Question 1

What are the challenges and risks of alternative credit scoring?

Accepted Answer

Data ownership and fraud are the two biggest concerns, followed by discriminative lending. Alternative data gathering should comply with GDPR and other regulations. Data should be stored securely to prevent misuse by fraudsters, and scoring should not be biased or lead to discriminative, preferential lending.

Question 2

Are there any regulatory challenges for alternative credit scoring?

Accepted Answer

Yes — a lot of alternative data sources are tightly regulated by the GDPR, PSD2, the CCPA Act, and open banking and FTC  regulations. In addition, access to these sources requires secure data practices to protect PII. However, all of these can be handled by an experienced software development partner.

Question 3

How accurate is alternative credit scoring compared to traditional credit scoring?

Accepted Answer

Alternative credit scoring is based on accurate real-time data on the spending habits and financial discipline of a person or company. While these have lesser weight than traditional credit scores, it helps validate applicants with thin credit files or those with none at all. This is essential to increase the borrower audience and attract new customers.

Question 4

How does using alternative credit scoring improve the lending process?

Accepted Answer

Automation with ML models helps significantly shorten loan origination and underwriting, decrease costs, and prevent human errors. It also allows lenders to offer better interest rates to the clientele of their competition, which benefits all parties included.

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