Karsten Wenzlaff, Advisor
August 26th, 2025
August 19, 2026 | NCFA Resource | Cybersecurity And Fraud, Risk Compliance And Regtech, Capital Markets And Market Infrastructure

In August 2026, the Financial Industry Regulatory Authority published Cybersecurity Effective Practices, a 12-part framework for FINRA member firms reviewing cybersecurity programs, controls and operating procedures. A firm can use the resource as a structured checklist for who owns cybersecurity, which systems and vendors create risk, who can access sensitive data, how threats are detected, and whether the business can recover when systems fail. FINRA designed the practices to scale with firm size, business model, technology complexity and risk profile.
FINRA organizes the resource around 12 areas:
The framework starts with accountability and risk ownership. FINRA recommends a designated cybersecurity lead, regular reporting to senior decision makers, documented policies and periodic reviews, while also making cyber risk part of decisions about new technology, systems and operating changes. From there, firms are expected to identify the information, systems and business functions they depend on, assess threats such as ransomware, insider activity and vendor exposure, test important systems for weaknesses and revisit those risks when technology or operations change.
Third party risk receives detailed treatment. FINRA treats vendors with access to customer information or critical systems as part of the firm’s security perimeter. Firms should know which vendors have access, understand important fourth party relationships and identify which providers support critical operations. Contracts can address audit rights, data handling, breach notification and visibility into subcontractors, while ongoing oversight should include access monitoring and a documented process for removing access and handling customer information when a relationship ends.
That concern extends beyond US broker dealers. Weak access control governance can expose sensitive information when a partner or service provider retains permissions that are unnecessary or poorly monitored. FINRA’s guidance connects vendor governance with the practical question of who can access systems and data, for how long, and under what controls.
Asset management and access control fit naturally together. FINRA recommends keeping a current inventory of hardware, software, cloud services and data flows, assigning owners to important assets and identifying systems that no longer receive security updates. Once firms know what they have, they can control who gets access through unique credentials, role based permissions, multifactor authentication, periodic entitlement reviews, segregation of duties and least privilege. Access should also be changed or removed promptly when employees change roles or leave.
Data protection, training and patching cover another part of the operating picture. Firms are encouraged to classify sensitive data, encrypt it at rest and in transit where feasible, control retention and protect backups, including with immutable or air gapped storage. FINRA also recommends ongoing employee training, role specific instruction for staff with sensitive access and phishing simulations backed by records of participation. Vulnerability management should include regular scanning, risk based patch priorities and verification that remediation work was completed rather than assumed.
The primary users are FINRA member broker dealers, including compliance teams, cybersecurity leaders, technology teams, operations executives and senior management. Smaller firms can use the 12 areas to identify where basic controls are missing without trying to copy the cybersecurity program of a much larger institution, while larger firms can use the same structure to review whether responsibilities, documentation and technical controls are working together.
Technology providers, managed security firms, consultants and RegTech companies serving broker dealers can also use the resource to understand what clients may expect around access, logging, vendor controls, data handling, patching, incident response and recovery. Boards and senior executives can use it as a governance checklist because FINRA makes cybersecurity ownership, management reporting, resource decisions and documented risk acceptance part of the program rather than leaving cyber risk entirely with the technology team.
The main strength is that FINRA connects governance directly to operating controls. A firm can follow the framework from senior accountability through asset inventories, identity controls, encryption, training, monitoring and recovery testing, which makes the document more useful than a high level cyber policy statement.
Third party risk is also handled with more depth than a basic checklist. Firms are expected to understand vendor dependencies, monitor privileged access, address fourth parties and plan how systems and data will be handled when a provider relationship ends. Security monitoring extends that discipline to unusual access, suspicious data transfers, system changes and privileged accounts, with logs retained long enough to support operations, investigations, forensic work and applicable recordkeeping requirements.
The framework also includes threat intelligence, incident response and recovery. FINRA recommends using relevant threat feeds, updating defenses as attack methods change and participating in trusted information sharing networks. Incident response focuses on how a firm detects, escalates and contains an event, while recovery planning deals with how critical systems and data return to service afterward. Tested backups, tabletop exercises, offline procedures and defined Recovery Point Objectives and Recovery Time Objectives all help firms decide how much data loss and downtime different systems can tolerate.
The main limitation is jurisdiction. FINRA developed the resource for US member firms and connects several practices to US requirements, including SEC Regulations S-P and S-ID, FINRA Rules 3110 and 4370, and Exchange Act recordkeeping rules. The document also doesn't create new legal or regulatory requirements or reinterpret existing ones. For Canadian financial technology and service firms, its best use is as a practical comparison and control review, not as a statement of Canadian regulatory obligations.
FINRA Cybersecurity Effective Practices (12-part cybersecurity control framework)
Cybersecurity Effective Practices PDF (downloadable nine page resource)
Small Firm Cybersecurity Checklist (small firm program checklist last reviewed February 2024)
Core Cybersecurity Threats And Controls (small firm threats and control questions)
FINRA Cybersecurity Resources (cybersecurity tools, guidance and related material)
2026 Cybersecurity And Cyber Enabled Fraud (current threats and effective practices)
Proposed Class Action Targets Equifax Access Controls (access governance and third party permissions)
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: [www.ncfacanada.org](http://www.ncfacanada.org)
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |
```html
August 18, 2026 | NCFA Insight | Artificial Intelligence And Data, Payments Infrastructure And Money Movement, Digital Assets

On August 18, 2026, Amazon Web Services made AgentCore Payments generally available, taking the capability from its May preview into production. AI agents can now encounter paid APIs, services accessed through Model Context Protocol (MCP), or other digital resources during a workflow and initiate payment through infrastructure that connects spending controls with external wallets.
AWS can enforce how much an agent is allowed to spend and for how long, manage access to wallet providers and coordinate the payment from inside the same infrastructure used to run the agent. Coinbase or Stripe's Privy provides the wallet, while external providers and blockchain networks handle signing, verification and settlement.
AWS isn't taking custody of customer money. It is taking a position earlier in the transaction, where software determines whether it has permission to buy something and which payment connection to use. That puts payment authority closer to the AI execution layer.
AgentCore Payments already supported Coinbase and Privy wallets, spending controls and x402 payments during preview. General availability adds the Machine Payments Protocol (MPP), easier Coinbase wallet setup, improved discovery of paid x402 services and an x402 pricing option called upto.
The upto model is designed for services whose final cost isn't known before use. An agent can approve a maximum amount, while the provider charges for what was actually consumed. AWS points to model inference, compute and other usage-based APIs where a flat price per request may not reflect the real cost.
That fits how autonomous software may buy digital services. Instead of establishing a subscription with every provider in advance, an agent can encounter a paid resource during a task, check whether the price fits its delegated budget, pay for it and continue.
MPP adds another payment protocol. Developed by Stripe and Tempo, it lets software exchange payment requirements during an online transaction and can support different payment models, including microtransactions and recurring payments.
x402 takes a somewhat different approach. It lets an online service respond to an agent's request by saying payment is required before the resource is released. The agent can then authorize the payment through its connected wallet and retry the request.
Stripe says MPP can support stablecoins as well as conventional payment methods, but AgentCore Payments currently documents an embedded crypto wallet as its supported payment instrument.
The architecture adds useful boundaries around the word autonomous. A user or business first provides the wallet and grants authority. AWS then applies rules around how the agent can use that authority during a payment session. NCFA's Financial Innovation Map tracks this convergence of AI agents, financial permissions and programmable infrastructure.
Those controls can include an expiry and a maximum amount the agent is permitted to spend. Before a transaction proceeds, AgentCore checks whether the request fits within that budget. A payment that exceeds the limit is rejected at the infrastructure level rather than left to the agent's judgement.
AWS also keeps the wallet-provider credentials away from the agent itself. Coinbase or Privy provides the wallet infrastructure, while AWS uses controlled access to request operations such as signing a transaction.
The result is delegated spending rather than independent control of money. The person or business sets the authority, AWS enforces part of the operating boundary and the connected wallet provider controls the financial instrument.
AWS also records payment activity through its monitoring tools, giving developers logs and transaction information they can use to review what agents attempted and what payments succeeded. That adds an audit layer around activity that would otherwise be difficult to supervise once agents begin buying resources during longer workflows.
This is where AWS gains a potentially valuable position. It doesn't need to become a bank or payment processor to influence whether an agent-side transaction can proceed.
Coinbase is one supported provider, not an exclusive requirement. Its developer infrastructure provides embedded wallets and supports x402 payments, while Coinbase's Bazaar service helps agents discover online services that accept the protocol.
Coinbase documents payments in the USDC stablecoin on Base and Solana for its AgentCore implementation. That makes digital assets a substantive part of the current product architecture rather than a side effect of Coinbase's involvement. It also connects directly to NCFA's Programmable Stablecoin Payments opportunity brief, which examines programmable money movement and payment infrastructure.
Privy provides another embedded-wallet option. The company is now part of Stripe, but its role in AgentCore is still wallet infrastructure rather than ordinary card processing through Stripe's full payments stack.
AgentCore Payments doesn't require every payment protocol to use cryptocurrency, and MPP itself can support other payment methods. But AWS's currently documented AgentCore payment instrument is still a crypto wallet.
Payment companies therefore remain important underneath the agent platform. They provide the wallet, credentials and financial infrastructure needed to execute transactions, while AWS controls more of the environment where an agent decides when to call them.
This isn't the only infrastructure model emerging. Circle's USDC infrastructure for AI agents combines policy-controlled wallets, service discovery and programmable payments under predefined guardrails.
Travala provides a useful production example because its implementation shows where the customer's authority remains. Its current Travel MCP lets an AI agent search and book hotels, with payment settled in the USDC stablecoin on Base from a Coinbase wallet connected through AgentCore.
The customer still has to authorize the spending relationship. Travala says the permission is revocable and time-limited, the company never receives the private key and the customer must explicitly confirm the hotel purchase before payment is made.
Once that permission is in place, the agent can complete the payment within the delegated limits and continue the booking workflow. That is more precise than saying an AI agent independently controls money.
AWS also names Anchor Browser, SpreadX's Incarna, Elsa AI and Heurist AI among customers or integrations using AgentCore Payments. AWS does not provide transaction volumes for those implementations, so there isn't yet enough evidence to describe agent-led payments as broadly adopted at scale.
The Travala example is still important. It shows a live consumer transaction where conversational software can search, obtain approval and complete payment without sending the customer into a separate checkout flow.
Traditional electronic payments divide responsibility among merchants, gateways, processors, acquirers, networks, issuers and customer interfaces. Agent commerce adds another decision point before many of those functions because software has to decide whether a paid service is useful, whether the price is acceptable and whether the purchase falls within the user's authority.
AWS now controls part of that decision environment. It doesn't set the merchant's price, supply the customer's money or settle the transaction. It can, however, determine whether the agent's payment request fits its permitted spending session and coordinate access to the wallet needed to proceed.
That creates a new distribution question for payment companies. A wallet provider may still own the financial relationship underneath the transaction, while the cloud or AI platform controls the environment where an agent discovers a service and decides which payment connection to use.
AgentCore Payments still has important limits. AWS isn't providing general merchant acquiring, and its documentation doesn't establish native chargebacks, universal merchant controls or a standalone fraud-screening service inside AgentCore Payments. Those functions may remain with the merchant, application, wallet provider or other payment infrastructure.
Control of the agent execution environment can still become valuable payment real estate even when the platform never holds the money. If agents increasingly choose services and initiate purchases on behalf of users, the infrastructure governing those decisions becomes another point where payment providers compete for access.
AgentCore Payments is currently available in 12 AWS regions across the United States, Europe, Singapore and Australia. AWS does not currently offer the capability from its Canadian region, even though several other AgentCore services are available there.
That creates a practical constraint for Canadian developers that want to keep this part of the stack in an AWS Canadian region. They can deploy AgentCore Payments elsewhere, but there is no Canadian region for the capability today.
The longer-term issue for Canadian fintechs and financial institutions is less about one AWS region and more about where financial authority is being placed. Agent payments combine AI governance, delegated spending, wallets and payment infrastructure inside one operating workflow.
Firms will need to decide which controls remain inside their own applications and which can be delegated to cloud, wallet and protocol providers. That becomes more important as agents gain permission to buy services during a task rather than simply recommend what a person should buy.
If AI and cloud platforms control the environment where agents receive spending authority and decide whether a transaction can proceed, while payment companies provide wallets and settlement underneath them, which layer will ultimately control distribution in agent-led commerce?
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 18, 2026

Markets have a few gauges that traders keep open even when they are not planning to trade them. The Nasdaq 100 is one of those gauges. It tends to get attention before the US session, during earnings weeks, and on days when rates or technology shares move hard.
Part of that comes from the companies inside the index. The Nasdaq 100 includes many of the names people already know from software, chips, cloud services, online retail, and consumer devices. When traders change their view on those companies, the index often shows it quickly. That is why the index can be useful even for people who are not trading it that day.
The Nasdaq 100 tracks 100 large non-financial companies listed on the Nasdaq exchange. Because the index leans toward technology and other growth businesses, it can move differently from broader benchmarks that include more banks, utilities, and industrial stocks. A broad index may look calm while the Nasdaq 100 is already showing stress in growth shares.
That mix gives the index a sharper edge. It may rally when traders feel more confident about growth and future earnings. It may also sell off quickly when rate expectations rise or when a large company warns that demand is slowing. The same feature that makes the index interesting can also make it uncomfortable to hold through rough sessions.
For active traders, those swings can create setups. For people watching the wider market, they can also show how much risk investors are willing to take. A strong Nasdaq 100 session can point to renewed appetite for growth stocks. A sudden drop can signal a more cautious mood, especially around inflation data, central bank comments, or major earnings results.
Price movement in the Nasdaq 100 rarely comes from one headline. Traders usually look at company news, macro data, and the general tone of US equities before deciding whether a move has staying power. A rally based only on one strong stock may fade faster than a move supported by several sectors inside the index.
Those drivers can overlap. A company may report strong revenue but still fall if margins disappoint or if traders think interest rates will stay high. Another stock may rise on weaker numbers because expectations were already low. That is why Nasdaq 100 moves often need context rather than a quick headline reading.
For many traders, the index is a shorthand for how the market is treating large growth companies against the current economic backdrop. It is not a perfect economic signal, but it can show whether investors are leaning toward risk or stepping back from it.
Trading platforms make that monitoring easier than it used to be. A trader can keep charts, watchlists, alerts, price data, and instrument details in one place instead of jumping between separate screens. That convenience matters when the market is moving and a slow check can lead to a late decision.
This is useful when the market starts moving quickly. One earnings report, one change in rate expectations, or one sharp move in US equity futures can change the tone of the session. Traders following the Nasdaq 100 usually want to see price levels, spreads, recent volatility, and related news before they place an order.
Someone comparing index products can use Vantage's nas100 page to check instrument details, pricing context, and platform access before deciding whether the market fits their plan. That page is not a trading signal. It is a reference point for understanding the product before putting money at risk.
Good platform habits are usually boring, but they matter. Traders may set alerts near levels they care about, check the daily range before deciding position size, and compare current spreads with what they normally see. None of that predicts the next move. It simply reduces the chance of entering a trade without knowing the basic conditions.
A chart helps, but it is only part of the job. Traders also need to know how the instrument behaves on the platform they use. That includes the typical spread, order types, margin requirements, and how quickly prices can change during busy sessions.
Risk controls deserve the same attention as the setup. Stop-loss orders, position sizing, alerts, and account limits can keep a market view from turning into oversized exposure. That matters even more with index-based products, where leverage can magnify losses as well as gains.
Execution is another practical issue. In quieter sessions, prices may move in a fairly orderly way. During data releases or earnings headlines, the same market can become much harder to read. Watching how a platform handles those moments can be as useful as watching the chart.
A simple pre-trade routine can help. Check why the index is moving, decide where the idea is wrong, and know the maximum loss before entering. Traders do not need a complicated checklist, but they do need a repeatable one. Without that, a fast market can turn a reasonable idea into a rushed reaction.
The Nasdaq 100 is easy to follow because many of its companies are familiar. That familiarity can be misleading. Knowing the names in the index does not protect a trader from sudden gaps, sharp reversals, or bad timing. A familiar company can still move in a way that surprises even experienced traders.
Past moves do not guarantee the next one. A pattern that worked during one earnings season can fail in the next. A level that held last month can break when macro conditions change. The index is liquid and closely watched, but that does not make it predictable.
Used carefully, Nasdaq 100 price action can help traders understand the mood around growth stocks and wider equity risk. It works best alongside product research and a clear risk plan. Preparation matters more than prediction, especially in a market where speed can make confidence look better than it really is.
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 17, 2026 | NCFA Market Activity | Capital Markets And Market Infrastructure, Wealth Investing And Trading, Competition And Market Structure

National Bank is modernizing its fund and ETF accounting infrastructure with Multifonds, bringing work handled across separate systems onto one platform.
On August 11, 2026, Multifonds announced that National Bank of Canada had selected Multifonds for fund and ETF accounting after an evaluation and proof of concept.
The project gives National Bank one accounting environment for more of the valuation, NAV and ETF administration work it performs for firms that offer investment funds and ETFs.
National Bank provides fund and ETF administration services that include fund accounting, transfer agency, ETF basket creation, financial statements and tax support.
Multifonds Global Accounting brings fund and ETF accounting into one environment. It processes data in real time and uses exception based workflows so operations teams can focus on records that need review.
The platform includes more than 350 configurable controls across NAV, valuation and distribution work. Multifonds says it supports more than 40,000 funds across 35+ jurisdictions.
National Bank plans to replace siloed systems with the platform. Multifonds expects the change to reduce manual steps, improve oversight and support faster product onboarding.
While those are the expected benefits, the results will depend on how the platform performs once National Bank moves more accounting work into production.
ETF administration involves more than calculating a fund's value. National Bank also supports transfer agency, market makers and the creation of ETF baskets.
Those processes depend on accounting records and outside data staying aligned. Multifonds connects ETF accounting with more automated data exchange, giving National Bank a common system for more of that work.
Canada's ETF market has grown sharply. Canadian ETFs attracted a record C$122 billion in net inflows in 2025, up 62% from the previous record, and Canadian ETF assets reached about C$790.5 billion by the end of March 2026.
Canada's ETF market has grown sharply. Canadian ETFs attracted a record C$122 billion in net inflows in 2025, while industry assets approached C$800 billion in early 2026.
The market is also under closer regulatory review. The CSA consultation on Canadian ETF rules examines areas including unit creation and redemption, ETF trading, NAV alignment and basket practices.
That growth means more products, valuations, baskets, records and exceptions for administrators to process. Automation can reduce repetitive work, but controls still have to catch problems before incorrect data reaches fund managers, trading partners or investors.
The same operating challenge appears in tokenized fund operations. New ways to issue or transfer fund interests still depend on reliable pricing, accounting, investor records and administration.
National Bank is investing in a part of the market where other large Canadian asset servicers are also spending on technology.
In April, CIBC Mellon expanded its Appian automation program. Planned improvements include a more digital ETF service and fund administration workflows designed to reduce manual work and improve data visibility. CIBC Mellon reported more than C$3.4 trillion in assets under administration as of March 31, 2026.
RBC Investor Services reported C$3.1 trillion in assets under administration in the second quarter. Its asset servicing technology investments include ETF modernization, automated reconciliations and predictive reporting.
These investments highlight competitive pressure. Fund administrators need to support more products and data without adding manual work at the same rate.
Technology can influence how quickly an administrator launches products, handles exceptions and gives clients access to accurate information.
National Bank is also using specialist technology in other operating areas. Its Sardine fraud controls deployment focuses on fraud and financial crime rather than fund administration, but both projects use specialist technology for high-volume financial operations.
Moving more fund and ETF accounting onto one platform can simplify operations, but it also increases dependence on that platform.
National Bank will need strong data quality, integrations, controls and recovery processes as the implementation expands. If a shared accounting system fails, the adverse impacts can amplify and reach more funds and ETF workflows at once.
As Canadian asset servicers automate more fund and ETF administration, will technology become a bigger factor in which providers win new business?
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 17, 2026

A mid-size alternative lender in Vilnius pulls company registry filings, marketplace pricing and sanctions lists into its underwriting model every night. None of it is illegal to read. Most of it becomes a liability the moment it is copied, stored and combined with something else. That gap between "publicly visible" and "lawfully processed" is where fintech compliance teams keep losing arguments with their own data science departments.
Public web data – company filings, marketplace listings, court dockets, sanctions databases, social media bios – has become a standard input for credit scoring, fraud detection, KYB and competitive pricing in financial services. In Meta Platforms v. Bright Data, a federal district court held that Bright Data had not breached Meta's terms of service by collecting data from logged-out pages, which was the specific conduct at issue. The ruling turned on Bright Data's particular conduct and its contractual relationship with Meta rather than establishing a general rule for scraping public websites. For a regulated entity, that distinction is not academic. A bank's third-party risk team, an EU DORA auditor or a state attorney general does not care whether the data was "technically public" if the collection method itself created exposure.
hiQ Labs v. LinkedIn is still the reference case for US practitioners, and it is more nuanced than the headlines from 2019 suggest. The Ninth Circuit held twice, first in 2019 and again on remand in 2022, that scraping data from pages open to any visitor does not amount to accessing a computer "without authorization" under the Computer Fraud and Abuse Act. That took the CFAA off the table as a criminal exposure for reading public pages. It did not end the case. hiQ and LinkedIn settled the remaining contract claims in 2022, and hiQ agreed to destroy the data it had already collected and pay damages, because its scraping still violated LinkedIn's user agreement. The lesson for a fintech legal team is specific: CFAA risk and contract risk are two separate questions, and winning on one does not close the other.
On the EU side, the CFAA question barely matters, because GDPR does not distinguish between public and private personal data. Article 4 defines personal data by whether it relates to an identifiable natural person, not by where it was found. A LinkedIn bio, a court filing with a defendant's name, or a marketplace seller profile with a real name attached all fall inside GDPR's scope the moment they are collected, and Article 6 still requires a lawful basis – legitimate interest is workable for adverse-media or fraud screening, but it requires a documented balancing test, not just a note in a Confluence page.
Four use cases account for most of the public-data traffic coming out of fintech data engineering teams. Alternative underwriting pulls e-commerce store metrics, invoice marketplaces and gig-platform ratings to score borrowers who lack conventional credit files – Kabbage and, later, Amex built entire product lines on this. AML and sanctions screening cross-references OFAC, EU and UN lists against onboarding data, refreshed daily because list updates are unscheduled. Competitive pricing intelligence in embedded finance and BNPL tracks merchant-facing rates across marketplaces to benchmark interchange and fee structures. Fraud and adverse-media screening checks court records, press mentions and social profiles as a secondary signal alongside device fingerprinting.
Not all four carry the same regulatory weight. The table below is the one compliance teams actually need before greenlighting a collection project, not a generic "data source" taxonomy.
| Data source | Typical fintech use | Regulatory sensitivity | Main legal basis to check |
| Company registries (Companies House, EDGAR, EU BRIS) | KYB, beneficial ownership checks | Low to medium | Public register rules and applicable data protection law; filings may contain personal data of directors, officers, beneficial owners and other natural persons |
| Sanctions and PEP lists (OFAC, EU, UN) | AML/KYC screening | Low | Government-published, but update frequency and source authenticity matter |
| E-commerce and marketplace pricing | Competitive intelligence, embedded-finance pricing models | Low to medium | Terms of service and contract law; CFAA exposure may be lower for pages accessible without login (per hiQ v. LinkedIn) |
| Public social media profiles | Alternative credit signals, fraud indicators | Medium to high | GDPR/CCPA personal-data rules apply even if the profile is public |
| Court records and litigation databases | Adverse media, fraud investigation | High | Jurisdiction-specific rules on re-use of judicial data (varies widely, e.g. France's Article 33) |
The engineering choices matter as much as the legal analysis, because a regulator or a bank's third-party risk assessor will ask for logs, not intentions. A defensible pipeline has five properties, and they map to concrete infrastructure decisions rather than policy statements.

Figure 1
Figure 1. Each control maps to an artifact a third-party risk assessor can actually inspect. The first four are described below; request logging is the fifth, and the one the practical takeaway returns to.
Reading a site's robots.txt crawl-delay directive and setting concurrency accordingly is a five-minute engineering task that changes the legal character of the whole program. A crawler hitting a company registry at 200 requests per second looks like a denial-of-service test to the target's security team, regardless of what the data is used for afterward. Most production fintech scrapers we've reviewed cap at 1 request per 2-4 seconds per domain, which keeps CPU load on the target negligible and avoids the WAF triggers that generate abuse complaints in the first place.
This is the point where proxy infrastructure choice stops being a procurement decision and starts being a compliance decision. Rotating through residential or datacenter IPs to maintain a stable success rate against rate limits is standard engineering practice. Rotating IPs specifically to re-access a source after being blocked for a terms-of-service violation is the fact pattern that turned hiQ's win on CFAA into a loss on contract claims. The distinction sounds semantic until an opposing counsel reconstructs your request logs during discovery.
Filtering personal identifiers (names, emails, phone numbers, biometric-adjacent fields) before the data lands in a warehouse is materially cheaper than filtering it after ten analysts have already queried the raw table. A regex-and-NER pass at the collection layer, logged with a timestamp and a rule version, is the artifact a DPO can actually show an auditor.
GDPR's storage limitation principle (Article 5(1)(e)) and most US state privacy laws expect a defined retention period. "We keep everything indefinitely for model retraining" is the single most common finding in the DPIAs we've read for alt-data underwriting programs, and it is usually fixable with a 90-180 day rolling window plus a documented exception process for flagged accounts.
Proxy and scraping infrastructure choice affects three things a compliance file will ask about: whether the vendor itself runs KYC on IP sourcing, whether the billing model matches your actual usage pattern (per-IP monthly vs. per-GB bandwidth), and whether the vendor's own terms indicate the network is ethically sourced rather than built from compromised devices.
| Provider | Billing model | Entry price | Where it fits a fintech workload |
| Proxys.io | Per dedicated IP / month | From $1.40/mo (individual IPv4), $0.13/mo (IPv6) | Steady, low-volume monitoring jobs (registry checks, sanctions list refresh) where a fixed, auditable IP per data feed is easier to log than rotating bandwidth pools |
| Decodo (formerly Smartproxy) | Per GB, tiered | $2.00-$3.75/GB depending on volume | Mid-volume scraping across many source domains where bandwidth, not IP count, is the cost driver |
| Oxylabs | Per GB, sales-assisted | Roughly $8/GB at entry tier, KYC required before provisioning | Enterprises that want a vendor-side KYC record as part of their own third-party risk file |
| Bright Data | Per GB (PAYG or committed) | $8.40/GB PAYG residential, down to ~$3/GB committed; datacenter from ~$0.90/GB | Large, multi-region collection programs where volume discounts offset the higher entry rate |
The billing model split matters more than the headline price. A sanctions-list refresh job that hits the same twelve government sources every night at a predictable, low volume is a poor fit for per-GB bandwidth pricing – you're paying for a metric (data transferred) that has almost nothing to do with your actual constraint, which is IP reputation and consistency of access over time. Vendors like Proxys.io bill per dedicated IP per month, which lines up better with that access pattern and makes cost forecasting for a fixed set of monitored sources straightforward. A marketplace-pricing crawl that touches thousands of product pages across dozens of domains is the opposite case: bandwidth is the real cost driver, and a per-GB model from Decodo, Oxylabs or Bright Data scales more predictably with that workload. Enterprises already running Oxylabs' or Bright Data's own KYC process may lean on that as one input to their own vendor risk assessment, though it doesn't substitute for one.

Figure 2
Figure 2. The two variables that move cost are how many domains a run touches and how much data it moves, not the headline price per unit. Per-IP and per-GB rates are quoted in different units and cannot be compared directly.
None of these vendors, including the ones with published ethics or KYC pages, remove the fintech's own obligation to define a lawful basis, log what was collected, and honor retention limits. The proxy layer solves an availability and reliability problem – consistent access to public pages without disproportionate load on the source – not a data protection problem.
Three signals usually mean a proxy or scraping setup needs to change, independent of price. First, a rising block rate on sources with unchanged rate limits – that's an IP-reputation problem the vendor's pool has accumulated, not something a compliance policy fixes. Second, the compliance team asking for source-level access logs the engineering stack can't currently produce – that's a signal the collection layer needs structured logging before it needs a new vendor. Third, a shift in workload shape, for example moving from a handful of steady, low-volume registry checks to broad multi-domain marketplace crawling, which usually means the per-IP pricing that worked for the first case stops making sense for the second.
A fintech data program built on public web sources holds up under regulatory review when three things are documented before the first request is ever sent: the lawful basis for each data category (not a blanket justification), the technical controls that keep collection proportionate to the source (rate limits, minimization, retention), and a request log detailed enough to reconstruct what was collected and why if a regulator or a counterparty's third-party risk team asks. The infrastructure vendor is a smaller decision than most procurement processes treat it as – it changes reliability and cost, not the underlying legal analysis.
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
![]() | ![]() | ![]() |
|---|---|---|
![]() | ![]() | ![]() |