Home / Banking Strategies / Fueling the data analytics engine

Fueling the data analytics engine

Hidden within the piles of documents at banks and credit unions is a reservoir of insights that intelligent automation can bring to life.


Sep 16, 2022 / Marketing & Sales

The entire banking industry is in a state of tectonic flux, the kind of industry reset that probably hasn’t been seen since the Great Depression. These challenges – among them, rising interest rates, declining or static net income and increasing regulatory compliance requirements – are combining to create unprecedented challenges for executive management and boards of directors.

Because banking institutions are largely unable to control earnings issues related to interest rates, they must focus on the issues they can control: labor costs, facilities management, IT and marketing, to name the big ones. This requires a commitment to optimizing processes, which in turn requires collecting and analyzing relevant information.

The principal source of this information gathering is, of course, documents. Documents provide the very basis of financial transactions and the flow of money, which is why bank regulators put such an emphasis on having them in order.

The problem is that the task of gathering documents, extracting valuable information and putting it to work is a manually intensive effort requiring the attention of a dwindling resource: bank employees. And for organizations with adequate resources, generating insights means dredging for information buried deep within a sea of unstructured documents strewn throughout the enterprise.

So how do we turn on the spigot of a sustained and deeper flow of information for data-driven insights? The answer has two parts: planning and technology.

Start by defining objectives: What is the bank trying to achieve, and what does it need to know to be successful? Is it looking to achieve a 360-degree view of the customer and enhance the ability to cross-sell and upsell? Maybe the bank wants to facilitate partnerships and integrations to enable faster expansion of service offerings. Or maybe it just wants to make the next audit less stressful. Once the bank knows what it wants to achieve, it can determine the kinds of information it needs to collect and establish processes and systems to make that information actionable.

Then put automation to work: Banks and credit unions will become more data-driven not by gathering more data but by tapping the data trapped in the mountains of documents they already have. At the heart of every successful data-driven organization is an intelligent automation service layer. This automation layer performs a consistent, reliable set of actions for all documents: accepting, classifying, extracting specific data sought and flowing document and data downstream to any process or system that needs it.

For most FIs, merely getting this far would provide a wellspring of benefits in terms of serving customers more effectively, enabling more straight-through processing, relieving employees of most mundane tasks and improving compliance.

However, taking it only this far would be a lost opportunity. Now that the information is embedded within the analytical systems of the institution, it is available for analysis and can be used to track a variety of metrics like cost per origination, average time to close for lending transactions, new account setup error rates and more.

Bear in mind that the move toward becoming data-driven involves more than a one-time investment in technology. The entire organization needs to adopt a data-driven mindset and commit to collecting what is needed, performing the analysis and maintaining the discipline to modify the models as goals shift.

Coming back around to compliance, the final revisions to Section 1071 of the Dodd-Frank Act are an increasing focus of attention. Most community banks and credit unions are concerned that new requirements that involve document collection and retention will drive up underwriting costs and even force smaller institutions out of the market.


The changing intersection of banking and technology

Banks and fintechs are on the partnership track

U.S. banks are playing catch-up on digital technology

Moving from low-code hype to successful implementation

Analyzing banking data and putting it to good use

Implementing the intelligent automation services described above can put an institution in a much better position to not only implement policies and procedures that improve compliance but also provide a much stronger reporting platform to prove compliance.

The road ahead presents challenges unprecedented in our industry, and the old rules are fast becoming obsolete. Banks that become data-driven institutions may be able to innovate while doing more with less. This can be accomplished by automating everyday document processes and putting more information to work.

Joe Labbe is vice president and managing director at KnowledgeLake. Bob Browne is president and CEO of Cedar Creek Consulting Inc.

Learn how financial services organizations can use data to create strong relationships and enhance other business opportunities in the BAI Executive Report, “The power of data: How banks and credit unions can put it to work.”