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Predictive Data Analytics

Make data-driven decisions and improve business processes and outcomes with precise analytics.

Business Intelligence, Data Analytics & Predictive Forecasting Analytics

CRIF has developed an in-depth understanding of the business processes of its banking and insurance clients. The result is the ability to build data-driven business solutions thanks to the available information assets.

CRIF Business Intelligence and Data Analytics involves planning, designing, and delivering data science business applications based on proprietary, open, web, alternative, and big data. 

CRIF is a valued partner in developing and implementing advanced analytics business solutions through:

  • Knowledge of business banking processes, enabling us to support our clients in the selection and processing of internal data to maximize the effectiveness of predictive models;
  • An accurate and diverse proprietary data ecosystem that integrates with open sources and internal bank data, completing the range of information needed to understand the different phenomena;
  • Significant market experience in developing “augmented” analytical models, recognized by independent research firms;
  • A team of more than 200 data scientists around the world, dedicated to data-driven research and innovation;
  • An end-to-end approach, from model design and development to the application and integration into business processes, thanks to a specialist advisory service and dedicated modular as-a-service management platforms;

Experience in cross-country and cross-industry data augmentation projects, enabling a rapid scale-up; ready-to-use platforms for the implementation of AI-based processes, both in SaaS mode (CRIF Studio platform) and on-premises.

Key Benefits

  • Significant reduction of loss ratios

    Optimization of risk forecasts in multiple domains, from identifying drivers to weather-related damage or digital identity.

  • Business and consumer insights

    Strategic campaigns, with unparalleled geographic data points and industry-specific scores.

  • Risk measurement

    Measurement of contagion effects of risk and virtuous circles linked to belonging to a network of companies, reducing credit losses.

  • Significant and meaningful cost savings

    Accurate algorithms improve the reliability of liquidity forecasts and generate greater control over key decisions.

Solution details

CRIF Business Intelligence and Data Analytics involves planning, designing, and delivering data science business applications based on proprietary, open, web, alternative, and big data

By innovating how data is used, CRIF enhances efficiency across multiple processes and industries, including pricing sophistication, improved campaign targeting, reduced false positives in transaction monitoring, stronger fraud prevention, more reliable liquidity forecasting, and better compliance with ESG and transition‑risk requirements.

Other solutions

Credit, Risk & Digital Consulting