Rubix Data Sciences Wins ETBFSI Exceller Award for Analytics Solution

Mumbai, 5th December, 2024 – Rubix Data Sciences Pvt. Ltd. is delighted to announce that it has received the prestigious ETBFSI Exceller Award 2024 in the ‘Best Initiative in Analytics Solution of the Year’ category. The award has been presented in recognition of Rubix’s transformative initiative, the Rubix Risk Scoring Model.

The ETBFSI Exceller Awards celebrate outstanding achievements and innovations within the banking and financial services industry, and Rubix is humbled to have been selected for the Award in the field of analytics amidst very strong competition.

Revolutionising Credit Risk Assessment

The Rubix Risk Scoring Model is a cutting-edge solution designed to revolutionise the assessment and monitoring of credit risk for banks, financial institutions (FIs), credit insurance companies, NBFCs, fintechs, and corporates. This fully automated model leverages advanced AI/ML algorithms and integrates data from 120+ structured and unstructured sources, including financial, compliance, legal, and social media data.

The model assigns Risk Scores to businesses—including SMEs—on a near-real-time basis, enabling early identification of potentially risky counterparties. By offering rapid and reliable credit risk insights, the Rubix Risk Scoring Model empowers stakeholders to make informed decisions and implement timely measures to prevent credit losses.

Innovation in Action

This innovative solution addresses critical challenges in credit risk management, particularly for businesses such as proprietorships and partnerships, where regulatory disclosures and reliable financial data are often limited.

The Rubix Risk Scoring Model automates risk assessment processes, delivering actionable insights that enhance decision-making while being cost-effective and scalable. Banks, FIs, and corporates also use the model to assess B2B risks in their supply chains, helping mitigate exposure and build resilience across operations.

Rubix is proud to lead the charge in automating and optimizing credit risk management, enabling a safer and more efficient financial ecosystem for all stakeholders.