White-collar criminals attack the integrity of global financial systems and victimize thousands of people each year. These criminals must launder their illicit funds like any criminal group because they need and want to spend their “clean” money. Investigating white-collar criminal offenses such as bank fraud, wire fraud, mail fraud, consumer fraud, identity theft and other similar offenses is time-consuming and difficult. Complex international cases, such as the well-known Ponzi scheme, can involve hundreds of separate bank accounts and often require assistance from foreign governments through Mutual Legal Assistance Treaty (MLAT) requests and lengthy forensic analysis. Advanced data science solutions are available for banks to prevent, detect, and report white-collar crime to law enforcement.
Financial institutions (FIs) are often direct or indirect victims of white-collar crime. Whether actual funds are stolen from them, or if they have to respond to increased law enforcement requests related to white-collar crime, FIs pay the price. It’s now known that fraudsters exchange intelligence with each other on which FIs to utilize based on their weak controls, allowing several related accounts to be opened and utilized freely. If FIs don’t implement sufficient monitoring solutions to catch white-collar criminals, then the problem will grow exponentially.
By employing an artificial intelligence (AI) solution to assist with client onboarding, Know Your Customer (KYC), and Customer Due Diligence (CDD), FI’s could detect a string of intelligence often shared by white-collar criminal organizations. White-collar criminal organizations often share information such as addresses, phone numbers, identification numbers, and e-mail addresses to facilitate multiple account openings across the same FI’s platforms over an extended period of time.
For informational purposes, apart from the most commonly utilized white-collar criminal charges of wire fraud and mail fraud, bank fraud is a key tool in the federal charging apparatus.
18 U.S. Code § 1344 – Bank Fraud
Whoever knowingly executes, or attempts to execute, a scheme or artifice –
(1) to defraud a financial institution; or
(2) to obtain any of the moneys, funds, credits, assets, securities, or other property owned by, or under the custody or control of, a financial institution, by means of false or fraudulent pretenses, representations, or promises; shall be fined not more than $1,000,000 or imprisoned not more than 30 years, or both.
According to the U.S. Department of Justice’s 2015 U.S. Attorneys’ Annual Statistical Report, 732 defendants were prosecuted for federal money laundering offenses in 2015 and 8,245 defendants were prosecuted for white-collar offenses.
The breadth of the consumer fraud problem is growing daily. According to the Federal Trade Commission (FTC) Consumer Sentinel Network (CSN) 2016 CSN Data Book, approximately 1.3 million consumer fraud complaints were received by the FTC in 2016. Florida was documented as the state with the highest per capita consumer fraud rate. The report stated that approximately 37 percent of the fraud victims were age 60+. This statistic is noteworthy for FIs because of the potential for elder abuse being facilitated through FIs.
FIs often frontload extensive controls to target drug and human trafficking, terrorism, tax evasion, and other high profile crimes. However, FIs frequently forget to close the door on white-collar criminals. Proceeds from white-collar crimes are extensive, and are routinely transferred 10 or more times between different FI accounts to thwart detection.
AI-enhanced analytical systems can detect anomalies at the time of a new account opening and link suspicious transactions quicker. Data science can also help FIs detect elder abuse scenarios involving changes in account activity, changes in addresses, changes in services, and changes in contact information for at-risk older clients. White-collar crime is costly and damaging for FIs and victims. Data science and AI are solutions available today to assist FIs in disabling the white-collar criminal’s ability to exploit the financial system.