KL University students to develop a Machine Learning-based CIBIL Risk Analyser, simplifying credit risk assessment

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Students from KLH Aziznagar, a constituent of KL University with a 45+ year legacy, are developing a machine learning-based CIBIL Risk Analyser designed to assess an applicant’s financial profile and classify credit risk as low, medium, or high.

The project was initiated after the students studied how financial institutions evaluate factors such as credit scores, repayment history, income, existing debt, and overall financial conduct before making lending decisions. By bringing these indicators into a single assessment system, the students aim to explore how technology can support faster and more consistent credit risk evaluation.

Taking out a loan can be one of the most important financial decisions in a person’s life, whether it is for higher education, a business, a home, or emergency expenses. For financial institutions, however, every application requires assessing multiple financial indicators before a lending decision can be made.

This process caught the attention of the KLU students. During their research, they observed that lenders consider several factors to assess an applicant’s creditworthiness. Analysing such information manually can be time-consuming and may also lead to inconsistencies.

The students are now working on the CIBIL Risk Analyser, an intelligent system that brings multiple financial indicators into a single evaluation. The system is designed to scan an applicant’s financial profile and classify the level of credit risk as low, medium, or high.

The CIBIL Risk Analyser uses machine learning and data-based analytics to examine key financial indicators and build a broader profile of each applicant. By combining intelligent algorithms with structured data processing, the project explores how technology can make credit risk assessment quicker, more efficient, and more consistent.

The project is currently in the development stage and demonstrates the potential of emerging technologies to address a real-world challenge affecting both lenders and borrowers. It also reflects the curiosity and problem-solving approach encouraged across top universities in South India, as KLU students work on practical applications of technology beyond the classroom.

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