I feel the need to voice this concern about the financial industry. Maybe I shouldn’t—I actually think it’s a recipe for success and I certainly don’t want to give the competition too much fuel.

But, I genuinely feel you’ll read this, be inspired, and take no action.

You’ll agree, but you won’t change. You’ll like what I have to say, but not take on the fearless attitude required to cut through varying degrees of bureaucracy, organizational politics, and technological sludge. Forgive my cynicism, but remember, I’ve worked in the banking industry for some time now.

The Current State of Data in Financial Institutions

There are good conversations taking place between financial marketing teams, IT departments, and bank C-suite execs across the country, conversations about the “multi-channel” retail world in which we live, the need to improve the “branch experience,” and preparing companies to “go mobile.” These discussions center around implementing new customer-facing technologies, evolving the role of a branch banker, and exploring back office automation tools that signal the greatest leap in financial experience since the arrival of online banking in the mid-90s.

Yet, good conversations on how to better use data remain elusive. Banks have pursued “better reporting” since computers replaced paper ledgers decades ago, and reporting is better, too. It just hasn’t evolved. We still rely on classic metrics about our customers to determine their value and potential. Reports like “Top 25 clients by deposit dollars” or “Customers who have online banking” continue to define the furthest reaches of accessible customer intelligence at small- and mid-sized banks.

There has been little buy-in for new metrics from those at the top of financial companies, and plenty of pushback on just how much data and customer intelligence can actually inform marketing, selling, and service decisions.

The current modus operandi? In most banks with less than $10 billion in assets, data is delivered as:

  • PowerPoint presentations, PDFs, or Excel worksheets from a vendor you hired
  • MCIF export files
  • IT reports
  • An analyst’s combination of three to four spreadsheets

This information often satisfies a single reporting need by answering isolated questions like these:

  • How did we do on deposit growth in this market over the past six months?
  • What does loan growth look like in Region X?
  • How many CDs are 45 days from maturity?

Then, there are the occasional deep-dives, which include questions like these:

  • How many active mobile banking users do we have?
  • How many of our customers bank elsewhere?
  • Who are our most profitable customers? (Cue the cringing.)
  • How many products do we sell in the first 90 days of a new relationship?

These are the questions that, frankly, lead to a type of reporting that’s often misguided and simply incorrect thanks to disparate systems, incomplete vendor service, and poor aggregation practices.

Don’t Agree? Try This Experiment.

Determine one report you need, like a three- or six-month trend report. Next, request this report from your IT department or from the technology or product vendor where your data is housed. Then, if possible, request the same data from another source within the bank. Also, have a vendor use the same data to pull down the numbers for you. Try to get the info yourself if possible.

Compare notes. On the standard reports (DDA growth, loan growth, CD maturities), everything might be close. If it’s not, you have much more work ahead of you. On a deep-dive report, I imagine you’re going to see some variation—maybe a lot of variation.

How Can Financial Institutions Improve Their Data Intelligence?

You could write a book on this. Quite a few people have already, but your ability to make improvements boils down to two fundamentals: data integrity and distribution.

How To Repair Data Integrity

Data integrity starts with proper aggregation, and proper aggregation starts with strategic mapping. You may have 25+ potential data feeds (vendor applications, core database, website, marketing tools, CRM, etc.) with 20,000+ measurable items across those feeds. You’re not going to get it all right at first ingestion, nor should you try to wrap your arms around everything on the first day.

Here’s how to get your feet wet:

  1. Start by (literally) drawing all your systems out on paper or on a whiteboard.
  2. Identify the top three assets in each system you believe will address your goals (e.g. increased products/household, increased credit card engagement, bill pay adoption).
  3. Identify the “glue” asset, or assets, between key systems. Customer numbers, Social Security or ITIN numbers, card numbers, IP addresses, and email addresses are common glues.
  4. Identify the data or file language produced from each system (C, Java, image, text, SQL, etc.).
  5. Determine if data is convertible to a standard. If not, write clear rules for how the non-standard data will be connected back to the record.
  6. Ingest a few elements at a time and test the “full view” of the customer record.
  7. Show a full warehouse record for one customer and then check it against the individual data sources to measure quality.

That’s seven steps. Sounds pretty easy, right? You’ll encounter a lot of incompatibility and system limitations along the way, but the best advice for data integrity is to record everything—every rule, every qualifier, assumption, and missing piece. Keep it all clearly defined against the database solution you use.

Distribute Data and Intelligence Wisely

Banking (like many other industries) has long struggled to find the best way to share good information with their frontline employees and decision makers. There are endless reporting solutions with fancy dashboards and automated or customizable reports. Many offer employees a better view of their customers and prospects than they would otherwise have. However, some key underlying activities can make or break your data distribution strategy as well as the resulting adoption of these types of solutions within your company.

Passive vs. Active Distribution

When do you push information and when do you let users discover it? Think about the timing of each report relative to your employees’ schedules. Is a morning email about prospects the best idea because you’ve trained employees to follow up with prospects during the first 15 minutes of the day? Or is it the worst time for a prospect report because your branch employees are busy returning emails and voicemails, all while scurrying around to get their branches open on time? Ask your employees about timing.

Making It Actionable

You hear this often, but data is only as good as it is actionable. But, for some reason, we fail to provide clear actions within the context of the available data. Since five employees could look at the same data set differently, how do you help guide each of their perspectives? Every report should contain at least three to five scenario-based examples of what to do. Scripts and ancillary training materials help as well.

Onboarding and Training

Training applies to every new process and tool at your company. But, within the financial industry, training on customer analysis can feel like the most unnatural educational topic on an agenda.

Make sure you can track employee engagement with your data reporting tools. You’ll have superusers, monthly users, and inactive users. Many of the inactive users need help understanding the value of the report and how to use it, while monthly users might only engage with reports actively pushed their way. Superusers can be your evangelists and assist your Training department. Understand who falls into which group, then target your training accordingly.