Outsourced KYB review for banks and fintechs, done around the clock

Sweat AI is an AI-native BPO for banks and fintechs, and outsourced KYB review is our main service. Our analysts, working with AI tools, review your business onboarding applications 24/7 and return each one with the evidence behind every finding, a recommendation and a single list of what is still missing. Your team makes the decision.

This page covers what a review contains, what stays with you, what you receive, how the service compares with the other ways teams staff a KYB queue, and how an engagement starts. To see a finished review, read the annotated sample KYB review.

The problem this solves

Most KYB programs automate the easy part. A registry lookup, a sanctions screen and an identity check clear the straightforward applicants. What is left is the manual review queue: the holding company with a parent in another jurisdiction, the certificate of incorporation that does not match the name on the application, the website that describes a different business from the one in the form, the applicant who answered half of your questions.

Those cases need an analyst. They arrive unevenly, spike after a campaign or a partner launch, and pile up over weekends. Hiring for the peak leaves people idle in the trough. Hiring for the average leaves applicants waiting, and some of them leave.

Sweat AI takes that queue. We work it continuously, so the backlog stops depending on who is on shift, and we hand back reviews your team can decide on quickly because the evidence is already assembled.

Signs your queue needs outside help

• The oldest application in your manual review queue on Monday morning arrived on Friday or earlier.
• Analysts spend more time chasing documents than reviewing them, because each applicant gets several rounds of questions.
• Applicants that need investigation (layered ownership, foreign parents, unclear business models) wait longest, even though they carry the most risk.
• A partner launch, campaign or remediation project would double the queue, and you cannot hire for a peak that lasts six weeks.
• Case notes vary by analyst, so a reviewer or auditor cannot see what was checked, where or when.

If two or more of these sound familiar, the onboarding backlog calculator will put a number on it using your own inputs.

What's in a review

Every application is worked to your policy. A typical business onboarding review covers the following.

Entity verification

• The legal entity exists, under the name, number and jurisdiction on the application.
• Its status (active, dissolved, struck off) and formation date, compared with the history the applicant claims.
• Registered office and trading address, and whether they match what the applicant and its website say.
• Where the registry is silent or unreachable, that is recorded as a gap, never as a pass.

Ownership and control

• The ownership chain traced through each intermediate holding company to the individuals at the top, with direct and indirect percentages calculated and shown.
• Beneficial owners identified against your threshold. For US covered institutions the CDD rule sets the ownership prong at 25 percent or more of equity interests, plus a single individual with significant responsibility to control or manage the entity (31 CFR 1010.230). If your policy uses a lower threshold, we use yours.
• Control persons and directors, and whether the people named on the application match the people named in filings.
• Nominee arrangements, circular ownership and entities that appear only as a registered-agent address are flagged for your attention.

Screening

• The entity, its owners and control persons screened against the sanctions lists in scope, with each list's capture date recorded.
• Potential matches worked to a resolution with the identifiers that support or rule them out. A name that returns no match is recorded as an observation about the lists read on that date, not as a clearance.
• Politically exposed person and adverse media findings recorded with the source, the date and whether the story is an allegation, a charge or an outcome. See the glossary entries on adverse media and PEP.

Business model and activity

• What the business actually does, from its website, filings and public footprint, compared with what it says it does on the application.
• Whether the stated activity fits the product it is applying for and your risk appetite. For merchants this includes the merchant category and signs of undisclosed activity; see KYB for payments platforms.
• Expected volumes, counterparties and geographies, and whether anything in the public record contradicts them.

Documents

• Each document the applicant supplied is checked for entity match, date, completeness and what it can and cannot establish. A certificate of good standing proves status on a date; it does not prove who owns the company.
• Discrepancies between documents, filings and the application are listed, with the specific fields that disagree.

What stays with you

Outsourcing the work does not outsource the responsibility. Federal banking regulators say it plainly: a banking organization's use of third parties does not diminish its responsibility to operate safely and in compliance with law "to the same extent as if its activities were performed by the banking organization in-house" (Interagency Guidance on Third-Party Relationships, 2023). Fintechs operating under a partner bank's program carry the same expectation through their contract.

So the line is clear:

Our own Terms of Service say the same: our output is evidence for your review, and every decision and adverse action remains yours.

What you receive

Each completed review comes back as two things.

An evidence packet. Every finding is tied to the source it rests on: a quoted excerpt, the location of the record, the time it was captured and, where relevant, a content hash so you can show later exactly what the source said when we read it. Each finding also states its limitation, for example "registry extract shows shareholders as of the last annual filing; changes since then would not appear." Gaps are listed as gaps. The packet ends with a recommended disposition (approve, approve with conditions, request documents, escalate or decline) and the reason for it.

One consolidated request list. Instead of three rounds of follow-up emails, the applicant gets one list. Each item says what is needed, why it is needed and what an acceptable answer looks like. We only ask for what we could not find ourselves.

The sample KYB review walks through both, using an illustrative case.

How it compares

Teams usually choose between staffing the queue in-house, outsourcing it to a traditional BPO, or buying more software. Each is the right answer in some situations.

When each is the better choice:

• Keep it in-house if your volume is steady, your team has capacity, and you want every analyst on your payroll.
• Use a traditional BPO if the work is high volume, checklist driven and rarely ambiguous.
• Buy software if most of your queue could be cleared automatically with better data or orchestration. Software and Sweat AI often sit together: the tool clears what it can, and we work what it cannot.
• Use Sweat AI if your manual queue is uneven, spikes outside office hours, or is full of cases that need investigation rather than data entry.

For a deeper look at the trade-offs, see KYB tool or KYB team? our comparison pages, and the KYB review checklist.

Who it is for

• Payments companies, PayFacs and ISOs onboarding merchants (payments)
• Stablecoin and crypto platforms preparing businesses for banking and provider partners (stablecoin and crypto)
• Neobanks and BaaS programs opening business accounts under a sponsor bank (neobanks and BaaS)
• Community banks, credit unions and sponsor banks with business account or EDD backlogs (banks)
• Marketplaces and small-business lenders verifying sellers and borrowers (marketplaces and lending)

The team behind Sweat AI comes from Stripe, J.P. Morgan and Jefferies, and the company is backed by Alliance.

Coverage and escalation

The team works 24/7. Applications you hand over at the end of the day are worked overnight and over weekends, so the reviews are done when your team logs in. When a case is urgent or high risk (a likely sanctions match, signs of fraud, an applicant your policy says must be escalated immediately), we contact your named escalation contact as soon as it is found instead of waiting for the morning. Coverage terms and escalation paths are agreed with each customer. More on this in 24/7 onboarding review.

Engagement

Every engagement starts with a conversation about your queue: volumes, case mix, the products applicants are applying for, your policy and your escalation rules. We then agree how cases reach us (your case management tool, a shared queue or our workspace), what access we need and who to call.

We start with a first batch of your real applications. You review the packets, tell us where they do not match how your team works, and we adjust before taking more volume. Pricing depends on volume, case mix and coverage; talk to us and we will walk through it.

The step-by-step flow is on how it works. If you want to size your own queue first, try the onboarding backlog calculator.

Get your manual review queue worked tonight

If your KYB queue grows every weekend or your analysts spend their mornings chasing documents, Sweat AI can take it. We work it around the clock, hand back evidence your team can rely on, and leave every decision with you.