Problem
Objective
With the aim of enhancing collection efficiency and overcoming challenges faced by rural farmers in Rajasthan, we pursued a dual methodology.
Data Analysis
Analyzed feedback from 1015 customers using spocto’s analytical tools, including the spocto score and recommendation guru.
Primary Research: Conducted extensive field research, engaging with 45 end borrowers in Jodhpur, Jaisalmer, and Sri Ganga Nagar.
Problem Statement Identified
- Linguistic Barrier:
Communication hurdles due to diverse languages spoken. - Misinformation:
Inaccurate understanding of credit terms and processes. - Informal Credit Economy:
Dependence on informal lending channels. - Generational Gap:
Varied payment preferences across generations.
Our Solution
- Bhaasa:
Introduced “Bhaasa,” a multi-linguistic conversational bot designed to bridge the communication gap between lenders and borrowers. - KCC Educational Series:
Addressed misinformation by launching an educational series about Kisan Credit Cards (KCC), providing clear information on its benefits, terms, and application procedures.
Result
- Linguistic Barrier:
Bhaasa improved regional language interactions, enhancing engagement. - Misinformation:
KCC series clarified concepts, empowering farmers with accurate credit information. - Informal Credit Economy:
Awareness reduced reliance on informal sources, curbing exploitation risks.
Generational Gap: Tailored payments suited different age groups, enhancing convenience.
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