IDology: How to VERIFY Your eCommerce Customers Without Compromising SECURITY or CONVENIENCE
IDology: How to VERIFY Your eCommerce Customers Without Compromising SECURITY or CONVENIENCE
Heidi Hunter, Chief Product Officer, IDology
In episode 83, I speak to Heidi Hunter, Chief Product Officer at IDology, about how their platform helps businesses to create frictionless and secure eCommerce customer experiences.
We discuss how the platform provides many features including dynamic Knowledge-based Authentication, Transaction Monitoring, document authentication, biometric verification and many others to streamline checkout processes, increase conversions and prevent fraud. We also discuss the challenges and opportunities of digital identity verification in the eCommerce industry, and how IDology adapts to changing regulations and customer expectations.
AUDIO VERSION: thepayments.show
Episode Highlights:
Fraudsters Now Playing “The Long Game”
The most shocking thing for me over the last 4-5 years has been this immersion of the long strategy, where these guys are actually willing to create culture and cure identities over a period of time and build a worthiness level of them financially, and then they'll utilize that and just and just b*stardize it across different financial services providers for the gains that they want to make. People do things like actually open different kinds of accounts, credit accounts on them, low limit, instant access, and then they'll sit there and actually use them and pay the bills for a while to grow. And as the credit gets better and better, then it's ripe to be used for taking advantage of businesses.
ID Data Is Not Enough To Verify A Person
We need to collect the right information. We shouldn't collect data we don't need. You've got the core pieces, which is always name, address, date of birth etc… But that's not sufficient in this world in order to assert ownership of that identity, ownership of the device that it's on. For these, you're going to need to look at that for many different aspects. You need to make sure that this person is legitimate, exists, they're not synthetic. So looking at things like the email that they registered with, the mobile number, do they have some kind of ownership of that? Looking even at things like their IP address to try to get a sense of where the traffic's coming from, information about the device. Our solution will factor out to those different data points and pull back as much data as it can, it generates information that then can be run through decision matrices to come with the next step type of outcome.
Tracing Fraudulent Money As It Moves
Money moves. And a lot of times their fraud is one part of the process. It may have been a credit card that was opened and all the money was extracted off in some method, but then it's got to get moved. And maybe it gets moved through a payment service and then that's going to go into a different bank account, or it gets moved to a prepaid card where it's got some level of transience. Because of our reach across our solution sets, we can watch this move. Our ability to find it faster and flag it sooner is expanded because we're watching it move. And we actually will see this in our data. We will see a fraudster go from one customer to the next, to the next, to the next, to the next. And the way that we've engineered these solutions, we can provide those insights to all of them. This was iffy when it came to you, then it went to this person and this person and it's moved and it's travelled, and that greatly enriches the probability that this is a fraudulent activity. Because again, going back to what you were talking about, I mean, why would a consumer go open 10 bank accounts in one day?!
