Why AI-powered adverse screening should be core software for FI’s

As risks of financial crime continue to rise in the digital world, companies will need to improve the use of technology-powered solutions. Adverse media screening is of growing importance and can offer more than just security.

Quantifind’s new client report, ‘Transforming Adverse Media Screening: A New Paradigm Powered by AI’ offers a detailed look into the benefits of leveraging AI-powered adverse media screening coverage.

Adverse media screening is the process of using public domain information, such as mentions in digital newspapers, web posts, social media and more, to identify any negative news. This information is used as part of ongoing customer due diligence and helps a bank know if they are working with someone they should not be.

These reviews are typically irregular and can be time consuming, with some negative information remaining hidden for several months, the report claims.

The trouble is, adverse media screening is in somewhat of a grey area. It is used as part of AML monitoring and recommended by regulators, however, it is not always mandatory. The report highlights that current adverse media screening legacy technology is largely ineffective and inefficient, as well as costly to run.

As a result, many financial institutions only use adverse screening tools during the KYC onboarding, periodical reviews of high risk clients and during enhanced due diligence in watchlist screening and transaction monitoring.

Quantifind believes financial institutions should see their adverse media screening as a critical role within AML. It states that regulators are beginning to scrutinise firms for dealing with financial crime-related activities, which could have been spotted through adverse media screening. Furthermore, this method can be used to identify other serious criminal activity, such as human trafficking, corruption, fraud, counterfeiting of currency, extortion and more.

To make the most of adverse media screening, financial institutions need to implement AI-powered solutions, Quantifind said.

Natural language processing has the capacity to greatly improve the analysis of textual and unstructured data analysis. Its analysis can identify context, relevance and relationships within news articles.

Furthermore, by understanding the context it can flag the type of adverse activity and map them with AML topologies. Once this is done, it can then score them to rank them in order of relevance and riskiness. This will help financial institutions to focus more resources on the most important alerts.

In addition to improved context, AI-solutions enable the financial institution to increase the scale of their adverse media screening. It can hit more sources and those in different languages. Quantifind also states it can remove human biases and errors, with the report claiming up to a 75% reduction in case investigation time.

Some of the other benefits of AI-powered adverse media screening technology is the ability to automatically link and analyse entities across sources and conducting more frequent screening and client monitoring processes.

Read the full report here: Transforming Adverse Media Screening: A New Paradigm Powered by AI

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