1 min read
Success of Developing a Credit Score for Farmer Loan Financing
When joining iFarmer, I came equipped with a background in IoT technology development and business strategy planning and I was hungry to challenge myself further to solve new problems.
My major philosophy in life is to do things with a purpose for mankind and see it's use. So joining iFarmer, I got a scope to play around with data more and work on multiple projects among which was generating a Farmer Credit Score.
This project has rather been an interesting one as I had the opportunity to play with the data and conceptualize how we will generate a score - collecting multiple types of data from different sources, carry out data wrangling techniques to make the data easier to analyse and carry out feature engineering to develop a scoring mechanism. Finally at the end of it all, use machine learning to see how our model would perform on the real world data. And for all it's worth, our first version generated a score with mean absolute error rate less than 10%.
This is a milestone for me as I could be part of developing product from scratch that will be used to assess farmer credits scores to support banks and the company for loan financing applications. As for my aspirations, I got to apply Machine Learning to real world business cases to solve problems and more importantly in the Fintech space which is a domain that always fascinated me.
I'd like to thank our CEO, Fahad I. for setting standards for the company to reach through his vision and also my Team Lead A.S.M. Pushon for guiding us in the process.
Finally I'd like to thank the Data Team as a whole, as at the end of the day - team work makes the dream work!
To more interesting business problems to solve and improving on our skills as we go forward.
#machinelearning #data #business #engineering #opportunity #technology #iot #fintech #ceo #projects #banks #problemsolving
#productdevelopment #creditscore #agritech