Loan Approval Augmented Analytics Use Case

Predictive Analytics for Loan Approval

The Objective

Banks and lending institutions must protect the bottom line by making the right decision as to which prospective customers are eligible for loans and which are likely to default. The cost of dealing with ‘bad’ loans is high and it reduces profitability and productivity. To succeed, these businesses must have a dependable process for attracting the right clientele and reviewing, approving and managing loans.

The Solution

The application of advanced analytics to the process of loan approval and management is an important aspect of decision-making. While every bank and lender has a process (including rankings in various risk categories), the refinement of these processes using algorithms and analytical techniques can help the business to see the big picture and to target the right demographics in marketing messages, identify common risk factors across multiple variables and anticipate loan defaults or issues long before the customer defaults on the loan. If a business can get ahead of the problem, it can avoid catastrophic loan default and, if the business can avoid lending to poor candidates, it can avoid those issues altogether.

This Technique Can Be Used in Many Industries, Including

Credit unions, banks, insurance, real estate, construction


We invite you to explore our Advanced Analytics Use Cases here to find out how the Smarten Augmented Analytics product can help you to achieve goals and sustain a competitive advantage.
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