Checklynx Sanctions and PEP Customer Screening Reviews

From one side, we have the onboarding of new customers, which involves discovering their UBOs, the owners of those companies, and screening those owners against sanctions and Politically Exposed People, along with conducting adverse media background checks for the owners. The second part involves allowing payouts and moving funds in and out of the business account, necessitating continuous ongoing monitoring through Checklynx Sanctions and PEP Customer Screening. Basically, you upload a list of customers or create a list of customers, and then those customers are monitored against sanctions continuously. If any sanctions are detected or any alerts arise, you receive an email notification, allowing you to check the situation on the dashboard. There is a case that you can open and manage, as it's very important to record every decision to understand what happened with this case, who worked on it, how it escalated, how it was resolved, and whether it was a false positive or not, especially since we may face audits from the government.

We can search in batches of 200 customers per second without noticing any latency, so it scales quite well.

First of all, the data quality is very high. The data is structured in standardized ISO, which makes it very easy to integrate with our current workflow. When we get results, those results are clusterized, so it's much faster to quickly understand any open case. The coverage is really more than we need, making it very competitive in that sense.

We save approximately 30 to 40 percent on review time for the reasons I mentioned before. Firstly, there are fewer false positives due to the clusterized profiles, which makes the filters work more effectively. The compliance officer has one profile to check instead of 12 separate results, making it much easier compared to the tool we had before. Additionally, since every decision is recorded in the system, we do not have to worry about compliance or regulatory inquiries regarding why we made specific decisions.

Other tools give you all the results, which means you get all kinds of false positives from people who are not from that country or that birth year. However, with the clusterized results provided by Checklynx Sanctions and PEP Customer Screening, there's an algorithm that consolidates the raw results and removes all the raw results that don't belong to that person, so you won't even see those false positives. You will only get the real cluster profile, and for each cluster profile, you will receive the original sources with all the information. That is how they achieve a reduction in false positives.

There is a feature that we don't really use, which is the CSV upload and scheduled screening. It might be useful for smaller companies or companies that don't need as much integration, but we don't really use it.

Although we don't need that feature at the moment, having ID verification would be a very good asset that we might find useful in the future.

Since we started, we have never experienced any downtime. The API hasn't changed either; it has expanded with more endpoints, but none of those introduced any breaking changes or anything like that.

We can search in batches of 200 customers per second without noticing any latency, so it scales quite well.

Previously, we were using a tool called Sanctions.IO. For audits, we can export all decisions taken for any customer when requested, including transactions, onboarding, and ongoing monitoring. All decisions can be exported for a single customer, allowing us to deliver that information to the relevant body.

It was very easy. At the beginning, we used the API for certain workflows, and the developer documentation was very clear, enabling us to use the codecs for implementation. We also have in-house agentic workflows, for which we utilized Checklynx Sanctions and PEP Customer Screening MCP.

It was straightforward.

We have a basis to compare with other tools we used before. Checklynx Sanctions and PEP Customer Screening really excels in quality, and the price is about twice cheaper than that of the last provider.

First, check if the company is reselling data or if they own the data, as that's going to be a very important factor for quality and price. Also, check how they claim to reduce false positives, because some companies make claims but don't have a way to substantiate them. I rate this solution five out of five stars.