Increasing core deposits has become a key priority for community financial institutions. While you could, metaphorically, fish with a net or throw darts blindfolded, using advanced analytics is an ideal way to grow your FIs deposits. In this post, we discuss three practical methods for using advanced analytics to efficiently grow deposits.
1. Segmentation is everything: mathematically it may even be more

We’ve all heard about the 80/20 rule. But in many applications, the segment concentrations are even more extreme. Don’t be surprised in looking at data from your core if critical deposit segments fit a 90/10 or 95/5 concentration!

There are two keys to consider when embarking on a member or customer segmentation path. First, consider how you should identify the segments in which the extreme-minority produces the extreme majority. In other words, where should you look to find the 90/10 or 95/5 concentrations?

The second key is in finding the best way to drive action within the groups you identify from the previous paragraph. It’s one thing to identify groups to target and another to act on the information you uncover.

The solution is to have a quantifiable metric to identify and measure change. Specifically, a metric to measure engagement is strongly suggested. Consider asking the following questions to help understand your members’ engagement with your organization:

  • Identify which members clearly have a primary checking relationship with your FI. (In other words, which of your members treat your organization as their primary financial institution?)
  • Which members have a checking account, and make a loan payment from that checking account, but have very few other transactions?
  • For members who account for the vast majority of deposits, what products, transactions, and services do they most frequently utilize?
  • Answers to these questions (and a dozen more!) will reveal many intuitive actions
  • Developing an engagement metric helps to track these segments and measure changes in engagement for the critical segments identified
2. What’s more important than onboarding success?

Repeated statistical analysis reveals that habits are formed in the first several weeks of a relationship with a new FI. That is, the product relationships formed during the onboarding process represent a significant percentage of the entire products and service relationship an individual will have with a FI.

Consider questions such as:

  • How good is our onboarding and cross-selling process? Do we have well-defined goals? Do we achieve success?
  • Do we succeed in deepening the member/customer relationship to include multiple deposit products and loan products, strong utilization of digital services, etc.?
  • How do we measure success? Do we know which branch does the best job? Do we know which branch employee does the best job? What are the methods that lead to their success?

Measuring engagement at the two-day, two-week, and two-month mark should reveal the success of your onboarding process by region, branch, and employee. Generating more deposits is made drastically easier by achieving strong relationships during the onboarding process. Sharing information across the FI with other lines-of-business, coordinating follow-up, and measured actions are key.

Remember: what gets measured gets done!

3. Characteristics of our best deposit generating members

Once we have an operational engagement metric, measured action results, measured onboarding success, and a completed segmentation analysis of our best deposit-generating members, several analytical methods can be applied:

  • Consider a simple geographic cluster analysis to identify where the ideal depositors live. Through purchased or internally-mined lists, reach out through their preferred marketing channels.
  • What are the most frequent product mixes (typically 2-3 different products in a cluster) that occur within your strongest depositors?
  • How quickly can you recognize new members that could be “the best” and take action to help quickly deepen the relationship?

The key to success with growing your deposits lies within your data. Analytics should be empowering your journey and providing insights and key metrics. Consider the various bullet points discussed in this article and don’t discount the power of measuring engagement!

How confident are you that your organization’s analytics initiative is truly delivering real value?

Did you know, more than half of all analytics projects fail because they simply did not deliver the features and benefits that were intended at the onset of the project?

Your analytics project should contribute significantly to loan, deposit, and customer/member growth while also improving risk, retention, and profit. Analytics and even advanced analytics (machine learning based models) are empowering larger financial institutions, while many community-based financial institutions struggle to enjoy significant bottom-line impact.

To accelerate your analytics journey, consider these four topics:

1. Accelerate to Avoid Incremental Learning

Every journey begins with the first step. However, after every long journey or project, there are always things we wished we’d done differently. Advanced analytics, like machine learning, is often hampered by not knowing what we don’t know. Establish the 4 Cs of the process first: Collect, Cleanse, Compute and Consume.

Disparate data sources limit a complete picture of the members’ relationship. Once Collected and Cleansed, low hanging fruit is revealed within these data sources that would empower immediate action for the lines-of-business. The Compute phase should result in meaningful metrics that provide leaders feedback and measure progress. The Consumption layer permits leaders to view trends and identify key segments for action.

Each of the 4Cs has multiple iterations. More granularity is needed for deeper insights. As an example, some FIs have all debit card transactions grouped together into a single transaction code versus having separate PIN vs. POS transaction codes to reveal important insights.

Analytics can be used in identifying several recurring debit card transactions such as gym memberships and utilities. Another example is the integration of internet banking and mobile logins: helpful data in the computation of engagement, retention, and segmentation of digital vs. traditional users. The compute phase is obviously limited when the “right” data elements are not present. Worse, experience shows that the most statistically-predictive components of an advanced analytics equation are synthetic-variables. That is, a calculated metric derived from other data elements. The process to identify these best-elements takes time. Avoiding incremental learning can accelerate your analytics journey 2-3 years!

 

2. Accelerate to Avoid Incremental Learning

For most community FIs, the minority of customers provide the vast majority of many things. Dozens of sorts reveal immediate opportunities, such as:

  • Pinpoint the members that provide the majority of deposits and loans.
  • Determine how many customers have a checking product and use their checking account in a way that demonstrates your institution is clearly their primary FI.
  • Answer key questions like, of those members with a debit card, what percent generate the most transactions. In most cases, less than 20% generate 80% of all transactions.
  • Calculate profit and/or contribution. Many FIs can calculate that the top 1% of consumers typically generate around 100% – 150% of profit. Percentiles 2-15, generate another 150%. Percentiles 16-89 contribute a negative contribution of 80% – 100%.  The bottom 10% (familiar through bankruptcy notices and legal bills) contribute a negative contribution of 100%. The net result remaining is the net profit or contribution.
  • Identify top performing consumers. If we open 100 new relationships today, how long does it take to identify those with the potential to be in the top 1% or top 15%? Can you measure on-boarding success? Can you measure customer experience revealed by an engagement metric?

What gets measured gets done!

 

3.  The Role of Math and Machine Learning

So much talk of analytics and too little math is also a recurring obstacle to avoid. Often, math and machine learning are typically applied with little understanding of product and industry knowledge. Two entertaining illustrations:

  • A client engaged a multi-month machine learning consultancy that informed the Credit Union that the primary share account was their #1 product; nearly everyone has one…obviously!
  • A larger FI client, with Ph.D. mathematicians and statisticians on-staff challenged a complex model equation to minimize risk and loss. The equation did not include “customer account balance” as it had no predictive contribution. The bank staff disagreed as their findings showed that it was the #1 predictive component. The bank staff used the balance after the account was already negative. If the FI charges-off accounts on day 45 as a business rule, there’s a high probability that a negative account on day 44 will be charged-off tomorrow. However, that doesn’t enable a business leader to make an informed decision! Once they adjusted their challenge-equation to consider “customer account balance” 30 to 15 days prior to the account going negative, they agreed that balance was not helpful. This is another example of incremental learning.

The reality is, it takes industry and product knowledge coupled with statistical experience to reveal actionable insights. Dumping data into a neural network model or machine learning tools will have you chasing statistically significant, but likely-irrelevant, findings. Machine learning is best applied to improve or identify a specific segment on an existing equation or model. That is, Machine learning is an evolutionary, not revolutionary, tool.

 

4.  Put Actionable Insights to Work: Measured Action

Being able to collect the right data is one thing, but making it extremely useful and action-oriented requires a different skill and mindset. Contributing an immediate ROI should be your top goal. Initial success should be easily achieved because many opportunities will be revealed through the right concentration and segmentation steps. You can measure success by comparing targeted action against historical baselines. Over time, actions will be targeted on the right individual, at the right time, via the right channel, using the right message. Expected probabilities will be assessed and tested against previous results.

Soon the FI will formulate best practices and metrics through the data and insights. Your segments will become more narrow and refined. The FI’s culture will evolve into a data-driven culture, welcoming team suggestions and recognizing the best performing region, branch and individuals. On-boarding and experience goals measured at two days, two weeks and two months will result in improved retention and member/ customer service. Top performers can be recognized and learning organization theory can lift the performance of others. Over time, the bank’s culture begins to shift, strategic initiatives are measured, resources are provided to team members in the form of information and action lists, and performance can be assessed.

 

Are you ready to accelerate your analytics journey?

Let Coastline Analytics accelerate your journey by two years with our unique approach to establishing your organization’s advanced analytics capabilities.

Contact us today!