About the talk

The agri-fintech ecosystem represents the convergence of agricultural and financial technologies to address the unique challenges faced by farmers and stakeholders in the agricultural value chain. Using AI technologies, innovative solutions for crop insurance services, mobile payment systems, supply chain financing, and data-driven agricultural analytics are being developed, aimed at enhancing financial access and promoting sustainable practices in agriculture.

In this session, Raghu will share his experiences of building an agri-fintech solution, challenges faced in this ecosystem, and strategies for mitigating socio-technical risks.

Rumanu Bhardwaj and Rachna Maheshwari will moderate the session. Rumanu is a Machine Learning Researcher at ISB and Rachna works as a Practice Lead in Financial Risk Modelling with Crisil (S&P Global) in their global risk consulting practice and teaches Quantitative Finance as visiting faculty at institutions in Mumbai.

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About the speaker

Raghuchandra KR is the co-founder and CTO of AgriFi, and has specialized in agriculture technology for more than 8 years. He has previously contributed to NGOs like Rang De and Precision Agriculture for Development (PxD), and organizations like Cropin, where he shaped impactful initiatives.

RSVP and venue

This session will be held online on the 16th of February from 7 pm - 8 pm. You can RSVP to participate via Zoom or watch the livestream on YouTube.

About the AI and Risk Mitigation series

This session is part of the AI and Risk Mitigation series which will host meet-ups/talks on agritech, healthtech, fintech, ed-tech, and public services. The aim of this project is to:

  1. Build a community that will engage in issues of AI security, privacy, etc. and best practices to mitigate them.
  2. Develop a knowledge repository in the form of practical guidelines and a self-regulated charter for Ethical AI based on these sessions.

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About Anthill Inside

Anthill Inside is a community where topics in AI and Deep Learning such as tools and technologies, methodologies and strategies for incorporating AI and Deep Learning into various applications and businesses, and AI engineering are discussed. Furthermore, Anthill Inside places a strong emphasis on exploring and addressing ethical concerns, privacy, and the issue of bias both in practice and within AI products.

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