Every regulated onboarding does two kinds of screening: sanctions, to make sure you are not doing business with a prohibited person or entity, and PEP checks, to flag politically exposed persons who warrant closer scrutiny. The build-or-buy question is usually framed as one decision. It is really three, and they have different answers. This sits inside the wider KYC/KYB verification stack.
What sanctions and PEP screening actually is
Sanctions screening compares a person or entity against lists of individuals and organisations subject to legal restrictions — OFAC, the EU and UN consolidated lists, and others — where a match is a legal bar to transacting. PEP screening compares against lists of politically exposed persons, where a match is not a prohibition but a signal to apply enhanced due diligence.
The distinction matters because the consequences differ: a true sanctions match is a hard stop, while a PEP match changes the level of scrutiny, not the decision to proceed. Treating them identically either blocks legitimate customers or under-scrutinises risky ones.
What you are really buying: data, matching, workflow
Screening is three components stacked. Data is the lists themselves, kept current as they change. Matching is the fuzzy logic that decides whether "Mohammed Al-Rashid, 1984" is the sanctioned "M. Al-Rashid, 1982" or a different person. Workflow is what happens next: alerts, case management, escalation, four-eyes review, and the audit trail that proves a decision was made and who made it.
Buy or build is a different question for each layer — and most teams that get this wrong answer the whole thing as one.
The case for buying
- List data is a full-time operational burden: dozens of lists, updated constantly, with coverage and quality guarantees you cannot easily replicate.
- Matching quality is hard to build well; false-positive reduction is where specialist vendors have spent years of modelling.
- You get live in weeks rather than months, which matters when a licence or a partner depends on screening being in place.
- Regulators recognise established providers, which simplifies your own risk narrative.
The case for building
- Workflow and case management are specific to your risk policy, your teams and your SLAs — and generic vendor tools force you into their process.
- When compliance is your product, the alert handling, audit evidence and policy configuration are things you want to own and shape, not rent.
- Multi-entity, multi-jurisdiction and multi-tenant rules rarely fit a single vendor’s model without customisation.
- An orchestration layer lets you switch or add data providers without re-touching everything built on top.
The hybrid most regulated teams land on
The pattern that holds up is custom orchestration and workflow over best-of-breed screening data. Buy the lists and the matching engine from whoever does it best; build the layer that decides what to screen, when, at what threshold, how alerts are handled and how the decision is recorded.
This keeps provider optionality — you can add a new list source or switch vendors without a rebuild — and keeps your compliance logic where it belongs, in code you control and can prove. It is the same approach we take across compliance and trust engineering.
How to decide
- If screening is peripheral to your product and you need speed, buy end to end.
- If list data is the only need, buy the data and matching; do not build list infrastructure.
- If your risk policy, audit requirements or multi-tenancy are specific, build the orchestration and workflow layer, and buy the data underneath it.
- Whatever you choose, own the audit trail: which lists ran, at what date, with what result and what action.
Key takeaways
- Sanctions screening blocks; PEP screening escalates. Model them separately in both policy and software.
- Separate the three layers — data, matching, workflow — because the build-or-buy answer differs for each.
- Most regulated teams should buy the data and matching, and build the orchestration and workflow they must prove to auditors.
Founder & CEO
Yashwant DanielYashwant Daniel writes on compliance and trust engineering, custom software delivery and applied AI at Solvstrat — covering how regulated and mid-market teams build systems that hold up under audit, scale and scrutiny.
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