Whether you’re building an innovative fintech product or new digital banking experience, onboarding business customers is an opportunity to make a great first impression while also ensuring the integrity of your platform.
Unfortunately, onboarding is too often treated like an administrative hurdle: verify the business, collect a few documents, move them into the queue. But in reality, onboarding is one of the most important customer experiences you’ll ever deliver. Get it right, and you set the stage for trust, growth, and long-term revenue. Get it wrong, and you may never hear from that business again.
Here are seven common onboarding inefficiencies we see across fintechs, neobanks, and financial institutions — and what you can do to fix them.
1. Treating all business customers the same
Every company is unique. But many platforms apply one-size-fits-all verification logic, regardless of risk or complexity.
The problem: Your onboarding flow doesn’t adapt based on business type, risk level, or legal structure.
Why it hurts: A sole proprietor doesn’t behave like a VC-backed Delaware C-corp, and they shouldn’t be onboarded like one either. When you apply the same rigid process to every business, you create unnecessary friction for customers who just want to get started. At the same time, you risk under-scrutinizing high-risk or suspicious entities.
How to fix it: Build adaptive, automated onboarding flows that adjust based on the inputs you collect. For example, if the business is a sole prop, skip formation document requests and lean on tax ID validation. If it’s a high-risk industry or the entity has unusual patterns, route it for review. Your default experience should be seamless for low-risk businesses — and smart enough to escalate when something looks off.
2. Relying on incomplete or outdated data sources
A KYB check is only as good as the data it relies on. If your system pulls from limited, outdated sources, you’re making decisions without seeing the full picture.
The problem: Your verification tools pull from narrow, static databases that miss context and recency.
Why it hurts: Fraudsters exploit stale or low-quality data sources. They create shell companies, spoof legitimate businesses, or hijack real identities — and legacy tools often can't tell the difference. Worse, real businesses sometimes get caught in the crossfire because of minor mismatches or outdated records.
How to fix it: Don’t rely on a single source of truth. Layer multiple authoritative data sets — like Secretary of State records, business licenses, and federal registries — with real-time monitoring of web data, sanctions lists, and behavioral red flags. The more complete the picture, the better your decision-making.
3. Forcing manual reviews that could be automated
Many ops teams are drowning in review queues. Why? Because the system can’t tell the difference between a clear case and a suspicious one.
The problem: Every flagged case is reviewed by a human, even when the decision is obvious.
Why it hurts: Manual reviews slow everything down. They create backlogs, stretch thin operations teams, and delay access for legitimate customers. For fast-moving fintechs, this is a serious bottleneck — and it doesn’t scale.
How to fix it: Automate the easy stuff. Build rules to clear low-risk businesses that match authoritative records. Use manual reviews only for cases with conflicting data, fraud risk indicators, or edge-case entity types. This not only reduces queue pressure but also improves accuracy by letting your team focus on the complex issues that deserve their attention.
4. Requiring excessive documentation up front
Collecting documents may feel like a safe way to ensure compliance, but it introduces unnecessary friction when the same information could be verified elsewhere.
The problem: You ask for too much, too soon — EINs, licenses, formation docs — before verifying whether they’re even necessary.
Why it hurts: Legitimate businesses drop off when onboarding feels like a paperwork scavenger hunt. It’s especially painful for small businesses and sole proprietors, who often don’t have those documents on hand — or know why they’re being asked for them in the first place.
How to fix it: Only ask for documents when data verification fails. If a Secretary of State record confirms the entity's good standing and officer names, don’t force them to upload a formation certificate. Pre-fill where possible, verify behind the scenes, and reduce requests to the bare minimum needed for compliance.
5. Delaying onboarding until verification is complete
Many onboarding flows make users sit in limbo until they’re fully verified. For customers, this can feel like being stuck on hold.
The problem: Your product doesn’t begin until every KYB box is checked, frustrating would-be business customers.
Why it hurts: If users can’t see any value before clearing onboarding, they’re more likely to churn — especially if the process is slow or confusing. This is where fintechs lose high-intent leads for good.
How to fix it: Offer a “soft start.” Let users explore the dashboard, configure settings, or access non-sensitive features while verification runs in the background. Use UI cues to set expectations (“Your account is almost ready — we're just verifying a few details”) to keep users in-the-know and engaged during the waiting period.
6. Building onboarding flows around exceptions, not the majority
It’s important to plan for edge cases, but too many teams design their entire onboarding around the 5% of users who create the most risk or complexity.
The problem: You design your entire onboarding process to handle the riskiest, messiest 5% of businesses.
Why it hurts: You end up punishing the other 95% with a slow, over-engineered experience.
How to fix it: Start with the best-case onboarding journey. Make it as fast and seamless as possible for legitimate business customers. Then, add layers for the edge cases: higher-risk industries, unusual entity types, or mismatched records. This reduces drag without compromising your risk strategy.
7. Failing to learn from your onboarding data
You can’t improve what you don’t measure. But too many teams have no visibility into where or why business customers are dropping out of the onboarding flow.
The problem: You don’t track where customers drop off, which documents cause delays, or how long verifications actually take.
Why it hurts: Without data, there’s no feedback loop to improve your systems. Meanwhile, friction points persist and your ops teams spin their wheels while customers fall through the cracks.
How to fix it: Instrument your onboarding funnel like you would a revenue funnel. Track step-by-step completion rates, document rejection reasons, time-to-verification by business type, and manual review rates. Use this data to test and improve continuously, just like any other conversion flow.
Make onboarding count for your customers and your business
The fastest way to lose business customers is to treat them like a problem to solve. But when onboarding is fast, flexible, and designed for how real businesses operate, it becomes a growth engine. By simultaneously building trust with new business customers and protecting against fraud, you start every customer relationship on a path of long-term success.
At Middesk, we help banks and fintechs design onboarding that works for compliance, for operations, and most importantly, for your customers.
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Ready to onboard faster and reduce risk? Chat with our team to see how Middesk can help.
