Bringing New Clients – Increasing Approval Rates!

As many of you know, big data tools can add considerable value to identification of “good” and “bad” borrowers’ clusters. This research covers the use case of the seamless web identification technology in identification of “good” clients or in “saving clients from a ruthless credit conveyor.”
Many companies often encounter an absence of user income data; however, this should not be a reason to reject the new client. Alternative data can be of considerable help in this situation, and as part of our research, we identified a few patterns of “good” clients. These examples can help to increase approval rates by 2-5%, depending on the product and circumstances of alternative data collection:
We hope you find this review useful. We plan to conduct similar researches and provide presentations to market participants.
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