FCA Guidance 18/5 - a guide to managing open source media checks

Financial institutions have different approaches to Know Your Customer (KYC) programmes, especially when it comes to open source media screening.

There is a wealth of information available from these sources but they can be labour intensive to manage on a large scale. Irrelevant information needs to be consistently reviewed and ruled out, putting extra pressure on your analysts.

The recently updated Financial Conduct Authority (FCA) guidance on financial systems and controls (FG18/5) now requires firms to include open source media screening as a part of enhanced due diligence (EDD) programmes. How can this be successfully and consistently integrated without stretching your budgets and your resources? We give you five tips for the successful implementation of open source media checks in light of the updated FCA standards.

1. Have defined policies in place

As a starting point, creating an operational model with clear policies will give analysts a consistent model to follow. Guidance on which sources of media are searched as well as how internet searches are to be handled are necessary. Policies may also need to define how many adverse articles should be reviewed by analysts, balancing the risk with a pragmatic approach to resource management. Consideration should also be given to when a customer would be off-boarded if adverse information is found.

2. Consider your information sources

In today’s data-rich society there is a lot of potential information to review as part of an open source media check. But some sources are better quality than others. For most firms the internet is the initial step, using free search engines such as Google or Bing. This is a live search of the most up-to-date information via unstructured sources. The chance of false positives is high, so this data stream is likely to be time consuming for analysts to manage. Firms should also be aware that sponsored content, language constraints and not covering the entire web can affect the quality of this data.

Premium content in the form of subscription news services provides a rich source of live information. Available on a global basis, premium content providers offer a very rich stream of information at a cost. Some firms may also consider using other structured data sources, for example PEP databases. This should not be relied upon as a comprehensive media source to comply with FCA guidance.

3. Put things in context

Finding information about a new customer is only half of the picture. The information needs to be put into context, which involves involves a more detailed review of the articles deemed to be relevant. Firms must have a search string in place, used as part of the search process. This would include terms such as financial crime, fraud or criminal and is established by a firm’s risk strategists. Analysts will need to confirm that the article is not a homonym or a related party and that it is definitely the customer in question. In addition, analysts will need to determine if the risk terms are directly associated with the new customer, for example “Mr X was convicted of a criminal offence”.

4. Create an audit trail

Having a clear and auditable trail of the steps taken and decisions made as part of the screening process is essential. Firms may be asked by the FCA or customers for details of the decision-making process and this needs to be quickly accessible and tamper-proof. For firms working with manual systems, this can be a significant challenge given the volume of information that is being processed. encompass dynamically builds a complete audit trail, including source documents, for every search and action taken on a profile.

5. Utilize artificial intelligence and natural language processing

Technology can transform this process to achieve twin goals of guarding institutions against risks of money laundering and of reducing the cost of compliance. The first step is to put KYC experts at the center of the process where their judgment and decision making are put to best use. Then it is important to augment their work with machines using artificial intelligence (AI) and natural language processing (NLP) to do the heavy lifting of collecting media articles, checking their subject is the entity of interest, and prioritizing articles for human analysis by relevance to the institution’s risk strategy.