The traditional credit scoring system, on which credit and lending decisions rest, is broken. Designed to serve a risk-averse system to reduce risk to lending institutions, the dominant credit scoring model focuses entirely on how consumers have behaved in the past. That is, how much have they borrowed before, how often they have applied for credit, and how have they repaid those loans?
With the rise of innovative fintech and an openness to more creative lending decisions, there are more tools available to understand customer risk profiles and make more accurate credit scoring decisions. With digital footprints and signals, you can see a range of data about a potential borrower that emerges from their digital/online activities. These signals, and the bigger picture they form, deliver real-time, more holistic insight into a consumer’s likelihood or ability to repay credit, qualify for smaller loans, such as microloans, or default on payments.
Practically, digital footprints help you gauge risk more systematically while gaining a richer view of potential customers.
The traditional approach to scoring and granting credit is outdated, incomplete and inaccurate. The “credit history” evaluation methodology for credit scoring relies on a limited (hard) data set that is not necessarily reflective of how likely a person is to repay their loans, even if it provides reasonable assurance of risk level. And worse, this approach entirely excludes a vast category of potential credit seekers: those without any credit history.
Until the nascent fintech industry recently began introducing disruptions, from lower-risk access to small amounts of capital in the form of microloans, to more multi-pronged scoring methodologies, access to credit and lending has been limited — and limiting — and entirely in the hands of the typically risk-averse banking and finance sector. Standard credit scoring, based primarily on historical credit records maintained by credit reporting agencies (CRAs), categorize people with limited or no credit histories as too high risk because credit scores are derived completely from credit bureaus.
The traditional credit scoring model thus becomes a barrier to credit access for large groups of people who may well be able to meet financial obligations, particularly for microloans, but who have been shut out of the system because, paradoxically, they are not already a part of it and have not been able to demonstrate their creditworthiness outside of it.
Download the full-version of this white paper and learn how digital footprints can improve your lead qualification.
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