Center For Customer Protection

The survey was conducted between March and April of this year in partnership with Gram Vaani, a social technology company, in seven districts of Rajasthan: Ajmer, Alwar, Bharatpur, Bundi, Dausa, Deeg, and Jaipur.

Fairness, explainability and human-in-the-loop principle are vital elements of Responsible AI

By studying people’s instinctive, unguided ‘trust-decisions’, we hope to uncover their mental models of trust. More specifically, we aim to (i) articulate the expectations that customers have of trustworthy lenders, (ii) help lenders design their products in a manner consistent with the customer's expectations, and (iii) translate these principle-level expectations into processes that lenders may adopt in their customer service to become trustworthy.

This Whitepaper unpacks what RTAI would mean in the context of digital lending. While the term Responsible AI has been adequately conceptualized in academia and elsewhere, it still needs to be coherently contextualized to specific domains.

In this blog, we delve further to uncover the institutional, cultural, and evolutionary factors underpinning the challenges of engendering formal savings among LIHs.

In this paper, we aim to identify the challenges and opportunities in financing regenerative agriculture within the context of smallholder farming in India and offer suggestions for enhancing the financing of regenerative agriculture in the country.

When AI-driven decisions are fair, respect privacy and are not opaque, they foster customer confidence

Almost 65% of India’s population lives in its rural areas.1 India’s financial sector has seen unprecedented expansion, driven by policy initiatives, digital infrastructure and regulatory reforms. Initiatives like Pradhan Mantri Jan-Dhan Yojana (PMJDY), Aadhaar-linked banking, Unified Payments Interface (UPI) and digital lending have significantly improved access to financial services, particularly for underserved segments.

This study sought to understand the impact of the new regulations on the microfinance sector through the lens of different categories of stakeholders – customers, leadership at microfinance institutions (MFIs) and intermediating staff.

The response presents our thinking on the governance of artificial intelligence (AI). It is divided into two parts. Part A summarises our key inputs which are also presented below in the form of this write-up. Part B provides a section-by-section paragraph-wise detailed feedback as per the Ministry’s Consultation Form requirements.