There’s more data available to banks than ever before. So why aren’t they using it to drive growth? Most commercial banks know that making better use of their data would have a significant impact on their business. As I discussed in my first post in this series, data can be used to improve a bank’s bottom line in several ways.  

As banks respond to the rich market valuations of data-driven fintechs, they are ramping up their investments in data, advanced analytics and artificial intelligence to start making their data work harder for them. But many banks are struggling to get out of the starting blocks and to sustain momentum in their journey to mastery of both internal and external data.  

Accenture’s report, “Data-driven mastery in commercial banking” has identified four barriers that often stand in the way of a successful transformation to data-driven banking. Let’s examine these barriers and what’s needed to overcome them. 

Organizational silos 

Data is most useful when it can be pulled together from multiple areas to create a complete picture of customer behaviors, risks, opportunities, preferences and more.  

Over the years, banks have built various departments and functions one at a time. This has created data silos that are difficult to access across functions and regions. Without the ability to harmonize data and technology assets, and to loosen the constraints around budgets, intellectual property and priorities, it is difficult to undertake large-scale data analysis using all of the available data. 

Solution: Reconfigure processes and systems and reorient the organizational culture to support easy sharing of data. Leaders can help by painting a picture of how data gathered from across departments can come together to improve overall results, and by putting resources in place to ensure that there are no technical barriers to sharing. Investments in enabling architecture such as cloud-based accelerators, self-service tooling and data hubs will help make cross-pollination of ideas and insights a reality. 

A focus on incremental improvement 

Many commercial banks try to gain traction for their data-driven transformation by starting with some small, easy wins. The problem is, this pattern establishes itself and the bank continues to focus on incremental improvements, rather than large-scale change. Compatibility problems can also arise if individual departments or functions are introducing their own data solutions, which are not part of an overall plan where all of the pieces work together. 

To turn data into a real competitive asset, leading banks are aligning their data strategy with their corporate strategy.

Solution: Data-driven growth must be part of the bank’s overall business strategy. Leaders are more likely to drive real growth when they are open to change on a large scale, rather than trying to retain the old, comfortable structures and use data as an add-on.  

Thinking big requires a leap of faith, but that is how data-driven businesses create value. Data should be used to drive new business models, not just to tweak current processes and products. 

Digital transformation fatigue 

Banks have been in the midst of a digital transformation for years. It may feel like technology becomes obsolete faster than it can even be implemented. This non-stop cycle of trying to keep up has made many banking leaders reluctant to embrace additional large (and expensive) IT projects—especially projects that extend beyond their area of expertise. If the benefits are unclear or hard to understand, it can be difficult to get C-suite buy-in. 

There has to be a clear plan for how data is going to be used by the bank. There is little value in collecting huge amounts of data and simply overwhelming staff with it. To be useful, data needs to be meaningful and consumable.  

Solution: Commercial banks need data evangelists in senior positions who can help to drive understanding and adoption. Most banking executives have a limited understanding of the specific ways that data can be used to jumpstart major growth. Create enthusiasm for change with a compelling vision of the transformation that an ambitious data-driven evolution can bring. Leverage leaders across lines of business and functional areas to rally support and boost the speed of enterprise change. And don’t forget the business case! Providing a clear and compelling view on what the journey will cost and what use cases and value drivers will be unlocked will help set the right expectations and create strong forward momentum. 

A lack of business ownership 

For many commercial banks, data has yet to become a C-suite priority. Successful fintech and bigtech companies are built from a data-first perspective, and their leaders know that the strategic use of data can make company value skyrocket. But this commitment to data-driven growth is not common in the banking world. In fact, in many banks, the widespread lack of such a commitment makes it difficult to prioritize bold, cutting-edge data projects.  

“81% of senior business leaders agree that data skills are required to become a senior leader in their companies, but two-thirds say they are not comfortable accessing or using data themselves.”

– Splunk

Solution: The leadership role for data-driven banking has to move from the technology department to the C-suite. Leaders at the board and executive levels can demonstrate their ownership of the bank’s transition by encouraging the sharing of knowledge, data-driven decision making, product orientation and appropriate risk-taking. They can also demonstrate the entrepreneurial mindset required to be successful in this space: be bold, be willing to experiment and make mistakes, stay alert and keep pushing. 

In the final post in this series, I’ll be explaining how banks can use machine learning and artificial intelligence to unlock exponential growth. 

Contact me to find out how your bank can overcome the barriers to mastering your data and transform it into growth.

In the meantime, you can register below to download the full report, Data-driven mastery in commercial banking.

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