How many loan applications does your credit union reject because of the applicant’s credit score?
Harder question: how many times are those credit scores erroneously lowered due to faulty information in credit reports?
Listen to Clint Lotz, ceo of TrackStar AI, and the answer is that plenty of loan apps are rejected for exactly those reasons.
What if your institution could harness machine learning tools to swiftly analyze a credit report and identity probable errors that when fixed would result in a 50 to 100 point jump in the credit score?
Sound good? That’s why you want to listen to Lotz as he talks about contemporary, cutting edge credit repair tools that will enable a credit union to empower a loan applicant to quickly initiate repair of his/her credit report and, in the process, position the credit union to comfortably grant the credit the applicant seeks.
How good does that sound?
Why haven’t you heard of similar before? Probably, says Lotz, because it is all new, enabled by the emergence of inexpensive cloud based computing (think AWS, Amazon Web Services). But powerful cloud on demand computing is here and that has made it possible to analyze loan apps and credit reports in wholly new ways, says Lotz.
Along the way you want to hear what Lotz has to say about FICO. No hints here as to what he says. But buckle up when this moment arrives.
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