Digital Onboarding Feature Photo

You’re contemplating a relationship. If things work out, it’ll be forever. If not, it could be an ugly breakup and you’ll need to pick up the pieces and start again. You want to do your homework but you’re no expert at this stuff. Is having a picture of your pet on your Facebook profile a deal-breaker? You’re making up the rules as things go along, asking friends, and reading self-help guides. You don’t have much time to make up your mind and it’s a competitive landscape out there. You just want to get this part over and get started on the relationship.

Digital onboarding is when you sign up a customer for the first time. You have no prior history of this individual other than what you’ve been able to learn using credit bureau reports, social media, terrorist watchlists, and the DMV. You’re hoping that they are who they say they are and that their intentions are honorable.

For most businesses, onboarding is a necessary evil: not part of your core business but essential if you want to engage in the digital economy.

An onboarding stack involves integrating a diverse set of identity verification and KYC data vendors. Uncorrelated features must be extracted from these different data sources and accurate models built that balance fraud risk with top-line growth. These models must be monitored and updated continuously to keep pace with shifting behaviors and demographics. 

Digital onboarding services specialize in the task of finding good customers and keeping out the bad. They have access to large data sets because of the broad spectrum of industries they serve. They are able to leverage these data sets to build complex models spanning a comprehensive feature space and to maintain these models as fraud patterns drift. Detecting synthetic and third-party fraud patterns is their core business, not a secondary cost center. 

Fraud loss indemnification takes this outsourcing a step further. An onboarding service that controls the entire fraud detection stack, choosing high-value data vendors and building the models and rules that turn raw data into high fidelity decisions, is able to certify their ability to reduce fraud and grow the business at the same time. In this case, the fraud risk can be underwritten and moved off a company’s balance sheet. This eases capital requirements standards demanded by regulations like Dodd-Frank and Basel III and re-focuses the business towards core activities, be that banking, e-commerce, or digital match-making. 

Maybe a good onboarding partner can’t fix a broken heart but wouldn’t it be great to have coverage in case of a breakup?