Organized crime is very active in the private and public sectors. From banks to large retailers, from federal governments to small businesses, fraudsters don’t exercise judgment when deciding which type of organization to target.
Additionally, criminal networks are actively recruiting and deploying groups of thieves across the United States, making it increasingly difficult for companies to catch bad actors before they strike.
Overwhelmed by unmanageable amounts of data, companies have left gaps in their IT systems that criminals are eager to exploit.
It is high time that businesses and governments take action to thwart bad actors using technology that outruns them, protects customer data, and protects organizations at all levels.
Artificial intelligence can provide this advantage.
It’s no secret that fraudsters seek out and exploit organizational weaknesses. Today, however, they have even more choices and more weaknesses to identify than ever before: nearly every company stores data online to some degree.
This data is as much an opportunity for companies as it is a vulnerability if not well managed. Unfortunately, countless organizations do not manage their data appropriately.
At this point, data has become the friend of the criminal, who can easily set up phishing and social engineering scams, not only in the digital world, but also in the physical world.
There has been a boom in fraud and physical theft along rail, shipping and trucking lines, as criminals approach financial institutions for fraudulent trade finance loans. For example, a criminal may approach a bank for funds to export thousands of television sets, using fictitious information.
Meanwhile, these people are working with a bogus importer or purchased to reroute the products, giving financial criminals the ability to file bogus claims to recover the money they lost, claiming the TVs were “stolen”.
They can also, just as easily, use synthetic IDs to apply for a loan to purchase products, only to default on the loans. It is at this point that banks discover they have been the victim of fraud as they investigate the identity of the loan applicant, only to then come up empty.
The crime was committed, the criminal got away with it, and banks have to clean up the mess, all caused by flaws in how institutions collect and monitor customer or supplier information.
AI can help stop fraud before it happens
The quality of data depends on how it is applied, which is why so many organizations struggle to prevent fraud. They have the data they need, but often they don’t have the ability to easily access it, and if they do, they don’t know what to do with it.
With the help of artificial intelligence (AI), however, banks and corporations can improve the security of their operations and customer data. Instead of feeling overwhelmed by endless lines of disorganized data, businesses should embrace and leverage that data through the use of AI and machine learning.
This would improve the detection and identification of suspicious individuals before — not after — a crime has been committed.
Many organizations are faced with the question of how to actually navigate through their mountains of data. It sits in silos, rather than a contextual framework, which makes it difficult to sort through and make sense of. This means that organizations cannot derive any actionable value from their data.
But AI can provide a way forward without having to solve all your data problems first.
Advanced technology takes control out of the hands of criminals with powerful tools designed to detect discrepancies and suspicious patterns, such as entity resolution, network generation, and advanced analytics. For example, the right algorithm can sort data, developing ways to detect patterns that could lead to fraud.
These patterns may include similar names, addresses, locations, IP addresses, and multiple similar applications with slightly different information. These tools help companies not only identify, but also predict fraud on certain networks, making them indispensable in a world where data never stops flowing.
The rapid identification of behavioral patterns gives organizations, whether private or public, the ability to locate and eradicate fraud before it occurs. As AI and machine learning-based systems support the collection, sorting, and analysis of data as it comes in, employees can focus their time and talents on tasks other than endless data mining.
Instead, when AI-based technology alerts these people to the potential for fraud, they can then use their human intelligence and judgment to determine whether or not to launch an investigation.
This places more emphasis on the actual risk and less on the noise that plagues organizations today.
This way, businesses can make better use of their time and talent rather than wasting it collecting and sorting data.
AI can put data into context so that it is actually useful, and as a result, organizations can detect potential fraud faster and catch criminals before they can execute their plans.
Clark Frogley is Head of Financial Crime Solutions at Quantexa. He began his career with the FBI investigating organized and financial crime and served as Deputy Legal Attaché at the United States Embassy in Japan. Previously, Frogley worked as an executive at IBM in the roles of Global Head of AML Services and Anti-Fraud Banking, Head of Financial Crime Practices for IBM in Japan, and Head of Anti-Fraud Solutions against financial crime for AML, Sanctions and KYC.
He can be reached via social media at Twitter: https://twitter.com/quantexa; et alinkedIn: https://www.linkedin.com/company/quantexa/