Empowering Fin-tech Merchants: AI-Powered Interactive Information Journeys in Real-world Trials
Yixiang Xu, Rupalee Ruchismita, Ganesh Iyer
Collaborators
FINO Payments Bank
Grants
Researcher Assistants
Yisen Du
- Chinese University of Hong Kong, Shenzhen
Nikhil Goyal
- Indian Institute of Technology-KGP
Varun Rao
- Hindu College, University of Delhi
In emerging markets, local merchants often act as financial agents, providing crucial access to banking services for underserved communities. By significantly reducing the cost of financial access, these fintech-enabled merchants offer a promising path for financial inclusion.
However, this channel suffers from poor merchant retention rates. A range of factors, including the high cost of sourcing both firm and market information impede merchant profitability. Indeed, of the 3,000 surveyed merchants, more than 50% found it difficult to acquire necessary know-how to provide reliable banking services. For the fintech firms, providing timely assistance to a large number of dispersed merchants has proven to be financially unsustainable, creating a demand for low-cost technologies for network support.
To mitigate these challenges, we leverage Generative AI to design personalized, interactive and digestible ‘information journeys’ covering a wide range of business-relevant content for merchants. To further enhance the information acquisition experience for merchants, we use Large Language Models (LLM) to create multimedia content with text, audio and video content journeys in the local language.
Research Methods
AI in emerging markets
This study offers insights on General-purpose AI’s ability to undertake content personalization, especially in data-scare emerging markets facing cold start problems.
Oversight for equity and quality
We investigate conditions where human-AI collaboration versus AI-delegation more effectively aligns AI content personalization with merchant needs. In addition to equity concerns and ongoing AI quality concerns, and emerging market infrastructure limitations were factors which supported a decision to avoid a direct AI supported merchant chatbot, but one intermediated by humans/researchers.
Business and Policy Implications
For the fintech firms, we hope this experiment has insights on contexts where merchant support services can be handled by AI supported solutions. We also offer insights into the extent to which the mainstream Generative AI is generalizable to emerging market contexts and the necessity of developing localized GAI solutions for these markets.