The United Nations estimates that 2-5% of global GDP is laundered every year, which makes money laundering one of the most pervasive financial crimes in the world. Money Laundering is the act of concealing the ownership of illegally obtained money by integrating criminal proceeds into the legitimate economy and undermining trust in institutions.
As financial products, digital payments, and cross-border transactions become more complex, the opportunity for criminals to exploit financial institutions grows in parallel. The digitisation of corporate registries, social networks, public databases, sanctions lists, and media archives has created a vast ecosystem of open data.
Open Data Intelligence is the shared foundation where the advantage goes to those who use publicly available information to create actionable insights.
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What is Open Data Intelligence?
Open Data Intelligence refers to the collection and analysis of publicly accessible data to derive actionable insights that support decision-making. It includes data from sources such as government databases, social media, business registries, and media channels.
Open Data Intelligence or Open-Source Intelligence (OSINT) has a long history that dates back centuries. It began with traditional methods like newspapers and broadcasts and evolved through World War II with the establishment of specialised monitoring services like the BBC Monitoring Services. Today, it has transformed with the rise in digital infrastructure and now incorporates Artificial Intelligence (AI) and machine learning.
Ways to use open data intelligence to derive actionable intelligence-
- Enhanced Customer Due Diligence
Enhanced CDD leverages open data intelligence to provide a more in-depth understanding of a customer’s or an entity’s background and risk profile. Financial Institutions can cross-reference through multiple accessible sources to confirm the legitimacy of stated activities and detect any discrepancies that may indicate hidden risks. - Reveal Ownership Structures
Money Launderers use layered networks of offshore entities and shell companies to hide the true ultimate beneficial owner of a company. By drawing from publicly accessible sources such as corporate registries, Open Data Intelligence tools can help in providing complex networks and ownership structures. Identifying UBOs can help in understanding risk exposure and can improve the ability to meet regulatory requirements. - Improve Suspicious Activity Reports (SARs)
Open Data Intelligence improves SARs by verifying identities, uncovering adverse media, mapping hidden networks, and providing independent evidence that strengthens and supports law enforcement actions. - Adverse Media Screening
Continuous monitoring of global news sources helps detect negative mentions of individuals and entities. Open Data Intelligence tools help in flagging potential risks like fraud investigations or sanctions violations, enabling timely interventions. - Regulatory Risk Monitoring
Open Data Intelligence tools track real-time updates from sanction lists, regulatory bodies, and high-risk jurisdiction alerts. By integrating this information into risk assessments, institutions can identify customers or transactions linked to sanctioned individuals or high-risk countries.
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Conclusion
There exist ~400 billion documents on Google’s web index, which remains largely untapped and with immense potential. In a global landscape where criminals continuously adapt to exploit the gaps in the systems, financial institutions must leverage every source of intelligence available.
By integrating Open Data Intelligence into customer onboarding, ongoing monitoring, and investigative research, institutions gain a clearer and more comprehensive view. This will not only improve regulatory compliance but will also strengthen the integrity of the financial system. As public data continues to expand, Open Data will remain an essential pillar in the fight against money laundering.