FCC programmes increasingly rely on risk screening solutions from providers such as LexisNexis, Thomson Reuters and LSEG to help banks meet KYC and AML obligations.
These platforms support financial crime compliance (FCC) teams by verifying customer identities and screening individuals and entities against sanctions, adverse media and watchlists, each drawing on their own proprietary global datasets, said Workfusion.
However, compliance teams have long understood that no single data provider offers a truly comprehensive view of risk. For years, analysts have filled these gaps by turning to general-purpose web search engines such as Google, Bing and DuckDuckGo. Google, in particular, has become the default supplementary tool for many FCC operations, despite growing frustration with the limits of what it can actually reveal.
That frustration persists because web search alone does not deliver the complete picture compliance teams need. While it might seem logical that combining Google results with screening platform data would close the information gap, the reality is more complex. FCC leaders continue to struggle to access reliable, comprehensive data on higher-risk individuals and entities, even with these tools at their disposal.
One reason lies in Google’s inherent blind spots. Estimates suggest the search engine indexes only 15–20% of publicly available online information. What appears in search results is determined by proprietary relevance algorithms, user location and search history, rather than by what a compliance analyst actually needs to see. For FCC teams conducting KYC, AML and fraud investigations, this filtering can obscure critical context and lead to incomplete assessments.
Search engine optimisation practices further distort visibility. Organisations with strong SEO capabilities can push favourable narratives to the top of search results, while less optimised but potentially important sources are buried pages deep. Geographic restrictions compound the issue. In markets such as China, Iran, North Korea, Russia and Turkey, censorship and access limitations mean large volumes of relevant public information never surface in mainstream search results at all.
Beyond missing data, the risk of disinformation is a growing concern. Studies have shown that state-backed or well-funded organisations can disproportionately influence what appears in news and search rankings. When such dynamics are applied globally, including in the EU and North America, it becomes clear why web search engines can deliver both incomplete and misleading inputs to FCC analysts.
In response, leading banks are adopting more sophisticated approaches to data collection and analysis. Rather than relying solely on screening platforms or open web searches, they are working with solution providers that combine deep AML, KYC and fraud expertise with advanced technology. Large language models (LLMs) such as ChatGPT, Anthropic and Gemini are increasingly used to augment traditional searches, enabling analysis at scale and summarising large volumes of content across multiple languages.
Crucially, these tools only deliver robust results when guided by subject matter expertise. Effective FCC workflows require carefully designed search strategies, multilingual prompts and an understanding of how adverse media is reported in different jurisdictions. Financial centres such as Jersey or Guernsey, for example, generate highly localised reporting that generic search tools often miss without expert input.
Banks that embed this expertise into their data strategies are already seeing results. By pairing advanced AI with curated data sources, they reduce analyst workloads while improving accuracy. Instead of reviewing dozens of articles, analysts receive concise summaries backed by clear sourcing, enabling faster, better-informed decisions across both historical and real-time risk assessments.
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