CRIF's experience in data analysis and its use in a proper and proactive way coincides with the core of the Management Consulting practice: that is to guide the client in the management of the credit value chain as well as risk, through the analysis of data relating to business and the market, with the identification of the best approach to credit management. The offering today is nevertheless broader. CRIF continues to be a leading company in data management, business information and outsourcing. CRIF Credit Solutions is known for excellence in providing integrated solutions which manage the entire value chain of credit (CRIF Credit Management Platform). In this context it was essential to go beyond analytics and processes and to integrate them with regulatory advisory, risk management evolved with advanced models, strategies and credit processes for the conceptual development of software solutions and support services such as BPO, as well as the evolution of 'research' which leverages CRIF information assets.
The areas of interest have been identified in order to provide targeted support for different phases of the customer credit life cycle, alongside the offer of CRIF and CRIF Credit Solutions as a whole. Specifically, it was crucial to distinguish between 'services provided on an ongoing basis' and services that are 'pure consulting'.
Risk Management and Predictive Analytics
Predictive analytics is the practice of extracting information from existing data in order to determine patterns and predict future outcomes and trends. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessment.
Recognized by Gartner, CRIF's expertise in predictive analytics, is demonstrated by the development of numerous scoring projects in many including Bureau scoring models, spanning over 18 countries which in total are used to make hundreds of millions of score calculations and decisions every year around the world.
Credit Bureau Scoring Systems
Credit bureau scores are a key part of banks and financial institutions risk assessment processes since they help improve the predicitability of a credit risk based decision. A credit bureau scoring system represents a powerful instrument to improve and enhance credit processes. It summarizes all the information contained in the credit report of a person or business into a number of potential risk factors using the proven power of predictive analytics.
CRIF's credit bureau scoring systems are used to make hundreds of millions of credit decisions every year worldwide, spanning Americas, Europe, Africa and Asia. Our customers have benefited from CRIF's analytic, objective and easy-to-implement solution which optimizes the value of data and in turn improves service and capabilities provided to their customers.
Regulation & Governance
Credit risk management experts who provide advisory services for governance, risk assessment and management, within a constantly evolving regulatory context. We can help you with:
- Governance: SREP, RAF, ICAAP
- Internal Control System Evolution: Early Warning, Second Line of defense, Internal Validation & Regulatory Benchmarking
- Supervisory Advisory: Asset Quality Review, NPE Guidelines & Plan
- Basel advisory: RWA Optimization Std & IRB, Basel Roadmapping
- Impairment advisory: modelling, validation & credit policy (IFRS9, Calendar Provisioning, Due diligence)
- Information Framework content Evolution: COREP, NPLs, Anacredit, AQR...
Process and Strategy Optimization
Putting our knowledge into practice by helping our customers analyze and improve the efficiency and effectiveness of business operations and strategies in every phase of the credit lifecycle, from engagement and origination to customer management and debt collection.
Marketing & benchmarking expertise to help our customers attract, retain and grow their customer base. By leveraging data and applying predictive analytics, we can help our customers to:
- have a strategic view of the market and its trends;
- understand their own performance in relation to the market and clusters of competitors;
- identify within their own customer base the most profitable segments and those with the highest propensity for up-selling/cross-selling;
- identify the best places to find new customers or to expand or modify the sales network.