Understanding and Minimizing False Positives in PEPs, Sanctions & Adverse Media Checks

In the world of compliance and risk management, ensuring that your organization is not doing business with individuals or entities that are on PEPs (Politically Exposed Persons), sanctions, or have negative media coverage is of paramount importance. One of the key challenges in this process is the risk of false positives. A false positive occurs when a person or entity is incorrectly flagged or identified as a match for a PEP, sanctions list, or as having negative media coverage. These false positives can cause delays in business transactions, wasted time and resources, and even strain relationships between parties. In this article, we will look at some of the well-known providers of screening systems, the techniques that can be used to reduce the number of false positives, and the impact that false positives can have on business.

Overview of well-known screening system providers

There are several providers of screening systems that are widely used in the industry. Some of the most well-known include World-Check, Dow Jones Risk & Compliance, Thomson Reuters and ComplyAdvantage. These companies provide screening services to financial institutions, government agencies, and other organizations that are required to perform PEPs, sanctions, and adverse media checks. They typically use advanced algorithms and large databases to match the information of individuals and entities against lists of PEPs and sanctioned individuals, and to scan news articles and other sources of information for mentions of negative media coverage. However, there are also providers that include IDV and AML checks along with PEPs, sanctions & Adverse Media, specifically ID4-S.com.

Techniques to minimise false positives

There are a number of techniques that can be used to reduce the number of false positives in screening systems. Some of these include:

Sentiment search: This technique is used to identify the overall sentiment of a text. Sentiment analysis can be used to help determine whether a news article or other piece of text is positive, negative, or neutral. By understanding the sentiment of a piece of text, organizations can better understand the likelihood that a person or entity mentioned in it is actually involved in negative activity.

Semantic search: This is a method of searching through large volumes of text data, to find semantic meaning of the text. By using techniques such as natural language processing and machine learning, semantic search can help to understand the intent of text, and identify relevant concepts, entities, events and relationships, which can help to better identify false positives and negatives.

Tokenisation: This is the process of breaking text data into smaller, manageable pieces, called tokens. Tokenisation is used to simplify the text and make it easier for a machine to understand. By breaking text into tokens, organizations can search for specific words or phrases, which can help to identify false positives that might otherwise be missed.

Tuning the system's parameters: The screening system can be adjusted to reduce the number of false positives by adjusting certain parameters such as the matching threshold, which controls how similar a match must be before it is considered a positive.

Using multiple data sources: A screening system that relies on only one data source is more likely to produce false positives than a system that uses multiple sources to verify the information.

Human review: Having a person review the results of the screening system can help to catch false positives that the system may have missed.

Data: Adding additional fields of data and increasing the match criteria to make it more restrictive

Impact of false positives on business

False positives can have a significant impact on business operations and compliance efforts. When a false positive occurs, it can cause delays in business transactions, wasted time and resources, and even strain relationships between parties. Organizations may have to take additional steps to verify that a person or entity is not a match before proceeding with a transaction. This can include additional documentations requirements, follow-up investigations, and even legal advice. These additional steps not only consume valuable time and resources, but they can also disrupt business processes and slow down the overall workflow. In addition, false positives can create mistrust and a bad reputation between the parties involved. It's important to minimize the number of false positives that occur in order to prevent such negative impacts on business operations.

Conclusion:

In conclusion, false positives in PEPs, sanctions, and adverse media checks can have significant negative impacts on business operations and compliance efforts. It's crucial to minimize the number of false positives that occur in order to prevent delays in business transactions, wasted time and resources, and strained relationships. The providers like World-Check, Dow Jones Risk & Compliance, Thomson Reuters, ComplyAdvantage and ID4-S.com provides screening services that use advanced algorithms and large databases to match the information of individuals and entities against lists of PEPs and sanctioned individuals, and to scan news articles and other sources of information for mentions of negative media coverage. However, utilizing techniques such as sentiment search, semantic search, tokenisation, tuning the system's parameters, using multiple data sources, human review and adding additional fields of data can all aid in minimizing false positives. Furthermore, using a single platform such as ID4-S.com, that brings various service providers together can also give greater efficiencies and business advantages. It's important to take steps to improve the screening systems and reduce the number of false positives to gain the advantages and to meet compliance requirements.