Winners are announced.
Welcome to Fibe- Hack the Vibe! Our credit scoring hackathon. The challenge is to develop a machine-learning model that can accurately predict which individuals are most likely to default on their loans. Using historical loan repayment behavior and transactional data, participants will need to create a robust model that can help lenders and financial institutions make informed decisions on extending or denying credit. This is a critical task as even the slightest chance of financial risk cannot be ignored in today's economy. Join us in this hackathon and showcase your skills in data analysis and machine learning to help improve credit decision-making processes and hack the vibe of the lending industry.
Participants are expected to build a robust Machine Learning Model based on a real-life problem statement (mentioned in themes section) faced by every Financial Institute who provides Credit Line facility.
Fibe (formerly known as EarlySalary) is one of India's leading consumer lending platforms focused on young, aspirational and tech-savvy Indian consumers. It is building a financial ecosystem that enables the mid-income group to fulfill their aspirations. It is an industry leader in the salary advance segment with the fastest processing time. Fibe has launched a host of financial products like cash loans, long-term personal loans and buy now pay later plans. It offers a 100 percent digital loan application process that takes just seconds to complete.
Fibe has grown multifold over the years and emerged as a market leader in providing financial assistance to young middle-income groups in India. It has been assigned a BBB+ rating by CARE Ratings and has been certified with ISO/IEC 27001 for its Information Security Management System (ISMS). The company has already disbursed more than 3.4 million loans worth Rs. 10,000+ crores.
Once registered for the Hackathon, your team leader will get a platform invite through email for submitting your solution on the ML platform.
The invite will start going out from 31st March.
Credit scoring is a statistical analysis performed by lenders and financial institutions to determine the ability of a person or a small, owner-operated business to repay. Lenders use credit scoring to help decide whether to extend or deny credit as for any organization, even the slightest chance of financial risk can not be ignored or ruled out. The objective of this challenge is to create a robust machine-learning model to predict which individuals are most likely to default on their loans, based on their historical loan repayment behavior and transactional activities.