Lending, much like dating, has been brought online in the past decade with the aim of streamlining the process and dramatically reducing the time spent for both parties. But as the backend systems involved become more complicated to include more data and decisioning points, how do lenders continue to create a simplified customer experience that will bring good customers back for that “second date”? To aid in this pursuit, let’s go back to a simpler time and take some lessons from a show some of you may remember, “The Dating Game.” Similar to online lending, the show was made up of three main stages: The Questions (landing page and application), The Big Commercial (screening and underwriting), and The Date (approval, loan fulfillment, and follow-up).
1. The Questions (the application – what information do you need?)
In “The Dating Game,” the lucky bachelorette would ask questions of each of the contestants. Some were of real importance, spanning life values, career goals, or favorite Chinese restaurants, while others were simply veiled innuendos barely appropriate for 70’s cable television. But, all the answers told a story about the contestant, giving the bachelorette insights and clues into whether the contestants were funny, serious, or just plain creepy.
In online lending, we also must prioritize our questions to understand the identity and risk of the applicant, while keeping the attention span of the applicant in mind. In seconds you’re assessing value/risk of the identity behind that application. What is the minimum amount of information we need at this stage? Are three pages of form fields necessary, or can we get away with one and do our due diligence using internal data and third-party tools later? The more friction we put in front of applicants, the higher the likelihood is that they will abandon the process and go to a competitor who gets them to their end goal faster.
2. The Big Commercial (screening and underwriting)
After questions, it’s time for the bachelorette to make her decision, but of course she must ponder—but first fade to a commercial break from our sponsors. Who will the bachelorette choose?
But back in the realm of online lending, the applicants have filled out the necessary fields, selected a loan amount, and clicked “Apply.” They’re not interested in a commercial break. So it’s time for your backend systems to do some major investigative work in the shortest amount of time possible, fractions of a second matter here.
- Have you seen these applicants before? Are they new, returning customers, or on your blacklist?
- Does the information they provided check out? Does the name match the email, address and phone number they’ve provided? Is their IP within a realistic distance to their physical address? How long has this email been in use? Using a tool like Ekata’s Identity Check with over 70 data attributes can deliver positive and negative data signals within fractions of a second to help assess risk. These signals provide actionable insights to help catch fraud and streamline higher quality customers through to the underwriting process.
- Time for underwriting. Qualitative filters can help improve your process by bringing higher quality applicants into the underwriting process faster. These are applicants where the unregulated non-PII data points match and give your staff confidence that the borrower’s provided phone, address, and email input data look positive. Maybe you auto fund with the leanest underwriting possible? Or maybe you see some data discrepancies, that require additional qualifications directly from the customer to verify. Filtering applicants based on quality optimizes costs and fights fraud, while retaining an excellent customer experience.
3. The Date (the approval, deposit, and next steps)
The commercial is over, the decision is made, and a reservation at some restaurant in a ritzy part of town is awaiting this probable trainwreck of a “date.” But making good decisions with limited information and even less time is often problematic.
Thankfully in online lending, we’ve got quality data, machine learning and technology on our side. After making your internal database queries, low-latency third-party API calls (like Identity Check), and other required screening steps, in mere minutes you’ve decisioned and let the customer know, beating your competitors in the process. Whether you use quality filters and underwriting in a rules-based system or machine learning model, you can feel confident in your decision, made in an incredibly condensed time period yet still creating an excellent customer experience.
Stage lights dim, the studio audience shuffles out, and the happy couple is whisked away to the location of their first (and most likely, last) date. Not for you though, the online lender, with your simple fillable form and comprehensive layered approach to identity risk screening and underwriting, you’ve made a connection that will have customers coming back for more.