How can financial institutions transform their adverse media screening?

A recent whitepaper by Celent has provided financial institutions (FIs) with tips on how to bolster their adverse media screening coverage to combat financial crime.

According to Celent, combatting financial crime in the digital era will require FIs to strengthen and widen their adverse media screening coverage while improving the efficiency and effectiveness of the process.

One of the key areas of innovation that the firm believes may have the potential to transform media screening is AI-powered solutions – with the technology potentially able to enable ‘more frequent, dynamic and proactive monitoring of customer risk’.

Celent noted that while critical money laundering-related information on a FI’s clients may be found in media sources, many traditional sources of technology used in adverse media screening is proving to be inefficient and ineffective in scanning a rapidly growing media ecosystem – limiting its effect on known high-risk actors.

With this considered, the company stated in its whitepaper that it believes FIs are turning to next-generation technologies to strengthen their adverse media screening process.

How are FIs innovating?

To get to grips with the challenges around financial crime, many companies have turned to technologies such as AI and machine learning – with significant adoption in financial services to be found around anti-money laundering (AML) operations.

Celent said in the whitepaper, “AI technology has the potential to transform adverse media screening. Specifically, Natural Language Processing (NLP) can greatly improve analysis of textual and unstructured data analysis and can bring about a paradigm change in adverse media screening.”

The company highlighted that NLP techniques are able to power intelligent analysis of textual information by going further than keyword-based search and instead, being able to identify context, relevance and the relationships that are embedded within news articles.

Through assessing the context, Celent said that companies can then flag the kind of adverse activity and map them with AML typologies. Then, for each search result, AI systems are able to offer scores that enable search result ranking according to relevance and risk. This allows FI’s to devote their limited resources to the most riskiest and relevant results and leave the less risky ones to be either managed by junior analysts, supressed or auto closed.

Furthermore, the whitepaper stated that AI-driven solutions enable expanding scale and breadth of coverage ‘exponentially’ by analysing a range of sources, including those in foreign languages.

Celent believes this automation-driven approach ‘removes human biases and errors and improves investigation consistency’ and also ‘ensures auditability’ as a software system is able to provide and record the rationale for its suggestions.

AI’s role in adverse media screening

The whitepaper went on to outline that FIs have started exploring the application of AI in adverse media, with Celent stating that it has found some FIs have seen a reduction in case investigation time by over 75%, as well as an accelerated corporate client onboarding time from two weeks to two days.

On the benefits of AI for FIs in adverse media screening, Celent noted that a natural extension of AI application will be to automatically link and analyse entities across adverse media and other screening sources such as company registries, beneficiary information, watchlists and sanction lists. This, the firm believes, will enable FIs to take a more ‘integrated and holistic approach’ in screening.

Furthermore, Celent highlighted that another critical edge AI-powered solutions have is through conducting more frequent screening and client monitoring. The company underlined in the whitepaper that this will allow FIs to undertake a more proactive and dynamic approach to customer risk monitoring and support them to conduct regular monitoring of clients so that when there is adverse media on a client, the systems will be able to trigger an alert that prompts an immediate risk reassessment.

The whitepaper also referenced that the ongoing screening of customer activity will also uncover trends and patterns about the ‘evolution of risk’ for different customer segments that can better inform the methodology of risk assessments and help in calibrating risk scoring systems.

Celent concluded the whitepaper by stating that it believed for smooth implementation and maximum benefit realisation, FIs need to pay more attention to issues such as data management, model governance, resourcing and system integration.

The firm remarked, “AI is not meant to replace human analysts and their judgments, and humans will still be in charge of decision making while working with AI-based systems. But AI-powered tools can and will augment human analysts by reducing their operational burden in adverse media screening and helping them with advanced insights.”

The full whitepaper can be viewed here.

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