Comprehensive and dynamic credit scoring model
Technology based Credit Model
Proprietary methodology and advanced data science combining to reduce risk and assess the true credit worthiness of borrowers
Improved Efficiency
Faster and more accurate credit scoring enabling faster loan processing with reduced resources and cost
Increased Conversions
Reduced decisioning time, accurate assessments and lower costs allowing expansion of client base
Efficient, proprietary credit scoring process
Increase in Data Accuracy
Unique AI driven framework for credit assessment, better “predictive profiling” and monitoring
Comprehensive Assessment
Holistic and robust credit assessment across a wide range of traditional as well as new age digital parameters
“Technology first” Credit Scoring
Standardized and transparent credit assessment based on digitized information gathering supported by manual overview
Dynamic Credit Modelling
AI enabled unique Risk Engine will regularly recalibrate to accurately predict credit risk for specific target customer groups
Robust and Scalable Software
Highly scalable technology capable of meeting the increasing business requirements of FI partners
A winning proposition for lenders
Larger Customer Base
Robust and automated credit scores will enable banks to reach out to thin file clients and untapped borrower pools
Better Credit Insights
Comprehensive data gathering and AI based analytics will provide superior understanding of the customer improving borrower selection
Reduced subjectivity in Credit Scoring
A digitized process removes the subjective nature of manual credit assessment improving objectivity and auditability
Better pricing for Loans
Highly calibrated credit decision engine allows better pricing flexibility for lenders
Reduced Losses
Improved customer insights coupled with better risk prediction leads to reduced losses and better balance sheet management
Granular, Module based Assessment
Unique modules based scoring process which analyses different sets of parameters individually before looking at the sum of parts