Karsten Wenzlaff, Advisor
August 26th, 2025
Aug 28, 2026

Image: Unsplash/Jakub Żerdzicki
Artificial intelligence is rapidly changing the way individual investors interact with financial markets. Tasks that once required hours of reading reports, comparing charts, or building spreadsheets can now be compressed into a few prompts or clicks.
Modern AI investing tools can summarize market news, screen thousands of securities, identify unusual price movements, compare financial metrics, analyze sentiment, and even help investors test trading ideas.
That convenience is valuable. But it also creates a new problem: when sophisticated analysis appears instantly on a screen, it is easy to confuse speed with reliability.
For investors, the real opportunity is therefore not simply finding the most advanced AI. It is learning where AI adds value, where it can fail, and which decisions should always remain subject to independent due diligence.
The term covers a surprisingly broad range of financial technologies.
Some tools use machine learning to identify patterns in historical market data. Others apply natural language processing to earnings reports, central-bank announcements, news stories, or social-media discussions. Generative AI assistants can explain financial concepts, summarize research, compare investment ideas, or help users create screening criteria.

Image: Pexels/Matheus Bertelli
In practice, retail investors are likely to encounter AI across several areas:
The important distinction is that these tools do not all perform the same job.
An AI assistant that summarizes an earnings call should be evaluated differently from an algorithm that generates trading signals. Likewise, a portfolio risk analyzer presents a very different level of financial consequence from software capable of automatically executing trades.
One of the easiest mistakes is choosing an impressive AI application before deciding what problem actually needs to be solved.
A better approach is to begin with a specific investment task.
| Investment task | How AI may help | What still needs human verification |
|---|---|---|
| Researching a company | Summarize filings, news and earnings calls | Financial statements and original disclosures |
| Finding opportunities | Screen large datasets quickly | Whether the screening logic makes economic sense |
| Monitoring markets | Detect unusual changes or sentiment shifts | Why the change occurred and whether it matters |
| Managing risk | Analyze correlations and portfolio exposure | Personal risk tolerance and liquidity needs |
| Comparing trading platforms | Organize fees, features and trading conditions | Regulation, execution quality and actual costs |
| Generating trade ideas | Identify historical patterns | Whether the pattern remains relevant today |
This simple framework changes the role of AI.
Instead of asking, “What should I invest in?”, an investor might ask, “Which companies in this sector have improving margins, declining debt and positive free cash flow?”
The second question gives AI a defined analytical task rather than handing it an open-ended financial decision.
AI is particularly useful when the bottleneck is information volume.
Imagine following several currencies, commodities, central-bank decisions and economic indicators. Reading every announcement manually can quickly become impractical. An AI system can summarize information and highlight developments that may deserve closer attention.
But summarization is not the same as verification.
A model may misunderstand context, rely on incomplete information, overlook a change that occurred after its underlying dataset was created, or confidently present an incorrect conclusion.
That leads to a useful rule:
AI should reduce the amount of information you need to inspect, not remove the need to inspect important information altogether.
For consequential decisions, investors should return to primary sources whenever possible.
If an AI summary says a company changed its guidance, verify the announcement. If it claims a central bank changed policy, read the official statement. If it identifies an unusual fee or condition at a financial platform, confirm it directly with the provider.

Image: Pexels/Tiger Lily
This distinction becomes especially important in actively traded markets such as forex.
AI can help an investor analyze inflation data, interest-rate expectations, currency correlations, technical indicators or market sentiment. None of those capabilities, however, answer another fundamental question:
Where will the trade actually be executed?
Broker selection involves a different set of variables:
These factors should be researched independently from any AI-generated market signal.
For example, an investor researching the trading infrastructure available in the forex market can use an independent comparison resource such as iamforextrader.com/en/forex-brokers/best/ as one starting point, and then verify relevant regulatory and account information directly with the broker and applicable regulator.
The principle applies beyond forex as well. A good investment idea and a trustworthy platform are two separate questions.
Every financial model has boundaries.
Traditional quantitative models depend on the variables selected by their designers. AI systems may work with much larger datasets, but they still operate within informational limits.
Before trusting an AI-generated conclusion, consider five questions:
The last question is especially important.
The more authority an AI system receives, the higher the standard of oversight should become.
A useful financial tool should help users understand why a result appeared.
Suppose two platforms both generate a “buy” signal.
Tool A explains that the signal resulted from improving earnings expectations, falling valuation multiples and increasing free cash flow.
Tool B simply displays:
AI Confidence Score: 94% — Strong Buy
The second interface may look more sophisticated, but it actually gives the investor less useful information.
An unexplained confidence percentage can create false precision. Without knowing the inputs, methodology, testing conditions or assumptions behind a signal, users cannot properly evaluate its reliability.
This is why explainability matters in financial technology.
Investors do not necessarily need access to every line of code, but they should be able to understand the basic logic behind a recommendation.
AI trading products often attract attention with historical performance.
Backtesting can certainly be useful. It allows investors and developers to see how a strategy would have behaved under previous market conditions.
But historical success can become misleading when a model has effectively been optimized to explain the past.
This is known as overfitting.
A strategy may perform exceptionally well because it has learned patterns that happened to exist in a particular dataset rather than patterns likely to persist in future markets.
When evaluating a data-driven strategy, look beyond headline returns and ask about:
A backtest that ignores realistic trading costs is particularly questionable for strategies that trade frequently.

Image: Pexels/cottonbro studio
AI investing tools can also create privacy and cybersecurity considerations.
Investors should be cautious about entering sensitive information into general-purpose AI systems, particularly:
Before connecting any application directly to an investment account, understand exactly what permissions it receives.
Read-only portfolio access is very different from permission to execute trades or transfer assets.
The principle of least privilege works well here: give a financial application only the access it genuinely needs.
Investors do not need to choose between artificial intelligence and traditional research. The two can complement each other.
A practical workflow might look like this:
Step 1: Use AI for discovery.
Screen markets, identify unusual developments or generate research questions.
Step 2: Ask for reasoning.
Request the factors behind the conclusion rather than accepting a score or recommendation.
Step 3: Verify important facts.
Check financial statements, regulator databases, company announcements and original economic data.
Step 4: Challenge the thesis.
Ask what could make the investment idea wrong.
Step 5: Evaluate execution conditions.
Understand fees, liquidity, spreads, platform risks and regulatory protections.
Step 6: Size the risk independently.
A high-confidence AI prediction should never automatically determine how much capital is placed at risk.
This workflow turns AI into an analytical assistant rather than an autonomous decision-maker.
The evolution of AI investing tools is part of a broader transformation in fintech.
Retail investors increasingly have access to analytical capabilities that were once expensive, technically difficult or available mainly to professional institutions. That democratization of financial technology can improve access to information and make research considerably more efficient.
But better technology does not eliminate uncertainty.
Markets still respond to changing expectations, unexpected events, human behaviour and information that models cannot perfectly anticipate.
The investors who benefit most from AI may therefore not be those who automate the greatest number of decisions. They may be those who learn to divide the investment process intelligently between machines and humans.
Let AI search faster, process more information and challenge assumptions.
Keep verification, risk tolerance and final accountability human.
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
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |
August 28, 2026 | NCFA Insight | Regulation And Policy, Capital Markets And Market Infrastructure, Wealthtech Investing And Trading, Risk Compliance And Regtech

On August 27, 2026, the Canadian Securities Administrators (CSA) and Canadian Investment Regulatory Organization (CIRO) issued new guidance on sports and entertainment event contracts. The CSA says those contracts belong outside securities and derivatives regulation, and CIRO will not approve dealer members to trade them.
The decision closes the securities-dealer route without banning every sports prediction market category under every Canadian law. Gaming and other applicable rules can still determine what is permitted elsewhere, but Canadian investment dealers now know sports and entertainment will not join the event contracts they can distribute through CIRO.
CIRO currently allows two investment dealers, Wealthsimple Investments Inc. and Interactive Brokers Canada Inc., to facilitate a limited set of contracts tied to economic forecasts, environmental outcomes and financial indicators. Permitted contracts generally need at least 30 days to maturity, clients cannot use leverage, and elections, referendums, political nominations and other political events remain prohibited.
In the U.S., sports category helped prediction markets reach a much larger audience. Prediction Markets Tighten As Wealthsimple Enters noted in March that a March Madness winner contract had already exceeded US$100 million in volume and 2026 Super Bowl contracts topped US$1 billion. Canada is now explicitly removing that demand interest from the securities-dealer channel.
That leaves economic, environmental and financial contracts to prove they can generate repeat participation and enough liquidity to remain useful. Rates, inflation, housing and climate outcomes can carry real forecasting value, but they don't naturally produce the same frequency, fan interest or habitual trading as professional sports.
Platforms are also experimenting with how prediction markets are presented. CRSHMARKET's livestream prediction-market model combines live video, creators and event contracts to make participation more immediate. That doesn't change Canada's regulatory limits, but it highlights why product format is important to growth if permitted contracts have to compete for attention without sports.
A contract within CIRO's permitted categories can potentially reach Canadian clients through an authorized investment dealer, while sports and entertainment contracts cannot use that route. Product teams therefore need to understand the event being priced, the applicable regulator and the distribution rules before estimating the addressable market.
As a result, the need for regulated event contract infrastructure is more valuable. Platforms need compliance controls, market surveillance, outcome verification, settlement and dealer integration, but they also need to know which contracts can be offered through which channel.
Infrastructure providers that help firms classify products, apply the right controls, integrate regulated distribution and settle outcomes can serve multiple markets even when the permitted contract set differs by jurisdiction.
CSA and CIRO say they are still assessing other types of event contracts. They haven't said which additional categories may eventually fit inside securities and derivatives regulation or which will remain outside it.
Those decisions will help determine the size of Canada's regulated prediction-market business. If CIRO dealers remain concentrated on economic, environmental and financial indicators, the sector may develop mainly as a forecasting and investment product. Additional permitted categories could create more reasons to trade and more opportunities for liquidity to build.
Regulators still need to consider market manipulation, insider information, outcome integrity and whether a particular event belongs inside financial regulation at all.
Can Canadian prediction markets build enough liquidity around economic, environmental and financial events without the sports contracts that helped drive U.S. adoption?
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
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |
August 26, 2026 | NCFA Market Activity | Capital Markets And Market Infrastructure, Regulation And Policy, Risk Compliance And Regtech

On August 19, 2026, CRSHMARKET promoted a wider vision for its livestream prediction market, where people can put money on events while a stream is still unfolding. Its campaign showed markets around dates, public interactions and creator content, while the live product currently remains concentrated in video games such as Rocket League and Among Us.
The format is built around speed. Users enter dollar amounts on short yes-or-no outcomes and some markets can settle within minutes. When checked on August 26, CRSHMARKET on-chain volume showed about US$7.79 million in cumulative USDC entry volume across current and earlier contracts. DefiLlama says each entry is counted once and treasury seed liquidity is excluded.
What happens if the product expands beyond esports into creator-led livestreams where the person on screen can affect what traders are betting on?
Prediction markets already have to manage insider information. Creator-led markets add another problem because someone close to the content may be able to influence the result itself.
A market on whether a streamer gets someone's phone number, spends more than $100 or completes a stunt can involve people who know more than the audience. The creator, production staff, guests or friends may know what is planned. Some may also be able to change what happens.
There's already a useful precedent. A Kalshi insider trading case resulted in a financial penalty and two year suspension after an internal editor traded on markets connected to MrBeast videos he worked on. Kalshi's surveillance tools and user reports helped identify the activity.
Livestreams compress that problem into a much shorter window. The event is happening now, viewers are trading now and the market may settle before a platform has much time to investigate. Controls therefore need to identify who is close enough to the event to have an unfair advantage before suspicious trading becomes the only warning.
<
| Risk | Why Livestreams Make It Harder | What Platforms Need |
|---|---|---|
| Inside information | Creators, guests or production staff may know what is coming | Restricted accounts and connected party checks |
| Outcome manipulation | People on the stream may be able to change the result | Creator rules and limits on controllable markets |
| Disputed results | Live video can be unclear, interrupted or open to interpretation | Clear settlement rules and independent evidence |
CRSHMARKET has already written some of these concerns into its operating rules. Its published CRSHMARKET Bonus Terms allow identity, age, location, wallet, payment and source-of-funds checks before promotional funds are paid or withdrawn. The terms also identify collusion, automated accounts, location masking and creator manipulation as reasons to cancel promotional value or restrict future eligibility.
Those are promotion rules rather than a complete public rulebook for every market, so they don't establish how all livestream disputes or conflicts will be handled. They do show that CRSHMARKET recognizes creator manipulation and connected-account behaviour as operating risks.
In the U.S., prediction markets can operate within the CFTC regulated derivatives framework, but that protection depends heavily on how the contracts and venue are structured. CRSHMARKET does not appear to be a CFTC registered exchange, so creator led livestream markets could still raise federal derivatives, state gambling and market manipulation questions.
The regulated event contract infrastructure opportunity tracks demand for surveillance, conflict detection, audit trails, settlement tools and dispute handling as prediction markets grow. Creator-led markets make those capabilities more valuable because the event, the people controlling it and the traders can be closely connected.
Some markets may also need to be excluded entirely. For example, when a trader can influence the event they are betting on, an issue already explored in prediction markets on controllable events.
For CRSHMARKET, speed is part of the attraction. It can turn ordinary moments inside a livestream into something viewers can trade almost immediately. The commercial model becomes stronger if creators gain another way to monetize audiences and viewers find the markets entertaining enough to return.
But they'll need to show that people close to an event cannot quietly trade on better information, creators cannot steer outcomes for financial gain and disputed results can be settled consistently. If it can do that, livestream prediction markets could create a new category of interactive financial entertainment. If it can't, the integrity issue may limit the model before the audience does.
If livestream prediction markets expand beyond esports, can platforms build controls fast enough to separate genuine audience participation from markets where creators or insiders can influence the outcome themselves?
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
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |
Aug 20, 2026

Source: Canva Editor
When it comes to online slots Canada has to offer, players are spoiled for choice. They can try their luck on slot games at locally licensed online casinos as well as casino sites based in other countries. The number of options for online gambling is huge, and it's constantly growing.
If a player’s lucky enough to win, naturally they want to get hold of their winnings as soon as possible. This used to take a fair bit of time, but nowadays the wait time has been dramatically reduced.
Deposits at Canadian casino sites are nearly always instant. Simply choose a payment method, enter a deposit amount and confirm the transaction. The money should then be added to your casino balance. You can now use it to place bets on slots and other games available at the casino.
Withdrawals, however, are different. This is because there are two stages to the withdrawal process, both of which can take some time. First of all, the casino site has to process your withdrawal request once you make it. The amount of time this takes varies depending on the site you’re at.
Some online casinos in Canada have fast processing times of a few hours or less. At others, you’re looking at a wait time of one or more working days for your withdrawal request to be processed. Many Canadian players prefer sites where the processing happens on the same day in a matter of hours. The quicker it’s done, the better.
Once this first stage is complete, your money will be on its way to you. The amount of time it takes to reach your bank account depends on the payment method you’re using. As with processing, some options can get your money to you in a matter of hours; for others, the wait time can be several days or even longer.
Interac, which launched in the mid-1980s, was one of Canada's first shared electronic payment networks. It came about thanks to the country’s key financial institutions coming together to create a shared cash dispensing system. Over the years, the usage and capabilities of Interac have both grown significantly.
Nowadays, Interac is the go-to option for all sorts of payments (both offline and online) throughout Canada. It enables people in Canada to make seamless bank transfers and is also used by businesses and banking systems. The popular payment method is widely accepted as an option for deposits and withdrawals at Canadian casino sites.
One such site is ToonieBet, which stands out thanks to its extensive collection of over 5,000 casino games. This site, which is licensed by the Tobique Gaming Commission, has a generous welcome package lined up for new players. This gives them the chance to claim up to $3,500 in bonus money and 200 free spins. Anyone who’s lucky enough to win can cash out using Interac and get hold of their money in next to no time.
Thanks to Interac, Canadians are used to money matters being sorted out quickly, not slowly. With many casino sites offering Interac as a payment option, Canadians expect withdrawals to reach them fast, as standard. When looking for a new casino site to join, people in Canada take the withdrawal times into consideration as a key factor. If the wait time’s too long, they’ll find another site where withdrawals reach them more quickly.
Withdrawals haven’t always been quick. For many years, the average wait time for withdrawals at Canadian slot sites was noticeably longer. It was common for cashing out to take multiple working days, not just a few hours like it can do today. Even when withdrawals took longer, the money was still on its way to the player.
These days, people are accustomed to getting things sooner rather than later. They’re used to instant gratification. When it comes to casino site withdrawals, players want their money to come through as quickly as possible, which is perfectly reasonable. The longer their money is ‘on the way’, the more of a chance there is that something will go wrong. There could be a technical issue or some sort of delay could make the withdrawal wait time even longer.
When the overall withdrawal time is short, things are less likely to go wrong. There can still be issues, of course, but they should be minimal. If someone knows their withdrawal is going to be quick, they’ll have less to worry about than if the withdrawal time was long.
Fast withdrawals increase a player's satisfaction and establish trust in the casino. Knowing that withdrawals will be handled reliably gives players one less thing to worry about when choosing where to play.
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
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |