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Italy’s Largest Bank Drives Big Data Decisions with Analytics

When you think about it, we’re really entering the third epoch of Big Data.

 

In the first epoch, businesses hustled to invest in infrastructures that could process the volume, variety and velocity of data coming from all directions. This represented a dramatic – and costly – evolution from BI-driven storage paradigms that provided a good look at what happened, but were less useful in predicting “what next” in a transformed world.

 

In the second epoch, organizations looked for ways to derive value from exponentially growing, diverse bodies of data – providing, of course, they could use it quickly enough so it didn’t become stale. Applications were created to help turn data into decisions, but most were cost-prohibitive to deploy and placed demands on core systems. Also, only a small subset of highly technical users had the ability to actually work with the data, meaning that most initiatives were “one-offs” – fun to play with, but not necessarily addressing the core business challenges that drove the Big Data investments in the first place.

 

Where are we now? Well, with cloud infrastructures, open architectures, and evolutions in Big Data processing all evolving the “how” of Big Data, a few organizations have evolved to the third epoch – making Big Data-driven decisions that drive customer experience, profitability, and risk management – all powered by analytic engines that can inform business units as to what happened, why, and what to do next – and when to do it.

 

Take Italy-based UniCredit, Italy’s largest bank, for example. It has adopted a corporate-wide strategy built around FICO decision management technologies to analyze high volumes of data across the enterprise and use prescriptive analytics to make better lending decisions and optimize its capital. Prescriptive analytics synthesize big data, predictive analytics and business rules to compare the likely outcomes of any number of actions, and choose the very best action to advance business objectives.

 

UniCredit’s big data risk management projects closely relate to a broader evolution that’s affecting the data infrastructure. It is replacing archaic decision-making processes by introducing a more agile, flexible and productive analytic-powered technology framework. FICO allows users across the spectrum – from data scientists to business analysts – to analyze data flowing across the system, thus democratizing the decision-making process and reducing traditional silos (e.g., originations and marketing) that can send conflicting messages to customers and adversely affect the organization’s risk profile.

 

To gain more insights regarding how UniCredit’s Big Data prescriptive analytics strategy is driving a new culture of decisioning within the organization, check out this case study: UniCredit uses FICO to apply prescriptive analytics to risk management.

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