Brands
Discover
Events
Newsletter
More

Follow Us

twitterfacebookinstagramyoutube
Youtstory

Brands

Resources

Stories

General

In-Depth

Announcement

Reports

News

Funding

Startup Sectors

Women in tech

Sportstech

Agritech

E-Commerce

Education

Lifestyle

Entertainment

Art & Culture

Travel & Leisure

Curtain Raiser

Wine and Food

YSTV

ADVERTISEMENT
Advertise with us

Decoding AI's impact on fintech lending, security, and inclusivity

Tanya Naik of PineLabs and Sabyasachi Senapati of Trillion Loans discussed how AI is powering more personalised fintech experiences at TechSparks Mumbai 2024.

Decoding AI's impact on fintech lending, security, and inclusivity

Saturday March 23, 2024 , 2 min Read

At TechSparks Mumbai 2024, experts from the fintech sector decoded the impact of Artificial Intelligence (AI) tools on fintech products and services in India, explaining that the maximum impact has been on improving lending and enhancing security.

Tanya Naik, Head - Online & Omnichannel Business, Pine Labs, joined Sabyasachi Senapati, Whole-time director, trillion loans (A BharatPe Group Company), at a panel discussion at the tech summit, and the two industry leaders shared how AI is powering more personalised experiences at scale.

Lending to merchants is a focus area for fintechs, and so, they are exploring AI-backed lending strategies to scale lending while keeping portfolio losses in check.

"Credit decisioning and underwriting is improving with AI because it helps make your algorithms more smart and dynamic, and your insights more meaningful," said Senapati.

Besides lending, AI can also provide insights on how to collect debt better, said Naik.

"Further, with better data analysis through AI tools, we can predict merchant churn better and create efficiencies for our field service representatives," she added.

Another key area of focus is heightening security of transactions.

"Identifying transaction patterns is critical to addressing fraudulent behaviour. With AI, we can also derive the types of customer profiles that are more prone to fraud," said Naik.

AI is also helping improve success rates for 'good' users, i.e., honest users who have been through various levels of authentication.

Senapati lauded these efforts, but highlighted that AI still has some way to go in making fintech truly more inclusive.

According to him, while frontend UI, customer channels, documents, etc., are being translated into regional languages using AI, culture-specific nuances are still not addressed.

"A lot more has to be done to account for region-specific nuances. A translation may be superficial. How do you account for region-specific differences, train the model on these data sets, and build it into the outcomes?," he said.


Edited by Megha Reddy