← Use Case Library

Use CaseFinancial Services / Banking

Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions

Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions - frequently with a turnaround time measured in seconds. This offers the potential for traditionally-underserved customer groups to be offered products.

🛡

Risk reduction

Risk reduction - Evaluate counter-party risk (eg credit scores)

⚙

Revenue

Revenue - Better targeting

⚙

Operational

Operational - Faster response times

Description

Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions

Technology & data

*** check categry and function

Linked Case Studies

BankMobile approves loans for young banking customers based on non-traditional data measures using Upstart''s machine learning

Branch grants loans to app users based on alternative data including contacts, social media, and call history and machine learning to assess credit risk

JPMorgan Chase sped up loan application and approval process for small businesses using AI-powered OnDeck to analyse a variety of online data

ANZ bank identifies high risk loans and predicts customer defaults with deep learning

Baidu does underwriting for consumers with limited credit history using machine learning

JD.com increases customer loan approval rate by 150% using Zest Finance''s machine learning platform

←Back to Use Case Library

Editor: sdg