AI driven data at scale enabling financial inclusion for the new-to-credit

Digital lending in emerging markets is growing at an incredible pace, with customers and merchants eager to embrace simplified loan requirements and faster access to credit. Fintechs are seeing wide adoption of alternative credit solutions like “Buy Now, Pay Later” (BNPL), micro-loans, and use-case led credit.

However, an ongoing challenge for these fintech firms is managing new account acquisition and expansion with the risk of default, and the subsequent collection on those defaults.

We can help you drive growth for your digital lending business and enable you to approve more loan applications at a reduced risk of default. Our high scale, AI driven, privacy complaint data is highly predictive of consumer behavior and easily integrable for a variety of use cases spanning customer acquisition, risk management, and fraud prevention.

BNPL Risk Management Webinar

Recently, Mobilewalla CEO Anindya Datta, joined the Fintech News Network's webinar discussing the Buy Now Pay Later Revolution.

“We are providing predictive artifacts: data that are predictive of how likely somebody is going to default in a loan,” Anindya said.

In this webinar, was joined by leading players and industry experts to discuss the future of BNPL. Topics include:

How can fintech firms leverage alternative data to gain competitive advantage
What is the next stage of growth of BNPL?
How to minimise consumer defaults

Read the original and full article from Fintech News

With Mobilewalla, fintech teams can:

Verify customer identity and manage the risk of fraudulent applications by comparing Mobilewalla data with customer inputs.
Use risk scores and predictive features to better understand propensity to default and manage credit risk.
Enrich your internal data with Mobilewalla data to improve your collections process and recovery.
Analyze affinity modeling for next best product and service offers.

Assessing Credit Worthiness with Alternative Data Case Study

eBook: Assessing Credit Worthiness with Alternative Data

Download the eBook to learn how a leading credit card and consumer lending company improved their financial risk modeling to evaluate applicants for online loans and digital credit cards.