Transforming Adverse Media Screening
A New Paradigm Powered by AI
Combatting financial crime in the digital era will require financial institutions (FIs) to strengthen and widen their adverse media screening coverage while improving efficiency and effectiveness of the process. Artificial Intelligence (AI)-powered solutions have the potential to transform adverse media screening and enable more frequent, dynamic, and proactive monitoring of customer risk.
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.
- NLP techniques power intelligent analysis of textual information by going beyond keyword-based search and by identifying context, relevance, and relationships embedded within news articles.
- By assessing the context, they can flag the type of adverse activity and map them with AML typologies. For each search result, AI systems can provide scores that enable ranking of search results according to their relevance and riskiness.
- FIs can then devote their scarce resources to the riskiest and most relevant results while routing less risky ones to junior analysts or suppressing or auto-closing them.
AI-driven solutions enable expanding scale and breadth of coverage exponentially by analyzing a myriad of sources, including those in foreign languages. This automation-driven approach removes human biases and errors and improves investigation consistency. It also ensures auditability because an software systems can provide and record the rationale for its suggestions.
FIs have started exploring the application of AI in adverse media. We have come across impressive outcomes reported by early adopters, such as reduction in case investigation time, accelerating corporate client onboarding time, and improving coverage of AML program. For smooth implementation and maximum benefit realization, FIs must pay attention to critical issues such as data management, system integration, model governance, and resourcing.
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.