How to Become a Data-Driven Bank

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New analytics tools help community banks harness business intelligence

By Nancy Michael and Mehna Raissi, Senior Directors, Moody’s Analytics

To read the entire whitepaper, click here:  

Banks collect lots of data on their customers, but they aren’t always adept at using it to grow their business. Community banks, in particular, are just beginning to realize the power of data analytics and business intelligence (BI).

Client data and the tools to analyze it can transform how banks conduct their commercial lending business. Data-driven banks can leverage analytics to make better informed decisions, streamline operations, and improve customer service. Here are some practical recommendations for a community bank that wants to turn data analysis into bottom-line results.

Define the data universe. The data that community banks can use includes company financials, qualitative customer data, and borrower behavioral data, including payment and credit utilization history. Establishing a centralized system that captures this unstructured data consistently is the first step in this process.

Consider a partnership. Effective analytics strategies ensure that short- and long-term goals are aligned with the bank’s current business operations. Partnering with a vendor with the required analytics technology and implementation expertise could help the bank capture the right data and integrate it into their processes.

Data quality is key. The top tactical issues with this approach involve collecting, organizing, and protecting the quality of the data. Maintaining the integrity of analytics requires clean data that is accurate, comprehensive, and continually updated. Data quality is key to realizing the value of BI tools.

Communicate early and often. Educating the organization on the value of credit measures, whether back office risk managers or front office sales professionals, will equip all stakeholders with a solid understanding of the new analytic tools and how they support the overall goals of the bank.

Leveraging advanced data analytics and BI tools is an investment that, if properly implemented, should pay dividends in the form of higher quality loans, better customer service, and increased operational efficiency.

Three Steps for Successful Adoption

  1. Support investment in systems that organize and centralize data and standardize processes
  2. Reinforce the systems investment with policy, training, and change management initiatives
  3. Champion the new systems and processes and how they contribute to the bank’s success


To read more, download the entire whitepaper: How to Become a Data-Driven Bank.