Verifying Sole Traders: Smarter Onboarding for One-Person Businesses

Verifying sole traders, often referred to as freelancers, self-employed professionals, or sole proprietors, presents a unique challenge for banks and fintech companies. These individuals operate independently, providing services or running small businesses under their own or registered trade names. While legally recognized as businesses, in practice, they resemble individual consumers, especially during onboarding.

That blurred line creates a compliance and operational gray zone. In many jurisdictions, particularly across the EU and the UK, sole traders are not required to register with official company registries. This means that the go-to verification method for small and medium enterprises—checking registry data—often fails or returns incomplete results. And yet, financial institutions are still expected to assess risk, prevent fraud, and remain compliant with anti-money laundering (AML) obligations.

As demand grows for fast, low-friction onboarding, verifying these one-person businesses with limited public records becomes a high-stakes balancing act: how do you screen for risk without overburdening legitimate users?

Why sole traders and single-owner businesses are hard to classify

Unlike incorporated companies, sole traders typically don’t operate with a formal business structure. Many don’t have a company number, are not listed in commercial registries, and rely on their personal name for invoicing, banking, and tax reporting. That absence of structure makes them harder to categorize—are they private individuals or business customers?

For onboarding teams, this creates tension. On one hand, sole traders are often seen as low-risk retail clients, particularly when onboarding happens through digital channels. On the other hand, they’re also requesting access to business banking services, payment tools, or credit products, making them subject to the same regulatory scrutiny as larger commercial entities.

They also span a wide range of sectors. Some of the most common types include:

• Consultants offering professional services
• Gig economy workers, such as rideshare drivers or delivery couriers
• Freelancers in creative and digital industries
• Self-employed tradespeople, from electricians to hairdressers

Despite their diversity, these individuals share one thing: their business identity is inseparable from their personal identity. That makes traditional business verification approaches less effective, especially when those checks rely on registry lookups or documentation that simply doesn’t exist.

The limits of registry data for sole proprietors and freelancers

For incorporated companies, national business registries are a foundational source of truth. They provide a structured way to verify ownership, check company status, and assess whether a business is real and operational. But when it comes to sole traders, those registries often come up short, or don’t apply at all.

In many EU countries and the UK, sole proprietors are not required to register their business with a commercial registry, especially if they operate under their own name. Even when they do register, the data available tends to be sparse: no beneficial ownership information, no indicators of business activity, and often no way to verify whether the business is currently trading.

This poses a clear problem for banks, fintechs, and other regulated institutions. Under the EU’s Anti-Money Laundering (AML) Directives, certain types of sole traders—particularly those operating in sectors like finance, crypto, real estate, and legal services—are considered obliged entities. That means they must be onboarded and monitored with the same level of due diligence applied to incorporated businesses.

And yet, the standard tools used for Know Your Business (KYB) checks—registry lookups, company filings, VAT verification—are frequently ineffective or inapplicable. The result is a gap in the onboarding process, where legitimate customers may be treated with unnecessary suspicion, and high-risk actors can pass through with little scrutiny.

This is precisely why financial institutions are now looking beyond registries and into richer, more dynamic forms of insight. As we explored in this article, registry data provides a structural view of a business, but not a behavioral one. To evaluate sole traders with limited documentation, open-source intelligence and alternative data sources are not just helpful—they’re essential.

What does a real sole trader look like?

When onboarding a sole trader or self-employed professional, the challenge isn’t just technical—it’s conceptual. These users don’t come with the same documentation or digital trail as incorporated businesses. So the question becomes: what exactly are you trying to verify?

For financial institutions, the goal isn’t to validate a company number—it’s to determine whether the individual behind the business is genuine, trustworthy, and low-risk. That breaks down into a few key questions:

• Does the business actually exist?
  Is there evidence—digital, behavioral, or otherwise—that this person is actively offering services or running a business?
• Is the person behind the business who they claim to be?
  Can their contact details, activity patterns, and digital footprint help support the legitimacy of their application?
• Are there any early signs of financial crime risk?
  Sole proprietors can be used as fronts for fraud, money laundering, or synthetic identity activity—especially if they’re operating across borders or in high-risk sectors.

In the absence of formal company records, these questions are answered through context—signals that paint a fuller picture of a user who exists somewhere between a consumer and a business. That might include digital footprint indicators, metadata around contact points, or behavioral clues tied to how the person interacts with the onboarding process.

Instead of chasing documentation that may not exist, onboarding teams can shift focus to something more realistic: building a confidence layer around limited information. That confidence doesn’t come from forms—it comes from signals.

How digital signals help verify sole traders and freelancers

When registry checks return nothing—or not enough—onboarding teams are left with limited inputs: a name, an email address, a phone number, and perhaps a trade name or personal domain. But even from these small details, a great deal of risk insight can be extracted—if you know where to look.

Digital signals turn passive inputs into contextual evidence of activity, legitimacy, and risk. They don’t require the user to submit more data. Instead, they focus on what’s already provided and how that information behaves across the wider digital ecosystem.

Phone number signals
Phone numbers are often taken at face value, but they’re rich with risk indicators. A newly issued or disposable number tied to a virtual operator may suggest the user is attempting to mask their identity. Risk increases further if the number appears in known breach datasets, or has been associated with other suspicious sign-ups. Porting history, operator type, and usage patterns all add depth to what would otherwise be a flat credential.

Email address data 
A real business email address often carries digital history. Trustworthy domains typically have verifiable owners, an established online presence, and visible activity tied to the name. In contrast, throwaway emails—often from free providers, registered recently, or tied to no other online presence—can be red flags. Additional OSINT signals like exposure in data breaches or links to fraud patterns help distinguish legitimate users from synthetic or high-risk profiles.

Domain presence (where applicable)
Some sole traders operate under a brand or trade name and maintain a business website. Even a basic domain check can reveal useful details: registration history, SSL setup, hosting provider, or whether the domain is connected to any active online footprint (reviews, social profiles, third-party listings). While not all self-employed professionals have a website, those who do offer another surface for digital evaluation.

IP and network signals
IP address behavior also offers verification clues. Risk rises when a session originates from anonymization tools, hosting services, or regions inconsistent with the claimed business location. Paired with browser and device fingerprinting, these indicators help establish whether you're onboarding a real user or a script designed to impersonate one.

These signals come together to fill in the blanks left by traditional KYB checks, helping institutions build a reliable risk picture without increasing onboarding friction. And because the data is passively collected without extra action from the user, it supports a faster, more seamless experience for legitimate applicants.

How to onboard self-employed professionals without the usual friction

Sole traders, freelancers, and other single-owner businesses represent a valuable customer segment, but they also pose a unique verification challenge. With limited registry data, minimal documentation, and a business identity often tied directly to an individual, the usual KYB methods fall short.

Financial institutions need to make confident, compliant onboarding decisions without alienating genuine applicants. That’s where a smarter approach comes in: one that treats available contact data not as static inputs, but as signals with behavioral and contextual value.

• Phone numbers, email addresses, domains, and device behavior all offer insights that registry data alone cannot provide. When layered into onboarding flows, these signals help financial services platforms identify high-risk accounts, detect synthetic patterns, and approve legitimate users faster without increasing friction.
• Trustfull brings these insights into focus, supporting onboarding teams with access to email intelligence, phone intelligence, and domain-level signals. Rather than requesting more from the user, these tools interpret what’s already there, helping teams assess risk early, invisibly, and more precisely.

For edge cases like sole proprietors and self-employed professionals, this kind of layered, digital-first verification isn’t a luxury—it’s essential. It ensures that low data doesn’t mean low confidence, and that valuable customers aren’t lost in the gaps left by outdated processes.