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Why Lenders Need Customer Identity Intelligence

By April 26, 2018No Comments

Why Lenders Need Customer Identity Intelligence

By: Craig Moore, SVP – National Sales Manager, Accelitas

The credit scores and data analytics systems, including loan decisioning engines, that lenders have relied on in the past simply don’t cut it anymore. Too much has changed. 

Here’s a list of what’s making traditional analytics approaches obsolete:

  • Technology, especially mobile technology. Smartphones have become the default computing device. Lenders need to be able to reach customers on their smartphones and tablets, anytime, anywhere.
  • Customer expectations. Smartphone-savvy consumers expect every brand interaction to be fast and frictionless. Long online forms, slow response times, and requiring visits to brick-and-mortar storefronts are deal-breakers. When experiences become frustrating, consumers will click away and shop elsewhere.
  • Markets. According to CFSI, the financial services market for financially underserved consumers is worth $173 billion. The total available market for small dollar loans alone exceeds $3 billion. Traditional analytics have trouble analyzing many of these consumers, especially the thin-file and no-file consumers who make up about 30% of the U.S.
  • Analytics. Data scientists have made tremendous strides with Artificial Intelligence (AI) techniques, including machine learning and deep learning. Lenders now have the opportunity to put this new technology to work in real time. Lenders who fail to leverage this new technology will lose business to others that do.
To seize open more profitable accounts, win over customers with engaging experiences, reduce fraud, and grow marketshare, lenders need a new type of analytics. It’s got to be fast, accurate, and easy to integrate.

Introducing Customer Identity Intelligence

At Accelitas, we call this real-time, highly predictive type of data analytics Customer Identity Intelligence.

Customer Identity Intelligence goes beyond traditional approaches to identity analysis, such as Identity Access and Identity Verification, which traditionally delivers only a cursory verification of a consumer’s identity—just enough data to comply with KYC guidelines.

Customer Identity Intelligences focuses on identifying customers at loan origination, which for lenders means when a loan application is either accepted or rejected. At that moment, and in real time, Customer Identity Intelligence delivers predictive insights, leveraging advanced AI techniques like machine learning and deep learning.

Using Customer Identity Intelligence, businesses can open the right loan and deliver a winning customer experience. They can detect and reject a fraud operator or potentially negligent clients before any losses are incurred. They can review rejected applicants with more advanced screening techniques, and welcome some of those applicants as customers. And they instantly re-verify those customers when they engage in activities that merit special scrutiny, such as initiating large account transfers or adding new users to a business account.

Artificial Intelligence to the Rescue

How is all this possible? Customer Identity Intelligence draws on data, both new and existing, but leverages analytics techniques–especially AI techniques such as machine learning and deep learning–that have only recently advanced to the point where they can be reliably used by lenders. These new techniques make loan decisioning and other types of analysis progressively smarter and more effective. Further improving accuracy, Customer Identity Intelligence draws on new data sources, and aggregates existing data sources in new, highly rewarding ways.

Here are some examples of how lenders can use Customer Identity Intelligence:

  • Opening More Profitable Accounts
    Lenders can open more accounts and ensure that more of those accounts are profitable. They can verify identities that traditional screening solutions miss, and benefit from predictive insights about applicants.
  • Credit Risk Management
    Especially when applied to custom data sources, AI can yield more predictive results for loan decisioning. Profits go up, rejections go down, and both lenders and consumers consider their relationship a win. Still rejecting too many accounts? New custom AI techniques can be applied to rejected applicants to discover previously overlooked indications of creditworthiness. Today these techniques are enabling lenders to achieve an ROI of 30:1 on this special application of predictive analytics.
  • Mobile Account Opening
    AI can be used to analyze identity documents used for identity verification. This real-time analyze can detect fraud while simultaneously culling ID data for use in auto-form-fill, helping complete the account application for the user. Benefits? Lots, including an improved customer experience, fewer typos and other errors in applicants and reduced fraud.

Customer Identity Intelligence: Predictive Analytics You Can Take to the Bank

Today’s companies need insights that they are simply not getting from traditional databases, data feeds, and marketing lists. They need keener intelligence that provides a personalized experience that only predictive analytics can deliver. They need it available anywhere: in a store, in a branch, or on a mobile device.

Customer Identity Intelligence provides the predictive insights that lenders need in today’s fast-paced, mobile-centric market.