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Community Banks and Their Data

Everyone has heard comments like these:

“Data is your greatest asset”.

“If you don’t learn how to leverage your data, you’ll be left behind”.

“Your number one technology challenge is to get control over your data”.

But is it really true for community banks? If so, why are so few doing anything about it?

What Data do Community Banks Have?

This may sound like an obvious question, but do community banks actually have useful data that they’re not already leveraging? Emphatically yes! Even if it isn’t in their own systems, they have access to many kinds of data. Banks’ data could drive marketing, sales, decision-making, risk management, and product design.

  • Customer data is the most obvious data that others don’t have the same access to. And the deeper a bank is into a customer’s business, the richer the data. Some is structured (e.g. transaction data) and some unstructured (e.g. financials, asset records). But it is also potentially valuable.
  • Bank financial data: when brought together, gives a stronger basis for risk management and financial decision-making.
  • Market data: gives insights into local markets and the prospective customers’ industries
  • Economic data: global, national and regional/local trend data. This should help with both marketing insights and portfolio risk management.

Why Data Matters to Community Banks

Community banks that plan to continue their current business model don’t need to do anything about their data. But they will also fall further and further behind. They are missing out on:

  • More focused marketing approaches that use data about markets and companies. These will allow better use of different media, and drive messaging to speak to real problems faced by banks’ customers.
  • Insight-driven sales: using the right media to approach the right people at companies most likely to buy bank services.
  • Management reporting and analysis. Allowing executives and senior managers to have a complete picture of bank operations and financials.
  • Deeper understanding of risk (credit, market and operational). Insights that will help with risk-based decision-making.
  • Design and delivery of new products. Meeting emerging customer needs, based on insights into customer businesses and industries.

So yes, data is very important for community banks. But it seems to be hard for them to get their arms around it. Why?

Why is Data Difficult for Community Banks?

I see several challenges that need to be overcome before banks can truly take advantage of their data.

  • Without a strategic plan for the bank’s development and even transformation over the coming years, it is hard to see how data will help the bank. It is a means to an end, not an end in itself.
  • Much of the bank’s data is locked up in its core banking system. As core vendor contracts are renewed, banks should look for increasing openness of systems. They should also demand flexibility of access to their data.
  • Most community banks do not have the in-house expertise to organize and utilize their data. Most of their outsource providers are generally not data specialists. There is a need for specialist firms that know data, and know the opportunities and challenges of community banks.
  • Bank boards are reluctant to invest in technology to the degree necessary for data management, analysis and reporting. In part this is because bank executives struggle to make the business case. However, now is the time to invest – while loan books are full and revenue streams area steady.

What Will It Take?

There are several steps that must be taken in order to harness the full value of a community bank’s data:

  1. Create a well-articulated business strategy. This will determine what a bank needs from its data, and indeed all its technology.
  2. Build a technology strategy that responds to each point of the business strategy. Such a strategy will almost certainly be data-centric. It will include an architecture that will provide access to all the bank’s data, as well as relevant data available from outside the bank. Elements may include:
    1. A data lake, which is a collection of all the different sources of data without focusing on format and structure. This data may be a mix of structured and unstructured data.
    2. A data integration platform that will validate, cleanse and transform data. This will make the data is usable by transactional systems and the data warehouse environment.
    3. One or more data warehouses to provide a general structure to all related pieces of data.
    4. Data marts and analytical views of the company’s data. These provide a window from the perspective of particular business functions (e.g. marketing, sales, finance, risk).
    5. Visualization tools that work with the functional views of data. They will allow building of reports, dashboards, interactive web pages, and insights to realize the data’s full value.
  3. Bring in data experts to build out and execute on the detailed steps. It doesn’t make sense for a community bank to build a data core competency. This is a good area to outsource. However due diligence, strong contracts, and rigorous vendor management are essential. Data is indeed one of a bank’s most critical assets, and must be protected accordingly.
  4. Get help from your data experts to design new data-driven customer products. These may also use Artificial Intelligence to analyze the data. These products will differentiate the bank from its competition (both bank and non-bank). For example, utilize your customer’s data to build out cash management products that will allow a bank to meet the needs of larger commercial customers.
  5. Continue to maintain, manage and leverage data as more becomes available. Create new views and visualizations as market conditions and customer needs change. Ideally outsource this to the same firm that build the data stack in the first place.

Conclusion

Bank CEOs and CIOs should be getting more from their data. As a result, they can transform their businesses.

Look for future posts to drill deeper into some of these topics.

 

 

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