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Old is New Again: Past Prospects Can Become New Customers

Marketing using Predictive credit analytics

Marketing for the banking industry during the pandemic.

The banking industry is inundated with monitoring and simulator programs, but most don’t give lenders actionable options to generate credit qualified applicants. In our COVID-19 era, getting and measuring creditworthy applicants is an acute problem, as more customers need loans to cover monthly expenses, keep their businesses afloat, or for mortgages of new homes. 

However, before COVID, assessing credit for consumers was problematic, given the amount lenders spend on marketing to reach qualified applicants.

Marketing Remains Expensive

The traditional marketing lenders rely on to find high-value customers does not come cheap, as most of their viable leads average around $90 cost-per-click. Even to the biggest lenders in the U.S., this adds up exponentially when they’re targeting hundreds and thousands of qualified customer leads.  Lending is also very competitive, which is why lenders heavily rely on lead aggregators (think LendingTree) to find these leads. This gets compounded when a lead aggregator sends leads to multiple lenders, while at the same time, customers can easily get bombarded with competing offers at the same time.

marketing in banking industry

These factors result in high cost of acquisition (COA) numbers, as lenders continue to solely focus on reaching out to consumers with healthy credit, thus trapping lenders in a never-ending marketing outreach loop.

True Results

Alleviating the need for lenders to be solely dependent on lead aggregators, the newly launched predictive API from TrackStar.ai is designed to help lending institutions offer loans to customers based on information in existing databases using predictive credit analytics.

In applying predictive credit analytics to a lender’s own database, lenders can qualify loans to prospective customers who were previously turned for being 20-50 points shy of a qualifying credit score — customers who may remain loyal to the lender for years to come. The API also enables lenders to reduce risk and increase the value of a lending portfolio by improving customer’s credit files, all while extending loan offers.

A New Alt Data Set

With a credit dataset like TrackStar’s, lenders can predict what credit items could be disputed/removed in the future and when a consumer’s credit score should rise, enabling lenders to qualify them for lending products immediately. This, in turn, gives consumers the opportunity to access funding for their future right now.

Marketing During the Pandemic: Exploring Previously Uncharted Territory 

The pandemic has created an uncertain economic climate that continues to shift daily. In addition to loans to help sustain businesses and current homeowners, many potential first-time homebuyers are looking to lenders for funding.

In these uncertain times, lenders can reduce their expensive marketing budgets and reliance on lead aggregators by using their own existing databases in new ways, with predictive data — addressing the needs of and empowering past prospects to become current customers.

Summary:

Predictive Analytics in Marketing

Marketing for the banking industry during the pandemic. The traditional marketing lenders rely on to find high-value customers does not come cheap, as most of their viable leads average around $90 cost-per-click. Even to the biggest lenders in the U.S., this adds up exponentially when they’re targeting hundreds and thousands of qualified customer leads. Applying predictive credit analytics to a lender’s own database, lenders can qualify loans to prospective customers who were previously turned for being 20-50 points shy of a qualifying credit score — customers who may remain loyal to the lender for years to come.

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