When it’s time to hire a new employee, organizations go to great lengths to avoid hiring someone who commits fraud: background checks, credit checks, drug tests, and more. them.
If we look at the profile of a professional fraudster, these people are not always what we expect of them. In fact, when a corporate fraud has been discovered, most companies don’t look for the right person. Almost half of professional fraudsters have 5 years or more of seniority, while only 9% have joined an organization for less than a year.
While you can’t tell who is planning to defraud you, you can put in place the systems and technologies that will protect your business and your customers. Let’s explore some scenarios and how artificial intelligence and biometrics can help uncover and combat fraud.
Scenario 1: Professional fraud
Imagine that your employees – now working remotely – have access to your CRM. They (and potentially their roommates or neighbors in the cafe) can see everything about your customers, from their addresses and shopping habits, to driver’s license numbers, to the mother’s maiden name and other business details. personal identification.
Instead of allowing employees full and unhindered access to CRM at all times, an AI-powered fraud prevention solution can be deployed to better secure your customers’ information. With the right solution on board, your agent would only have access to a particular customer’s information when that customer is on the phone and the customer and employee have been securely authenticated using biometric technology.
This way, your agents would not be able to access personal information when they want to, or make changes to the client file without consent and proper biometric authentication.
Scenario 2: External fraud
Say, for example, that a professional fraudster calls your organization’s contact center several times a day. Each time, they represent a different customer, whose personal information and even the password were available for sale on the dark web. Without an AI-powered fraud prevention platform and biometric authentication, this type of fraud could easily go unnoticed. In other words, the average contact center employee cannot recognize that one person is responsible for multiple contacts.
But that’s exactly the kind of problem AI and biometrics are uniquely suited to tackle. With biometric authentication on board, the fraudster simply cannot replicate a customer’s voice, conversational style or behavioral characteristics to access account information. Additionally, by constantly authenticating the customer across the communication channels, the AI-enabled solution will quickly identify if or when a fraudster enters a conversation, helping to avoid losses in this way as well.
It should be mentioned here that fraud prevention can and should be more than preventing financial loss for your organization: it is also a matter of corporate citizenship. A high profile Case A few years ago, the FBI investigated and uncovered a complex fraud scheme involving a hacked telephone system, international calls to a paid service, and the resulting revenue to fund a terrorist network.
While preventing financial loss was important, preventing terrorist attacks was an unexpected but critical side effect of this particular fraud prevention effort.
Scenario 3: Opportunistic fraud
Throughout my career in fraud prevention, I have heard the adage of 10-10-80 fraud, as I’m sure many of you have. It’s a concept that assumes that about 10% of people are honest all the time, 10% of people are dishonest all the time, and the remaining 80% could potentially take advantage of the ârightâ circumstances to commit fraud.
While we are not aware of any data research that formalizes this concept, it is useful to base our final scenario here. Given the right circumstances (pressure, opportunity and rationalization), it is impossible to predict when an otherwise honest citizen will seize an opportunity to defraud an organization.
Consider the process of filing an insurance claim. An otherwise honest person can take advantage of the situation to inflate the value of his loss; it is not professional fraud, but someone who seizes an opportunity. According to FBI, insurance fraud like this totals over $ 40 billion a year, so it’s a huge problem worth addressing – and one that is at the heart of an emerging area of ââresearch. and development.
In the near future, we can expect AI-based deception detection solutions to hit the market. These solutions continually analyze how people answer questions when filing insurance claims and guide agents through their follow-up questions if the information points to anything suspicious.
All types of fraud will continue to present new and evolving challenges, especially as the number of customer engagement channels increases. As fraudsters take advantage of the growth of your organization’s channels, devices, and access points, businesses need to take a cross-channel approach to fraud prevention, from biometric authentication to intelligent detection solutions that go beyond simple perpetrator detection.