In March 2012, Nikolay Garifulin was sentenced to two years in prison for his part in the Zeus cybercrime spree that defrauded banks for hundreds of millions of dollars and infected more than 2,400 computers around the world. Garifulin himself was just one part of a franchise of fraudsters that used the Zeus malware, which allowed an imposter to capture personal information from the computers it infected. Garifulin was convicted of stealing more than $3 million.
As a point of comparison, Thomas Woodward was sentenced to 10 years in prison for robbing $4,267 from a bank in Massachusetts. While Garifulin’s sentence was considerably lighter, the most interesting thing, frankly, is that he was sentenced at all. Most fraud and abuse activity goes untried. In many cases, it goes undetected. Typically, the cost of fraud is passed on to customers, constituents or owners in the form of higher fees, increased taxes or lower margins.
What the Zeus cyber-attack and others like it teach us is that fraudsters are prevalent, active, coordinated and technically skilled. In our efforts to open our organizations to Web commerce, we have created new concerns for the protection of our funds, information and customer data. Cyber-attacks will continue, and some believe there may even be a crippling attack in the near future, which could lead to a crisis with even more devastating impact than our current financial crisis.
It doesn’t have to be this way. In fact, the digital age has more to offer the defenders than the offenders. With analytics, you can move front-line fraud management from detect-and-defend to prevent-and-eradicate. While many still engage in an arms race of rule-based detection to lock offenders out. It’s time to analyze big data to neutralize organized crime and to prevent the opportunity seeker from making the wrong choice.
Own and understand the fraud process
Fraud is everyone’s problem and cannot be ignored. Its cost is trickled down through the economy, putting pressure on those of us who are honest and forthright in our dealings. For many people in government and business today, it is difficult to think like a fraudster, but just one abusive person in 100 can make all the difference. These social vampires exist, and they are collaborating.
Too often, I see organizations with limited fraud prevention, such as a black box system – or worse, none at all, other than a firewall. As more and more doors open through growing online services, it is imperative that your organization’s fraud prevention efforts keep up. Fortunately, high-performance analytics, coupled with big data, is available to organizations susceptible to fraud and abuse, helping them manage and prevent these activities. Many organizations around the world are using data and analytics to build fraud prevention technologies that save money, protect corporate reputation and reduce process costs. It is important not to lock yourself into a black box fraud solution built on some historical perspective of fraud. Instead, success comes when you can own and understand the fraud process and respond to the ever-changing dynamics of fraudsters.
A holistic approach to fraud management
Fraud has often been compared to a balloon, since pressing on one place in the balloon just forces the air into another. Like the air, fraud moves from one inefficient process to another within an organization. When we stop transactions or decline claims without prosecuting the person responsible and without fixing the inefficient processes to begin with, we are training fraudsters to just keep trying. This cycle teaches people who are bent on criminal behavior how to attack your system. Many times you need to follow the suspect – rather than just disconnecting – to convict and eradicate. Indeed, business changes can often have a big impact on your fraud exposure, produce alerts, provide holistic reporting, control workflows and case management, and learn from past experience to become – and remain – effective. It essential to be active and elastic in fraud prevention – not just fraud detection – and to use technologies that will grow as your needs grow.
A complete set of processes to access and integrate data
Organizations from the public and private sectors alike are finding this fraud framework valuable. Along with accurate detection, these organizations find value in a holistic approach to fraud management. Combining technologies such as business rules, anomaly detection, predictive and learning models, and social network analysis can predict fraud with astounding accuracy. Using analytic models like neural networks, these systems become learning systems that get better over time, and they become more dynamic by accounting for evolving fraud activities and by using anomaly and social network models.
Fraud continues to be a major concern that continues to grow. There are more white collar workers unemployed now than ever before – and fraud is a white collar crime. Three factors are present in fraud: motive, rationalization and opportunity. With a highly skilled unemployed population, these causal factors make for a trained, motivated and potentially desperate group of people. Add to that the Internet access available to so many people today, and you have a toxic mix.
Most governments and organizations around the world are beginning to take this growing threat seriously. Now is your chance for your organization to aggressively pursue fraud prevention processes.
Learn to apply a holistic approach to fraud detection and prevention.