Financial Crime Complexity and Impact

Financial crime is rampant. According to INTERPOL, financial crime and corruption are among the top three threats investigators face. International financial crime rings use complex money laundering schemes to avoid detection and maximize their illicit profits. These threat actors also abuse virtual assets, such as cryptocurrencies, as a widespread crime tool.

Leveraging the growing globalization and digitalization, these crime syndicates commit their crimes with increasing efficiency and sophistication. Apart from causing enormous losses to businesses and individuals worldwide (estimated at USD 42 billion in 2020), these threat actors also undermine global financial systems and impede economic growth.

Fraud detection and fighting crime are complicated since it requires cross-border investigations to identify the members of a crime ring and to trace illicit financial money flows. Especially the latter has high priority since investigators are only intercepting less than 1 percent of criminal funds flowing through the international financial system.

The combination of low risk and high profits associated with financial crime makes it a very attractive activity for organized crime groups. The likelihood that fraud will be detected and prosecuted is low because of the complexity of the investigations required. This especially applies to fraud cases that need international cooperation to be successful or where the jurisdiction is not clear (e.g., online fraud or ransomware attacks on financial institutions). In other words, organized criminal groups operating at an international level benefit from differences in national legislation.

To make matters for law enforcement even more complicated, financial crime is often interlinked with corruption, which makes the financial crime landscape even more complex. Transnational organized crime groups commit fraud and are involved in corruption using similar mechanisms to move and launder illicit funds. Furthermore, the COVID-19 pandemic has demonstrated that criminal groups are extremely adept at modifying their methods to take advantage of new opportunities for defrauding individuals and companies, with millions of dollars stolen every day. Furthermore, crimes such as human trafficking and environmental crimes also have corruption or financial crime component.

OSINT Aids Complex Financial Crime Investigations

Analysts and investigators need OSINT tools for efficient data collection and processing. Such tools must have feature is Natural Language Processing (NLP), since the content on and the dark web and online forums is often in languages other than English. The solution needs to combine AI, machine learning, automation, and predictive analytics to identify new schemes in the fight financial crimes. With an OSINT solution that uses these and other ahead-of-the-curve decision models, investigators can process and categorize big data into meaningful categories, learn from complex patterns, and identify abnormalities for a holistic view of criminal activities such as financial crimes, fraud, money laundering, terror financing, payments connected to corruption, human trafficking, illegal drugs trade, crime-related cryptocurrency payments, etc.

Cobwebs Technologies Fights Financial Crimes

Our AI-powered WEBINT platform allows investigators to access the dark web quickly, anonymously, and securely to detect and identify organized crime groups committing financial crimes (including online fraud), map their activities, identify the kingpins, pinpoint their location, and get insight into the identities, movements, and intentions of their members anywhere and in any language.

The Cobwebs platform integrates its OSINT solution with streamlined AI and ML analytics algorithms that help investigators (but also financial institutions such as banks) to scan a multitude of publicly-accessible data sources based on operator-provided search terms. It will only display relevant information through an intuitive user dashboard, allowing organizations to build reports or suspect cases rapidly. Investigators can also use the results to identify trends and patterns to anticipate and prevent financial crimes in the (near) future. Other benefits are the acceleration of the investigations thanks to the AI (Artificial Intelligence), ML (Machine Learning), and NLP (Natural Language Processing) algorithms that improve outcomes. Investigators with limited resources will be able to reduce crime and improve investigation times, which makes the decision-making process highly efficient and effective. This solution can immediately accelerate a financial crimes investigation, halting illicit activity online and identifying bad actors quickly, before another fraud or financial crime occurs.