1. Clarify Timing

Monitoring every single news source 24/7 might be the most bulletproof way to capture all adverse media, but it is neither practical nor sustainable.

A more realistic approach is to identify when to search for adverse media. For example, search for adverse media against newly added account parties at the time of account opening and then revisit the account based on a schedule guided by policy-designated risk criteria (i.e., account type, jurisdiction, expected activity, etc.).

Relying on a risk-based model alone won’t safeguard an institution if it fails to act upon receipt of information obtained between scheduler reviews. In other words, identify event-triggered media reviews – those activities that may warrant an ‘unscheduled’ investigation of news sources as a result of newly discovered account activity, law enforcement inquiries, or higher-risk counterparty relationships.

2. Balance Manual and Automated Reviews

Even institutions with effective manual processes may not be able to dedicate adequate staff to review all account parties in-depth and keep up with newly identified media activity. Automated processes can complement manual review as an integral part of adverse media screening.

Systems that cast a wide net scraping the internet or news source databases are likely to produce an overwhelming volume of non-relevant alerts. For more productive screening, look for a solution that answers the question, ‘Who in the customer base has noteworthy news already compiled on them by a reputable data provider?’ rather than, ‘What information exists in the world that may be related to my customer?’

Automating the ongoing review of news media sources must balance the obvious benefits of daily monitoring and surveillance while avoiding the pitfalls of overwhelming analysts with a sea of results containing very few actionable items—or worse, missing relevant actionable items. CTA –

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3. Apply Risk Categorisation

The identification of adverse media does not necessarily result in a binary, black and white designation of ‘risk’ or ‘no-risk’ in the way a sanctions alert might. Since adverse media findings are not all the same, they require a greater depth of qualification to assess the true level of risk.

Developing models based on categories and severity of adverse media can help to both prioritise the reviews and more effectively understand the appropriate level of risk associated with a client as part of the general KYC profile.

4. Consider the Timeliness of Findings

The concept of news decay is an interesting consideration in assessing risk. Some customers with adverse media findings that might have qualified as higher risk could be reclassified as lower risk with both the passing of time and the absence of subsequent adverse media.

Determining the materiality of adverse media based solely on the age of information can be effective in some instances. However, there are certain types of severity related to adverse media that do not subside over time, such as negative news surrounding corruption or other serious financial crimes.

5. Ensure Ongoing Monitoring and Surveillance

After determining when to search, what to search and how to evaluate results, the next step is deciding what to do with the information.

A one-and-done screening of any given account party will at best identify risk related to historic activity. Whether findings are material or immaterial (i.e. not severe enough to align with a programme’s calculation of risk), it is necessary to monitor initial findings for future updates.

Having a separate, automated process to review updates and changes to known findings will allow for a more targeted use of resources. Otherwise, there is potential to lose sight of updates within the overall results of a volume-heavy adverse media screening system.

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