Scratch around the surface of the internet and you’ll soon discover that the world generates over 400 million terabytes of data per day, or 147 zettabytes per year.
Banks and fintechs hold vast amounts of this data but struggle to extract value from it. CRIF, a leading credit bureau and data analytics and solutions provider, helps them unlock its potential.
“Data has always been in our DNA,” explains Claudio Sangiorgi, Business Development Manager for International Markets at CRIF.
Despite its many iterations and transformations over the years, CRIF has always maintained its focus on data. The company’s primary mission is to help businesses make sense of data by refining what’s already there—such as parsing account data for risk signals or sales opportunities—and enriching the data through external sources.
CRIF’s origins
Founded in 1988 as a credit bureau, CRIF has grown into a global business with over 6,600 employees and annual revenues of over €800 million. The company offers a comprehensive range of services, including data analytics, decision-making tools, and consultancy services.
In 2023, Forrester Wave recognized CRIF as a leader in AI decisioning platforms for its StrategyOne product.
CRIF designed StrategyOne as a comprehensive decision-making management platform for businesses, particularly in the financial sector. It serves as both a business rules management system and a decision-scoring engine.
The company also made the platform user-friendly so that it wouldn’t require a team of highly skilled IT personnel to configure it.
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AI and Innovation
“We established an innovation hub called InnovEcos to study, analyze, and test the most innovative trends and solutions, creating a network with fintechs and exploring emerging technologies such as quantum computing,” says Sangiorgi.
For several years, CRIF has also been providing ML- and AI-based decisioning solutions, making a natural move into generative AI when it emerged. The company has already leveraged generative AI to help clients automate processes and improve data quality, such as by making complex data more accessible.
For example, CRIF has used large language models (LLMs) to extract valuable insights from the typically unstructured documents involved in the credit process. By transforming unstructured data into structured data, this information can then be accurately processed by tried and tested tools.
CRIF in the Nordics
In the Nordics, the company has noticed an uptick in interest for subjects that were previously a higher priority for Mediterranean countries, such as collection, NPL (non-performing loan) management, and fraud prevention.
CRIF’s proven solutions can predict certain behaviors and warning signals, enabling financial institutions to reduce negative impacts and the associated costs.
“Another strength, particularly in the Nordics, is that we have many customers operating across multiple countries, and we can provide solutions that are multicountry, multilanguage, and multicurrency, capable of managing millions of transactions within a single production environment. These solutions can be provided as a service, on-cloud, or on-premise,” comments Sangiorgi.
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Looking to the future
CRIF’s priorities for the coming year include expanding its AI and ML capabilities to deliver more advanced decisioning solutions. It also wants to enhance its open banking services to provide greater value to its clients.
“Our aim is to strengthen our partnerships with clients by offering tailored solutions that address their specific needs and challenges, ultimately helping them to mitigate risks, reduce losses, and increase revenue,” explains Sangiorgi.
By staying at the forefront of technological advancements and maintaining a client-centric approach, CRIF believes it can continue to make a significant impact on the fintech ecosystem and drive positive change for its clients.