Why Data Analytics Should Be in Your Strategic Plan

FIs are leaning more and more on their ability to use data to keep a closer eye on leading indicators of growth, profit, and risk. Your ability to gain access to all your data may mean the difference between taking advantage of changing conditions or them taking advantage of you. As we found out with the pandemic (and previous crisis), having the right tools in hand matters.

How can you identify patterns and trends so you can get ahead of the curve?

Many FIs are creating strategic plans that include data analytics. This article outlines some of the major things to think about when you are creating your plan.

Data is becoming more important every year and it is the key to driving so many things. Here are a few questions that we hear FIs talking about:

• How can I use data to create better customer experiences to retain and grow relationships?
• What 3rd party FinTech services are getting between my customers and my bank?
• Which customers are adopting my new FinTech services and which aren’t?
• Who is using cryptocurrency services? What are their distinguishing characteristics?
• What products and services do my customers need?
• What are they likely to buy?
• Who are we talking to, and more importantly who aren’t we talking to?
• What checking accounts are likely to close?
• How can we leverage transaction data to know who needs business services (payments, treasury, etc.)?
• Since it is hard to find the right human resources, how can a use data when I don’t have a data scientist?

The Data Dilemma

The traditional problems with accessing and using data are getting worse as FIs adopt and offer more FinTech services to their customers. Each new service adds new data points that can help you understand customer behavior. Yet they are often in new siloed systems that add to the data dilemma.

There is an increasing number of vendors in the market that target financial institutions with solutions that claim to help you wrangle your data problems. You need to be aware that they may only solve part of your dilemma. This makes it more difficult to know what to include in your strategic plan.

This article outlines some things that you should consider when planning for data analytics.

Step 1: Understand the Nature of the Problem

Many of you have probably experienced frustration when you try to get answers to basic business questions. You may hear things like:

• We don’t have that data
• That isn’t in the same system
• We don’t have the tools need to analyze the data
• We’ll put that in the IT project list

This happens because FIs have dozens of silos of customer data. It makes it hard to see all your data work together and prevents you from creating a complete picture of your customers. It is frustrating because you know that the information is there, they just can’t get to it.

Step 2: Document What You Need and How You’ll Use It

While this sound simple, it is often the hardest part of planning. Think about all the questions that you can’t answer today and write them down. Then think about how you want to use those answers. What business processes to you want to enable with the new information?

Here’s an example:

What I Need: Transaction information to better understand the digital banking services that my customers use

How Will I Use It: Target customers that use a 3rd party digital service to offer them ours

It is also important to understand what is common across your stated needs. This helps you prioritize what data you need first. It is important to recognize that this is not a one-time process. As your needs and technology evolve, you will need to add new data to answer your questions.

Step 3: Find the Sources of the Data You Need

Core systems contain a lot of data from customer information to accounts to transactions. If everything that you need is in your core, the problem is easier to solve. However, with today’s technology environment, this is rarely the case.

Compare your list of needs to your applications. Where does the data live? How often is it updated? When think about the data that lives in your applications, you will likely think of new things that you can do with it.

Here are some examples of non-core data sources to consider:

• Digital banking (online, mobile, bill pay) activity data
• Payments
• Loan origination
• Trust
• Investments
• Insurance
• CRM
• Marketing

Step 4: Plan for Integration

Data is messy. It can be incorrect and inconsistent, affecting the way your institution makes decisions. This is often due to manual data entry, which leaves a lot of room for erroneous or duplicate information. Data is also a moving target – people change their addresses, phone numbers, marry, divorce and so on, and they often forget to tell their bank.

Data integration is the most unglamorous and most important part of a data analytics strategy. If you cannot integrate the data sources you identified in step 3, you will not be able to find the answers to your business questions!

CRM, marketing, and dashboarding applications often include some level of data integration. However, these systems do not typically designed to provide the data or the tools needed to answer your most difficult questions.

Step 5: Make Data Accessible

Having clean, integrated data in one place is a major step in your analytics journey. The next step is to plan for how you will access that data. Use your list of business needs identified in step 2 to think about who needs access and how that access should work.

• How will you share information with your staff on a day-to-day basis?
• Who needs access to the data?
• Are you comfortable with static, vendor-supplied dashboards?
• Do you need to be able to create your own dashboards and reports?
• Do you need to analyze data yourself?
• Who will do that?
• Do you need help?
• Do you need to predict customer behavior?

Having the right access and the right tools are key to having success in the world of data analytics. Often, when people think of data analytics, they mean dashboards and reports. While these are important, you will need more to reach your goals.

Step 6: Make it Actionable

There’s nothing quite like having ready access to the information that you need to make more informed decisions but the ability to make that data actionable by automating business processes is even better. For example, it’s great to know which customers are likely to buy specific products and services but it is even better if you can automatically reach out to those customers with marketing offers.

Think about how you will deliver ROI with data analytics. Consider the processes that you want to drive with data. What problems can you solve that generate measurable results?

Step 7: Look for Solutions

The data analytics market is busy and there are many solutions that fall under that banner. These range from general-purpose analytics tools (business intelligence, predictive analytics, etc.) with no knowledge of FI data to solutions built specifically for FIs.

• Consider the full cost (software and implementation) of general-purpose data analytics tools (Tableau, Power BI). Solving the data dilemma with these tools can be very expensive.
• Beware of data warehouse solutions. They may solve part of the data dilemma, but ROI is difficult to achieve without applications that use the data.
• Dashboards can be great tools, but they are not the full answer. How can you get answers to new questions if there is no dashboard for that?
• Look for solutions that include data analytics and other applications that can use it. It is best if you can solve the most problems with the fewest number of systems.

Rise of the Customer Data Platform

Simply put, a Customer Data Platform (CDP) is software that consolidates and integrates customer data from many sources to create a single view of a customer to power data analytics, marketing, and CRM. Some CDPs (like FI Works) include analytics, marketing automation, and CRM applications to provide a complete solution.

To many in the financial industry, this just sounds like another new buzz word. However, CDPs have become very popular with large FIs and large companies in other industries. CDPs are purpose built to solve the problems outlined in this article.

Ready See How a CDP Can Meet Your Data Analytics Needs?

FI Works is here to help. Not only do we provide sophisticated software, we understand banking data. We are here to help financial institutions use data to better serve your customers. Our team are a group who are passionate about your success and ready to make you successful.