CRIF Categorisation Engine, designed to reveal pivotal insights into your customer base, bridges the gap between unstructured data and structured insights.
By leveraging artificial intelligence and machine learning, we turn account and credit card transactional data into precise, actionable information to guide your strategic decision-making.
CRIF advanced analytics suite provides a series of Key Performance Indicators (KPIs), allowing you to assess your customer portfolio, focusing on risk monitoring, Know Your Customer (KYC) requirements, and cross-/upselling strategies. Additionally, the unique CRIF Score, is derived from current account information and the categorisation of banking descriptions, providing a valuable perspective on customer knowledge.
Beyond categorisation and scoring, our engine includes KPI and score calculation, account transaction categorisation, cash flow indicators, risk monitoring of your customer portfolio, and marketing intelligence insights. Our platform is designed to provide you with a competitive edge, reduce risk, and offering an all-encompassing understanding of your customer base, all targeted towards driving your business growth.
Refining your customer understanding and enabling targeted strategies for increased efficiency.
Leveraging CRIF Score and advanced analytics to reduce risks and potential losses by identifying early warning signs in your customer base.
Uncovering new-to-credit and new-to-country subjects and develop targeted cross-/upselling strategies for business expansion.
SUCCESS STORIES
Tier 1 bank and leading financial institution
The objectives of our client were to improve their scoring model, time-to-market and digital customer profiling. The results: 50% increase in KYC procedures and automatic applications, and marketing campaign success 3x higher compared to traditional approach.
Success Stories
Tier 1 Lender
Our client needed to improve their scoring model, time-to-market and digital customer profiling. This includes developing a transactions categorisation model, integrating the CRIF advanced analytics model and considering specific early warnings that impacted customer monitoring and risk management. The results: 50% increase in KYC procedures and automatic applications, and marketing campaign succeeded three times more than traditional approaches.
Success Stories
Tier 1 Lender
Our client wanted to strengthen their existing scoring model by refining the medium risk level, improve KYC and customer profiling, reduce risk of loss, and define risk avoidance plans. The results: 92% categorisation accuracy, and >50% GINI Credit Score of current account transaction data.
Discover how some of the world's most important financial organisations improved their performance and defined a brand-new digital path, both for them and for their clients.
Discover more on CRIF.Digital
Banking
