Leveraging technology and strategy
CRIF, a global fintech and information services provider, faced a significant challenge as their cloud consumption rapidly increased. Managing costs across multiple providers like Amazon and Azure became increasingly complex. A unified approach to cost control to minimize inefficiencies has always been at the core of CRIF’s strategy.
Mr. Massimo Gentilini, CRIF Corporate CTO, explains, “Cloud provider invoices are detailed but very complicated, so you need a tool that provides a comprehensible, simple, and transparent summary like IBM Apptio™.”
CRIF integrated the IBM® Cloudability® platform into their existing systems to tackle their cloud cost management challenges. The Cloudability solution is contained within the IBM Apptio® FinOps portfolio and boasts advanced allocation features, such as intelligent mappings, to provide centralized visibility into the costs of various roles across the business. Cloudability includes dashboards and easy-to-understand reporting that surfaces detailed cost breakdowns tailored for various stakeholders across the business. In addition, CRIF is able to optimize their cloud resources effectively and identify areas of potential waste using the solution’s powerful—but user-friendly— optimization recommendations.
Mr. Gentilini highlights, “We understood that we had to use AI to generate efficiency in processes, operations, systems, and code writing—all in a phase in which things were changing very quickly and it was not easy to adapt resources.” The implementation process included data loading from AWS and Azure, integration with Active Directory for Single Sign-On, and comprehensive user training. The collaboration with IBM, supported CRIF in optimizing financial processes and strengthened the company’s capacity for future innovation and growth.
After implementing the new solution, CRIF observed gains in both financial and operational efficiency. Implementing Cloudability provided significant cost savings and enhanced transparency in cloud spending. This optimization allowed CRIF to allocate resources more strategically, advance AI initiatives, and further enhance financial decision-making.
Mr. Gentilini notes, “Cloudability has enabled us to manage cloud costs more effectively, reducing waste and optimizing resource usage, which has greatly improved our operational efficiency.” As an ongoing collaborator, IBM continues to support CRIF in their journey toward sustainable growth, helping ensure they remain at the forefront of technological innovation and cost management.
CRIFis a global company specializing in credit and business information systems, analytics, outsourcing and processing services, as well as advanced digital and open banking solutions for business development. CRIF aims to create value for consumers, businesses and financial institutions by providing information and solutions that enable more powerful decision-making, improve access to credit and accelerate digital innovation. CRIF also offers fraud prevention and cybersecurity services to consumers and SMEs. Furthermore, CRIF Ratings, a credit rating agency registered with ESMA and an External Credit Assessment Institution (ECAI), provides credit ratings and assessments on non-financial companies based in the EU. CRIF is also an AISP in all European countries where the PSD2 directive for open banking is applicable, and an AISP in the UK. Founded in Bologna in 1988, today the company operates in 37 countries across 4 continents, with over 6,600 professionals. Over 10,500 banks and financial institutions, more than 450 insurance companies, 90,000 businesses and 1,000,000 consumers currently use CRIF’s services.
© Copyright IBM Corporation 2025. IBM, the IBM logo, Apptio, Cloudability, and IBM Apptio are trademarks or registered trademarks of IBM Corp., in the U.S. and/or other countries.
Microsoft is a trademark of Microsoft Corporation in the United States, other countries, or both.
Examples presented as illustrative only. Actual results will vary based on client configurations and conditions and, therefore, generally expected results cannot be provided.