Analytics in Banking

The banking industry is going through a transformation requiring banks to make data and analytics an integral part of their processes and workflows. This transformation is driven in part by emerging fintech providers, who are entirely digital and built on top of cutting-edge technologies and analytics. At the same time, consumers are increasingly using mobile and online banking services. For example, one study found that 89 percent of consumers use mobile banking, and 70 percent said mobile banking is now their primary method for accessing their accounts. Business Insider predicts that the digital-only bank—or neo bank—market is poised for significant growth. This trend will be fuelled mostly by millennials who are frustrated with legacy financial providers.

In turn, digital disruptors and tech-savvy customers are putting pressure on traditional banks to modernize and embrace data-driven strategies. Right now, though, the banking industry is still behind the curve, as 92 of the top 100 global banks are still running on legacy IBM mainframes. While IBM mainframes are useful for processing large volumes of transactions, they’re less helpful for managing big data.

Yesterday’s systems and processes are no longer capable of serving digital consumers. As we move deeper into the digital era, the need to modernize will become even more critical. It is why an increasing number of banking institutions turn to big data analytics to figure out the best path forward.

After the initial big data explosion more than a decade ago, companies started racing to collect data despite lacking the tools to store and process it, making it very difficult to discover critical insights. This problem has gotten worse over time, too, as data has grown in volume and complexity. Today, around 2.5 quintillion bytes are created every day—a figure that’s certain to keep growing larger as we move further into the future.

To improve data management, a growing number of companies are turning to big data analytics solutions that prepare, process, and examine large data sets. Big Data analytics in the banking market are expected to grow at a 12.7 percent CAGR through 2025, with the market on pace to exceed $62 billion by then.

Thanks to advanced analytics in banking, financial organizations can now act with far greater agility than they could in the past. Simultaneously, with analytics, it’s becoming much more comfortable to predict future market conditions and emerging customer trends.

With that in mind, here are some of the ways banks are using data analytics to grow during this period of transformation.

Being in an industry that is getting transformed, are you and your team receiving more business questions that require deep analytics with short turnaround times? Do you grapple with data silos and a lack of tools to bridge those silos and foster collaboration among analytics team members?

DDC Spotlight helps analytics teams discover and merge data from multiple disparate databases, making it possible to discover insights that would otherwise go undetected. With robust integrations with a wide range of data sources and Business Intelligence and Data Science tools that your team relies on every day, DDC Spotlight serves as a virtual analytics hub that can take you from Data to Insights faster than ever.