Why Data Intelligence Is Broken In The Financial Industry

HIPPO: Highest Paid Person's OpinionAs an employee in financial industry, I felt the need to voice this concern. Maybe I shouldn’t because I actually think it is a recipe for success and I certainly do not want to give the competition too much fuel. But, I genuinely feel you will read this, be inspired, and take no action. You’ll agree, but won’t change. You’ll like what I have to say, but not have 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

In financial marketing teams, IT departments and bank C-Suites across the country, there are good conversations taking place. Conversations about the “multi-channel” retail world in which we live, the need to improve the “branch experience” and prepare the company to “go mobile.” These discussions center around implementing new customer-facing technologies, evolving the role of a branch banker, and exploring digital tools that signal the strongest leap in financial experience since the arrival of online banking in the mid-90s.

Yet, a good conversation on how to better use data remains elusive. Banks have pursued “better reporting” since computers replaced paper ledgers decades ago. And reporting is better. It’s just not 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” are still the extent of accessible customer intelligence in small and mid-sized banks.

There has been little buy-in at the top of financial companies for new metrics and plenty of push back on how much data or customer intelligence can really inform marketing, selling and service decisions. The current modus operandi? In most banks under $10 billion in assets, data is delivered as:

  • A PowerPoint presentation, PDF or Excel worksheet from a vendor you hired.
  • An MCIF export file.
  • An IT report.
  • An analyst’s combination of 3-4 spreadsheets.

Often, this satisfies an isolated reporting need and answers standard questions like these:

  1. How did we do on deposit growth in this market over the past 6 months?
  2. What does loan growth look like in Region X?
  3. How many CDs are 45 days from maturity?

Then, there are the occasional deep dives. Questions like these:Sign You Need Better Business Intelligence

  1. How many active mobile banking users do we have?
  2. How many of our customers bank elsewhere?
  3. Who are our most profitable customers? (cue the cringing)
  4. 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 is 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. Make it a trend report. 3 months or 6 months. Request this report from your IT department or the technology or product vendor where the data is housed. Then request it from another source within the bank if possible. Also, have a vendor use the same data to pull down the numbers for you. Try it 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 deeper dive report, I imagine you are going to see some variation. Maybe a lot of variation.

How Financial Institutions Can Improve Their Data Intelligence

You could write a book on this. Quite a few people have already. But, it 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 are not going to get it all right at first ingestion. Nor should you try to wrap your arms around it all on day one.

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

That’s seven bullets. Makes it sound fairly 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 or missing piece. Keep it all and clearly defined against the database solution you use.

Distribute Data and Intelligence Wisely
Data Warehouse Access Denied!

Banks (along with many other industries) have struggled for years with the best ways to share good information to their front line employees and decision makers. There are endless reporting solutions with fancy dashboards and automated or customizable reports. Many of these solutions offer employees a better view of their customers and prospects than they would have otherwise. However, some key underlying activities can make or break your data distribution strategy and 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? When selecting how you want to report to your front lines, think about the timing of each report relative to their schedules. Is a morning email on prospects the best idea because Training is teaching the first 15 minutes of the day as follow-up time? Or is it the worse time for a prospect report because the branch employees are frantic that time of day getting the branch ready and trying to respond to emails and voicemails? Ask your employees about timing.

Making It Actionable

Data is only as good as it is actionable. You hear this often. But, for some reason, we fail to provide clear actions in the context of the available data. Five employees could look at the same data set differently, so how do you help guide their view of the information? Each report should contain at least 3-5 scenario examples of what to do based on the report. 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 often feels like the most unnatural educational topic on an agenda.

Make sure you can track employee engagement with your data reporting tools. You will have super users, monthly users, and inactive users. Many of the inactive users need help understanding the value of the report and how to use it. The monthly users might only be engaged with reports actively pushed their way. Super users can be your evangelists and assist the Training department. Understand who falls into each of these groups and target your training accordingly.

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