alleged harm to children. Meta denies the allegations. A company asking people to trust far more capable personal agents will have to show that user empowerment, privacy and safety work in practice. Algorithmic accountability is already moving into the courts as AI and automated systems take on a larger role in people's lives.
Zuckerberg's decentralization argument has limits.
He wants individuals to have broad access to powerful AI, but he also argues that the United States and its allies should retain leadership in advanced models, silicon and infrastructure. Meta supports continued restrictions on exports of leading chips to geopolitical rivals and wants U.S. policy to make it easier to build data centres and energy capacity.
He also proposes closer cooperation between frontier AI labs and government. Rather than waiting until an advanced model is finished, Meta wants labs to share intermediate model checkpoints and technical staff so governments can identify cybersecurity and other security risks earlier.
The result still leaves considerable power with governments, frontier labs and the companies that control advanced compute. Individuals would gain far more capability. Governments would receive earlier access for security purposes. Independent boards would get more authority over release standards. Frontier labs would still control development of the most capable models.
Meta's vision is therefore decentralized at the user level while retaining substantial institutional coordination at the frontier.
Meta expects capital spending of US$130 billion to US$145 billion in 2026 and spent US$31.08 billion in the second quarter alone. It is investing in models, data centres, energy, networking, its own chips and outside accelerators while trying to deliver AI across products already used by billions of people.
If personal superintelligence is going to be free or affordable at global scale, someone still has to pay for the compute..
Meta wants superintelligence broadly distributed, but scarce compute still has to be allocated. Its answer is a dynamic auction for additional capacity, which means the vision of AI for everyone could still produce tiers of access based partly on what users can afford. (conflict?)
The business model hasn't been proven. Meta's second quarter free cash flow fell to US$784 million as infrastructure spending accelerated, even while its core advertising business remained highly profitable.
Meta is making these commitments under real pressure. Its infrastructure spending has climbed rapidly, the company is still building the compute capacity and custom chips needed to compete at the frontier, and its existing platforms face growing legal scrutiny.
The scale of the investment also reinforces a central tension in Zuckerberg's vision. Meta wants personal AI to give individuals more power, but only a small number of companies can currently finance the systems needed to provide it.
Meta's vision has clear upside for Canada.
Canadian entrepreneurs, researchers and smaller businesses could gain access to capabilities they would never be able to finance themselves. If AI lowers the cost of creating companies, learning new skills and developing new products, a smaller economy can participate without matching U.S. frontier model spending dollar for dollar.
Canada is already debating how to keep more domestic intellectual property, capital and compute capacity while using global AI platforms. The country's AI sovereignty debate is partly about preserving enough domestic capability to avoid becoming only a customer of technology developed and controlled elsewhere.
A recent pro-human AI initiative backed by researchers, business and labour groups also argues for human agency, limits on concentrated power and accountability for AI companies. Zuckerberg reaches some similar principles from a very different starting point.
Canada needs enough choice, competition, data control and domestic capability for its companies and citizens to use increasingly powerful AI on their own terms.
Zuckerberg's bet is that superintelligence can give individuals more power to learn, invent, work and build. Meta has the reach and financial capacity to put that idea in front of billions of people. The cost of doing so is already putting heavy pressure on cash flow.Whether users ultimately gain more control will depend on who controls the models, data, compute and rules behind their personal AI.
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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Aug 13, 2026

Winter in Canada is long, cold, and difficult for recreational watercraft. The upcoming boating season for the Great Lakes, Muskoka waterways, and the coastal areas of British Columbia is just around the corner. Without proper spring maintenance, though, you can have a great first outing and end up with a costly rescue.
Prior to entering the lake, do a visual check of all major subsystems of propulsion equipment. If you currently have an old and worn-out outboard motor, or if it has cracks, you have to replace it with a new outboard motor before the high season starts. You can seriously consider looking into quality used outboard motors for sale in Canada. Here is the ultimate outboard motor checklist for safe operation on Canadian waters throughout the summer.
The top reason for engine failure to start up in the spring is due to fuel degradation. As Canadian ethanol blends sit in the atmosphere over time, they tend to separate, with water accumulating at the bottom of the fuel tank.
A clean and clear fuel delivery circuit ensures proper combustion performance and helps protect delicate engine parts from expensive varnish and corrosion issues.
Marine batteries will use up power even if disconnected if left in cold Canadian storage. Electrical continuity is important for starting, electronic fuel injection (EFI) control, and for operating critical navigation systems.
A fully charged, properly connected electrical network means no unwanted power outages away from the dock.
Clean spark plugs to ensure fast starting and optimal fuel economy during long runs across wide lakes.
Addressing ignition components proactively ensures effortless engine cranking and smooth throttle response on your first voyage of the year.
The lower unit gearcase houses delicate gear sets and bearings working under extreme pressure. Checking gear lube protects against catastrophic gearcase failure.
Regularly auditing your lower unit lubricant safeguards expensive internal drive gears against moisture intrusion and friction wear.
Outboard motors rely on raw lake or ocean water for cooling. Running an engine with a failed water pump impeller causes severe overheating within minutes.
Verifying proper water circulation safeguards your powerhead from sudden thermal breakdown during long high-speed runs.
Mechanical responsiveness keeps your vessel safe when docking or navigating changing weather conditions.
Fine-tuning your steering and propulsion linkage hardware guarantees precise handling and effortless maneuverability in tight docking situations.
Never start an outboard engine dry on land without a continuous water supply. Attach marine water muffs (flushing attachment) connected to a garden hose over the water intake pick-ups before starting.
Start the engine on the trailer and monitor the following:
By completing this thorough pre-season inspection, you protect your marine investment and ensure a safe, hassle-free boating season across Canada's waters.
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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August 12, 2026 | NCFA Market Activity | Artificial Intelligence And Data, Capital Markets And Market Infrastructure, Competition And Market Structure

On August 6, 2026, AMD agreed to acquire Taalas, a Toronto AI chip company that designs specialized chips to run individual AI models more efficiently. The price wasn't disclosed and the transaction hasn't closed yet, as it's subject to customary closing conditions and regulatory approvals.
AMD plans to bring Taalas technology into its accelerator portfolio alongside Instinct GPUs. That's a useful clue to the strategy. GPUs remain valuable because they can handle many models and workloads. Taalas gives AMD another option for cases where a model is used often enough that more specialized hardware could lower the cost of running it.
Running an AI model requires processors to work through huge numbers of stored parameters. On conventional accelerators, much of that data has to travel between memory and compute hardware. The transfers take time, consume power and make high bandwidth memory an expensive part of an AI system. Taalas brings more storage and computation onto the same silicon and tailors the hardware to the model being run. The design can reduce the external memory, advanced packaging and data movement required by conventional accelerator systems.
Ljubisa Bajic, Founder and CEO, Taalas:
“The production of optimal silicon for each individual model.”
Its first HC1 demonstrator runs Meta's Llama 3.1 8B model on a TSMC 6nm chip with 53 billion transistors. Taalas packages the system in a 2.5 kW server and currently provides access through a beta inference service and API.
The trade-off is straightforward. A GPU can be reprogrammed for many models. HC1 is largely built around one. It supports different context lengths and LoRA fine tuning, but a substantially different model requires another hardware implementation.
Taalas says it can turn a new model into silicon in about two months. If that process works economically at larger scale, AMD could use specialized chips for mature, heavily used models while keeping programmable accelerators for workloads that change more often.
Taalas says HC1 can generate about 17,000 output tokens per second per user on Llama 3.1 8B using a 1K input and 1K output sequence.
That's a company benchmark. Taalas ran its own HC1 result and measured the Nvidia B200 comparison itself, while several other comparison figures came from Artificial Analysis. It shows what the architecture can do on this model and configuration. It doesn't establish that Taalas hardware is faster than Nvidia or other accelerators across AI inference.
HC1 also uses a custom format combining 3-bit and 6-bit parameters. Taalas acknowledges some loss in model quality compared with GPU benchmarks and says its next generation will use standard 4-bit floating point formats.
The company also reports large advantages in power use and system cost in its comparison. Those claims haven't been independently demonstrated across a wide range of models or production environments. It makes the acquisition a calculated bet. AI companies are spending enormous amounts to train models, but every model that reaches widespread use can create an equally serious inference problem: how to serve millions of requests quickly enough and cheaply enough.
That pressure is already changing how AI infrastructure companies compete on cost and performance. Taalas gives AMD a way to explore much deeper specialization without abandoning the flexibility of Instinct.
Taalas was founded in Toronto in 2023 by Ljubisa Bajic, Drago Ignjatovic and Lejla Bajic. The team brought processor experience from AMD, Nvidia and Tenstorrent, which Ljubisa Bajic previously founded.
The company raised US$50 million before emerging from stealth in 2024 and another US$169 million in February 2026, bringing reported funding to about US$219 million. Investors included Quiet Capital, Fidelity and semiconductor investor Pierre Lamond.
Taalas says 24 people developed HC1, which shows how concentrated the engineering effort behind the first chip was.
The deal adds another company to Canada's growing AI hardware record. Toronto and Waterloo based Astrus is working on automated chip design, while Tenstorrent has built a much larger processor business from Toronto.
It also follows another major Canadian semiconductor transaction. U.S.-based Qualcomm agreed in 2025 to acquire Toronto-founded Alphawave Semi for US$2.4 billion, putting another Canadian-founded chip company under foreign ownership.
AMD will control Taalas if this acquisition closes, but it has also said it plans to retain and grow Canadian talent. There is no disclosed commitment to a specific Toronto headcount or to keeping Taalas as a separate company.
That makes the Canadian issue less about whether foreign capital is inherently good or bad and more about how much ownership, intellectual property and future economic value Canada retains as its AI companies scale. Canada's own AI strategy debate has put sovereign capital and domestic IP retention directly on the table.
Taalas raised more than US$200 million, built working silicon and attracted a strategic buyer in about three years. Canada can clearly produce teams and technology that global semiconductor companies want. The difficult question is whether enough domestic capital, procurement and infrastructure exist for more of those companies to scale further before selling.
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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August 10, 2026 | NCFA Market Activity | Payments Infrastructure And Money Movement, Competition And Market Structure, Capital Markets And Market Infrastructure

On August 10, 2026, RBC and BMO agreed to sell Moneris to U.S. technology investor Francisco Partners for approximately C$2 billion in cash. The banks own Moneris equally and are expected to receive half of the proceeds each.
The ownership change does not end their commercial relationship with the payments company. RBC and BMO will retain long term referral agreements with Moneris, preserving a route for business banking customers into its merchant services after the sale. RBC expects the transaction to close in the first quarter of its 2027 fiscal year. Until closing, Moneris remains owned by the two banks.
RBC and BMO can monetize an asset they created in 2000 without giving up the distribution value tied to their business banking franchises. Moneris continues to receive merchant referrals, while the banks no longer have to own the processor that supports those customers.
The relationship already has commercial depth. BMO clients using Moneris can receive next day deposits into eligible BMO business accounts and access offers tied to the bank relationship. Moneris says the BMO partnership has operated for more than 25 years.
The sale therefore separates two economics that have traditionally aligned together. That's owning the payments platform and controlling access to merchant customers.
RBC and BMO first explored a Moneris sale in 2025. The signed transaction now shows what the banks chose to keep.
TD took a different route last year when it transferred part of its merchant business to Fiserv. That agreement covered roughly 3,400 merchant relationships across 30,000 Canadian locations while TD continued offering merchant services through its banking relationship.
Both structures reduce direct bank ownership or operation of merchant processing while preserving access to business customers. They also show why counterparties are important. Fiserv is now under pressure after cutting its 2026 outlook again, extending the difficulties NCFA tracked after Fiserv's sharp market value decline. Selling infrastructure to a specialist does not remove execution risk. It changes who carries it.
Moneris gives Francisco Partners immediate scale in Canadian payments. The company says it supports more than 325,000 points of commerce across Canada and processes roughly one in three Canadian transactions. Its products span in store payments, ecommerce, point of sale software, integrated commerce tools, data and merchant services.
The ownership change impacts Canadian control. One of the country's largest merchant payments platforms is passing from two Canadian banks to a U.S. technology investor. Francisco Partners will control decisions around capital, product investment and growth, even as Moneris remains headquartered and operated in Canada.
After closing, Moneris will be foreign owned but remain Canadian operated. Francisco Partners will control the company, while Moneris is expected to retain its Canadian headquarters and technology infrastructure. That separates ownership of a major Canadian payments platform from where the business and infrastructure are based.
Moneris has also been adding newer payment capabilities. In June, it expanded Konek pay by bank access across Moneris Checkout and its API, allowing merchants to accept eligible bank payments alongside cards.
Francisco Partners already knows payments. Its portfolio includes Verifone, Paysafe and payments enablement provider NMI. The firm also closed $21 billion in new funds in July.
None of that guarantees more investment at Moneris or faster product development. Francisco Partners and Moneris will still have to decide where capital goes, which products deserve priority and how aggressively the company competes with global platforms.
Moneris will still face a crowded market after the ownership change. Stripe and Adyen compete heavily around online payments and developer tools. Fiserv uses Clover to combine acquiring with point of sale software and merchant services. Global Payments, Square and other platforms compete across different merchant segments, while Canadian firms such as Nuvei and Paystone add domestic pressure.
Moneris enters that contest with assets competitors cannot quickly reproduce, such as national merchant scale, deep Canadian distribution and long established bank relationships. Its BMO relationship alone includes integrated payment and banking services such as next day settlement.
The challenge is keeping those advantages relevant as payment acceptance becomes more closely tied to software, data and new payment methods. Moneris already partners with outside technology providers across ecommerce, point of sale and integrated payments, while products such as Konek add direct bank payment options alongside card acceptance.
Private ownership could give Moneris more room to invest across those areas. It could also increase pressure to produce stronger returns from a mature payments platform. Neither outcome should be assumed before Francisco Partners takes control and sets its priorities.
The referral agreements reduce one important risk. Moneris is entering private ownership while retaining the bank channels that helped build its merchant base. For RBC and BMO, that may be the strongest part of the transaction. They receive cash for the asset while retaining a commercial connection to the merchants that use it.
RBC and BMO are selling the processor while keeping merchant distribution. Francisco Partners gets the payments platform and the investment risk. The banks get C$2 billion and keep a route to business customers. Which side of that relationship will create more value in the future?
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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