PEP Screening for AML Compliance in Europe: How to Run Efficient Checks

For fintech and crypto companies entering the European market, PEP screening is one of the required KYC checks that often raises the most questions.

On paper, the requirement looks straightforward. In practice, however, teams quickly discover that manual PEP screening does not scale, while poorly implemented automation leads to false positives, false negatives, and unnecessary onboarding friction.

We’ll look at how PEP screening is usually implemented, where teams run into problems, and how it can be operationalised more efficiently with Allpass.ai as part of an automated KYC flow.

What is PEP Screening in KYC and What the EU Requires

PEP screening is the process of identifying customers who qualify as Politically Exposed Persons. These are individuals who hold, or have held, prominent public functions, as well as their close family members and known associates.

The purpose of politically exposed persons screening is to identify elevated risk and apply additional controls where appropriate.

In the European Union, PEP screening is mandated as part of the broader AML and KYC framework. The requirement originates from the EU Anti-Money Laundering Directives and has been further reinforced by the Sixth Anti-Money Laundering Directive (6AMLD).

Under this directive, obliged entities are required to:

• identify whether a customer or beneficial owner is a PEP.

• distinguish between domestic and foreign PEPs.

• apply a risk-based approach, rather than automatic rejection.

• conduct Enhanced Due Diligence (EDD) where higher risk is identified.

• perform ongoing monitoring of the business relationship.

These requirements are aligned with the recommendations of the Financial Action Task Force, which serve as a global reference point for PEP-related controls.

PEP Screening vs Sanctions Screening vs Adverse Media

PEP screening is often discussed alongside sanctions screening and adverse media checks. While these controls are frequently implemented together within KYC and compliance workflows, they serve fundamentally different purposes and are driven by different regulatory expectations.

In the European Union, obliged entities are expected to apply all three controls, but not in the same way, and not with the same outcomes in mind.

Conflating these checks — for example, treating a PEP match as equivalent to a sanctions hit — results in overly rigid decision-making that is neither required by regulation nor aligned with a proportional, risk-based approach.

Therefore. It’s important to understand the differences to build compliance processes that are effective, proportionate, and scalable, and not unnecessarily restrictive.

3 Ways PEP Screening Can Be Done

The choice of the PEP screening approach is not only a compliance decision. It directly affects customer experience, internal operations, and how a brand is perceived.

The 6AMLD does not define how PEP screening should be operationalised; it is totally up to you. What matters for the regulator is the outcome. AML PEP screening can be done in three ways.

1. Fully Manual PEP Screening

In a fully manual model, compliance teams identify potential PEPs by searching public sources, official lists, and internal databases without the support of specialised screening tools.

Pros:

• Full control over decision-making.

• High contextual awareness in individual cases.

• Suitable for very low volumes or exceptional cases.

Cons:

• Does not scale with business growth.

• Time-consuming and resource-intensive.

• High operational cost per customer.

• Inconsistent outcomes across reviewers.

• Increased risk of human error and missed updates.

2. Manual Review Supported by a PEP Solution

In this model, automated tools like KYC software or standalone PEP screening solutions are used to identify potential PEP matches, but final decisions are made manually by compliance officers. The system provides data, alerts, and context, while humans remain responsible for assessment and escalation.

Pros:

• Better coverage and consistency than fully manual screening.

• Access to structured PEP data and updates.

• Improved auditability and documentation.

• Allows for contextual, risk-based decisions.

Cons:

• Still requires significant manual effort.

• Review queues can grow quickly as volumes increase.

• Decision-making speed depends on team capacity.

3. Fully Automated PEP Screening

In a fully automated approach, PEP screening is integrated into onboarding and monitoring workflows. Matches are assessed using predefined risk rules, scoring models, and escalation logic, with manual intervention limited to high-risk or exceptional cases.

Pros:

• Highly scalable and cost-efficient

• Fast and consistent decision-making

• Reduced manual workload for compliance teams

• Enables ongoing monitoring at scale

• Clear, repeatable logic for audits and reviews

Cons:

• Requires careful configuration and ongoing tuning

• Poorly designed automation can lead to over-flagging

• Less flexibility in handling truly exceptional cases without escalation paths

How PEP Screening Impacts Brand Risk in Europe

PEP screening is often viewed primarily through a regulatory lens. In practice, however, the way it is implemented has a direct impact on brand risk, customer trust, and long-term business reputation. This is particularly true for the European Union, where principles such as proportionality, fairness, and transparency play a central role.

When PEP screening is poorly calibrated, the resulting risks extend well beyond compliance.

Overblocking Legitimate Customers

One of the most common issues is overblocking — treating PEP status as a de facto reason for rejection. While regulation requires enhanced scrutiny, it does not require exclusion.

Automatically declining PEPs can lead to the loss of legitimate customers and create the perception that the business applies blanket restrictions rather than individual risk assessment. From a brand perspective, this signals rigidity rather than responsibility.

Unexplained Delays and Friction

PEP-related reviews are frequently routed to manual processes. When these reviews are slow or poorly communicated, customers experience unexplained onboarding delays.

In a competitive market, delays are rarely interpreted as a compliance necessity. Instead, they are perceived as inefficiency, lack of professionalism, and low product maturity. Over time, this erodes trust, even among customers who ultimately pass the checks.

Perceived Discrimination and Unfair Treatment

In Europe, heightened sensitivity around equal treatment and proportionality means that how compliance decisions are applied matters almost as much as the decisions themselves.

When PEP screening lacks nuance or context, customers may perceive inconsistent treatment and bias based on nationality or public role. This creates reputational exposure that extends beyond individual cases and can affect brand perception more broadly.

Lack of Transparency in Decision-Making

Many compliance processes operate as a “black box” from the customer’s point of view. When PEP screening outcomes cannot be reasonably explained — internally or externally — businesses struggle to justify their decisions to customers, partners, or even regulators. This can greatly undermine the brand’s credibility.

Best Practices for Accurate and Scalable PEP Checks

To run PEP checks accurately without creating unnecessary friction or manual overhead, we suggest a few concrete design choices.

Сontext at the Point of Review

One of the main reasons PEP screening produces noisy results is the lack of contextual information when a match appears. If a compliance officer sees only a name match, escalation,

A more effective setup ensures that additional context is available at the moment a decision is made, not later in the process. This typically includes information about the role held, whether the position is current or former, and the jurisdiction in which the public function applies.

When this context is visible upfront, teams can distinguish between cases that genuinely require enhanced due diligence and those that can proceed with standard controls without delaying onboarding.

Clear Escalation Criteria

Even with good data, PEP screening becomes inconsistent if escalation rules are unclear. When teams rely on ad-hoc judgment, similar cases are handled differently, which increases both operational risk and brand exposure.

Best practice is to define, in advance, which types of PEP exposure require additional steps and which do not. For example:

• senior public roles with active influence may trigger enhanced due diligence;

• former or low-influence roles may require monitoring but not escalation.

Clear criteria reduce decision fatigue, speed up reviews, and make outcomes easier to justify during audits or internal reviews.

Ties to a Verified Identity

Another practical issue arises when PEP screening is performed independently from identity verification. Name-based checks alone increase the likelihood of false positives for common names and create blind spots when identity manipulation is involved.

Linking PEP screening to verified identity data — such as document verification combined with liveness and face matching — helps ensure that screening results correspond to the actual applicant, not just a textual match. This significantly improves accuracy without adding complexity to the decision process.

Traceable and Explainable Decisions

In the European regulatory environment, decisions are rarely evaluated in isolation. Regulators and auditors look for consistency and rationale over time.

A practical PEP screening setup should therefore make it easy to understand:

• what data was available at the time of review;

• why a case was escalated, approved, or monitored;

• how similar cases are handled across the organisation.

This reduces both regulatory and reputational risk, especially as teams scale and onboarding volumes increase.

Flexible Automation for Scaling

PEP screening typically involves checking applicants against multiple pep & sanction databases and continuously updated sources.

Manually processing these lists becomes impractical as onboarding volumes increase, and introduces a high risk of missed updates or inconsistent results.

To scale effectively, organisations need a solution that can:

• process large numbers of applicants automatically.

• keep screening data up to date across multiple sources.

• support configurable rules and escalation logic.

• allow human review where judgment is required.

Automation is not about removing human oversight. It is about making consistent, high-quality screening possible at scale, while preserving the flexibility required for a risk-based approach.

How Allpass.ai Supports PEP Screening at Scale

Applying best practices in PEP screening is relatively straightforward on paper.

The real challenge begins when teams need to apply them consistently across hundreds or thousands of applicants, while keeping processes auditable, flexible, and aligned with regulatory expectations.

This is where Allpass.ai comes in.

Allpass is a comprehensive KYC platform designed to help fintech and crypto companies operationalise PEP screening as part of a broader, risk-based onboarding flow — without relying on fragmented tools or manual workarounds.

A Single Flow Instead of Disconnected Checks

Rather than running document verification, sanctions screening, and PEP checks across separate systems, Allpass.ai brings them together into one configurable onboarding flow.

All screening results, enrichment data, and review outcomes are stored in a single applicant profile. This gives compliance teams full visibility into what checks were performed, what data was retrieved, and warning signs.

It is also a lot cheaper to maintain a single screening system compared to using multiple tools. A typical setup often includes document verification priced at around $1–3 per applicant and PEP or sanctions screening costing an additional $0.50–2 per check.

For a company onboarding a few thousand users per month, this can easily translate into several thousand dollars in recurring costs, not including engineering time and manual compliance effort. Instead of layered pricing and additional fees, Allpass.ai offers predictable plans starting from $199 per month, with no extra charges for integrations or core compliance checks.

Automation that Supports Growing Customer Database

As already mentioned, a key part of AML compliance in Europe is not only initial screening, but ongoing monitoring. Regulators expect businesses to continuously check their customers against PEP & sanction sources throughout the entire business relationship.

In practice, this is one of the hardest requirements to fulfil manually. A customer who is not listed today may appear on a sanctions or PEP list tomorrow. Tracking such changes across thousands of customers and hundreds or thousands of data sources quickly becomes unmanageable without automation.

In Allpass.ai, ongoing monitoring takes just a flip of a switch. Once enabled, the system regularly rechecks customers against more than 5,000 sanctions and PEP lists, and adverse media, ensuring that status changes are detected as they occur.

As a result, compliance teams can maintain continuous coverage even as the business scales. Growth in customer numbers does not translate into a proportional increase in manual workload, allowing organisations to meet regulatory expectations without expanding compliance headcount or relying on ad-hoc processes.

Context-First Screening to Reduce Noise

One of the key factors affecting PEP screening accuracy is which data is used at the moment the check is performed.

Relying on name matching alone is rarely sufficient — especially when dealing with common names — and often leads to both false positives and false negatives.

In Allpass.ai, PEP screening is designed to be context-first by default. During the verification step, the system automatically extracts core identifiers such as full name and date of birth directly from the identity document. These data points are then used together for screening, rather than as standalone inputs.

For more customised onboarding flows, additional flexibility is available. If a company collects relevant information through our questionnaires, these data points can also be used as screening inputs. This allows PEP checks to be performed using the most reliable and contextually appropriate data available for a given use case.

As a result, screening accuracy is improved by design, not through stricter rules or broader matching.

To Sum Up

PEP screening does not have to be a separate, time-consuming process that slows down onboarding or overwhelms compliance teams.

With Allpass.ai, PEP screening, sanctions checks, and identity verification can be handled within a single KYC flow. If you’re building or rethinking your KYC setup for Europe, you don’t need to overcomplicate PEP screening.

Try Allpass.ai and see how risk-based PEP checks fit naturally into your onboarding flow.