Financial institutions have more data on their customers than any other industry. Yet, this strategic asset is often inaccessible and underutilized due to legacy technologies and silos in your IT environment.
Most bankers know that this is a problem but are not sure where to get started to fix it. We frequently hear bankers say: “We know our data is valuable, but it’s all over the place and we can’t see it or use it effectively”. This leaves financial institutions with several data problems and no solution. Other industries are further ahead in leveraging their data while financial institutions lag behind because of their complicated relationship with legacy technology.
“We know our data is valuable, but…”
“How can I get access to all my customer data?”
“How can I use it to build better relationships?”
“Can customer data tell me what they need?”
“Can it help your bankers know what to do each day?”
We want to explore the 8 main data problems community institutions face, the reason behind them, and the best way to solve them. Financial institutions need to take control of their data problem because solving it is no longer optional. If the last few years have shown us anything, it’s that agility and leveraging data is more important than ever before.
The 8 Data Problems
1. Data exists in independent silos
Core vendors are known to say their systems are integrated, but it’s often just at the “logo” level, meaning it’s only integrated by brand name. Likely, your financial institution stores data across many systems that contain detailed customer, account, and transaction data. In addition to having silos from the same vendor, you can also have silos across systems like core, digital banking, loan origination, payments, trust, insurance, investments, and more. And with new fintech solutions appearing every day, the problem continues to grow.
Financial institutions can have dozens of silos of customer data. This makes it hard to see all your data work together and prevents you from creating a complete picture from of your customers. Bankers get frustrated by this because the information is there, they just can’t get to it.
When all these independent sources don’t connect, you can’t see what you need to know about your customers or your business. Even worse, your most valuable customers are often those with the most complicated relationships. That’s why the data residing in different sources must be combined to provide users a single set of verified information. This ensures everyone has a unified view of the data.
2. Data is dirty
Financial marketers know they need quality data to run efficient campaigns, but they can’t always get to it. This leads to only a partial view of customers and what they really want. Community institutions are often focused on personal relationships with customers, but without the data, it gets harder and harder to deepen those relationships.
Any data keyed by human beings is subject to data entry errors, and core technology isn’t good at detecting or preventing these errors. It is common for users to unknowingly enter duplicate customer information in CIFs. With 40% of this manual data entry being erroneous, plus over 25% of data in the core/CIF already erroneous, it’s clear that data quality issues are costing your institution time and money.
Think about the way you enter an address on most modern websites – all you have to do is type a few letters and a verified address appears. Your core technology may not know how to do this; therefore, it won’t know if someone has misspelled or entered the wrong data.
According to the Financial Brand Digital Banking Report, 60% of surveyed financial institution executives believe the quality of data used by their marketing and business intelligence teams is either unacceptable (22%) or acceptable but requires significant additional support (38%). Only 13% said the quality of their data is acceptable and 4% believed it to be excellent.
3. Data changes all the time
Customers’ information changes as their life changes. They move, change their names, get new phone numbers, and change their email addresses. Most won’t remember to alert their financial institution of this new information, so customer data quickly and consistently loses its value. With a 3-4% rate of decay each month, your data problem is a moving target.
4. Lack of data access
The dated and complicated reporting tools you already have are not helping you get access. Even when core vendors create a warehouse for you, they put complex tools on top of it that still limit your access. These tools are often limited to IT staff because they are too difficult to use. This creates a complicated environment where users regularly can’t get access to the data they need. This leads to a backlog of requests for IT – and you might not get access to the information you need for months!
5. Spreadsheets don’t show you the big picture
It’s nearly impossible to maintain a consistent view across the entire financial institution if there are tons of spreadsheets managed by multiple employees who calculate and define the metrics differently. By the time a report has been formatted on a spreadsheet and distributed, the data is already out of date by the time everyone can see it. Then different reports have different answers for the same questions! How can everyone be on the same page?
6. You can’t see the forest for the trees
You’ve probably heard the saying, “you can’t see the forest for the trees.” Because you’re in the middle of the trees, you can’t see what the whole forest looks like. When you finally get detailed reports from IT, they don’t actually help you understand the big picture because of all the detail. This again leaves you without the information you need to make better decisions. If you can’t access your data, you can’t take action. Bankers can’t see the metrics that they can influence directly, so they don’t know where to start.
7. You can’t do your own analysis
Sometimes you really do need to see the trees in order to understand a business problem and answer your own questions. You need to be able to do that without resorting to those complex tools you don’t have access to anyway. Often only a few people that are trained to use complex query tools can see and use your data – where does that leave the rest of your team? Users shouldn’t have to rely on IT to do their digging for them or start the strenuous process all over again if something isn’t included on a report.
8. New data is created when you connect with customers
Customer data doesn’t just exist in your transactional systems. Every time you connect with your customers with emails, phone calls, mail, and personal visits, you create additional data points that are vital to understanding your customers. How did a customer react to an email? What did they do next?
How do I solve these data problems?
No matter how bad your data dilemma may seem now, there are ways to solve these problems. You need all your data in one place, and you need access to it and make it actionable. Here’s how:
Step 1: Integrate Your Data
Data integration is like an automated factory – raw materials come into the front end and a finished product goes out the back. Automated data integration takes raw customer data from across your silos and turns it into makes fresh, clean data available each and every day. The finished product is understandable, usable data that the whole organization can see.
This is much easier to say than it is to do. It takes specialized technology and knowledge that are not available to most community institutions.
The raw data must be cleansed and standardized to make is useful. This includes cleansing address data to USPS standards, adding geocodes (latitude, longitude, census tract, etc.), and translating codes into business descriptions.
One of the most difficult problems to solve is that there are different representations of a customer in your source systems. Your users often enter customer data in different way within the same system and across different systems. This leads to duplicate representations of the same individual or business.
“Are John E. Smith and John Smith Jr in your CIF the same person?
Are they the same person as John Edward Smith in your trust or investment system?”
To see a “360-degree view” of a customer, you must be able to “resolve” these different identities to know whether this is 1, 2, or 3 people. This lets you connect their other data (accounts, services, and transactions) into the single view that is so vital to understanding your customers. Without solving this problem, you are left with partial views of the customer that can lead to awkward conversations and communications.
Many financial institutions rely on their IT departments to pull data from multiple systems into one source, but they don’t always have the time, tools, or resources to effectively integrate their financial institution’s data. That’s why you need a partner to help you integrate your data.
Step 2: Add Insight To Your Data
While integrated data is the first step, it still may not be enough to answer many business questions.
“How can I segment my customers?
Is this account profitable?
What is our attrition rate?
How many debit card transactions did this customer make?
What customers use 3rd party fintech solutions?”
You need to be able to create many new and valuable data elements that are not in the source systems using complex business logic. You also need to be able to enhance your knowledge of your customers by using 3rd party data. This makes is much easier for user to see answers to their questions without spending their time creating their own formulas in spreadsheets.
Step 3: Make Your Data Accessible
Once data is integrated, you now need to address how you will access it. This starts with the understanding that there are multiple types and needs for data access. This should be driven by your institution’s business objectives.
For example, if you are like most institutions, you need to know how your customers are using digital services like mobile banking. A metric like “percentage of customers with mobile banking” is a great way to measure where you are. Scorecards are a natural fit for this.
A scorecard is a management system that translates your strategic objectives into a specific set of performance metrics and goals. A scorecard makes it easy to understand multiple important metrics at a glance. They help you quickly understand 12 KPIs at once instead of pouring through 40 reports .
It provides timely and relevant information to measure, monitor, and manage progress. They show employees their role in affecting positive outcomes and expectations about how they can affect the measures.
Scorecards can also be used to:
- Monitor performance
- Motivate staff
- Provide accountability
- Communicate strategy
- Focus users on the most important aspects of their jobs
Scorecards are made up of key performance indicators (KPIs) that show progress toward goals. KPIs are the key metrics that help define and measure progress toward business objectives. They are metrics tied to targets that focus users on their most important tasks. There’s no purpose in measuring if users can’t change the outcome.
However, there’s always the need to drill-down from KPIs like this to get more detail. Is the KPI getting better or worse? How does that differ across markets? Dashboards are the best means to allow users to see more information without burying them in the details.
While a scorecard shows you the very highest level of that data and includes KPIs to put it in specific, bite-size pieces, a dashboard gives you the ability to see in much more detail by drilling down or drilling to specific topics. It’s not easy to comprehend all your data at once, so dashboards help you see different pieces of data by business topics. Scorecards show you where you are right now, dashboards show you the specifics. Ultimately, dashboards show a vignette of your institution’s performance. They show you what needs to be improved upon and what is working.
Finally, some users need the ability to analyze specific problems. For example, a marketing analyst needs the ability to explore the data to create their own dashboards and reports.
For further analysis, users should be able to “slice and dice” data to answer their questions without having to go to IT. Data analytics gives answers to your questions. For example, if you had had a sudden drop in deposits last quarter you need the ability to quickly look at your data to figure out why, instead of waiting for IT or sifting through multiple spreadsheets.
Scorecards, dashboards and analytics benefit every department because everyone will finally be able to access and use the data. You simply can’t get a clear idea of the variety and depth of data you have in a spreadsheet.
Step 4: Predict Customer Behavior
You have a tremendous amount of data on your customers and the data integration process adds even more. Each customer can have hundreds of data elements that can help you understand behavior. While you need to be able to visualize this information, it is very difficult for a person to use the multiple facets of customer data to predict behavior.
Will this customer respond to a marketing offer? What products and services do they need? Are they likely to close their account? Large financial institutions have solved these problems using predictive models that ingest the data and predict an outcome. This approach requires expensive software and dedicated data scientists.
“Machine Learning” is a newer approach to predict behavior that can use more data and produce more accurate results without expensive software and human resources.
To put Machine Learning to use, you must be able to apply it every day to answer these questions. Since the data integration process must be automated like a factory, all the data is readily available to Machine Learning models to create the predictions. In essence, the prediction just becomes another piece of the data that can be used in dashboards, marketing campaigns, and customer interactions.
Step 5: Make Your Data Actionable
Integrating and access your data is a major step forward, but how do you make that actionable? Scorecards and dashboards let you see trends and patterns, but you need to able to leverage what you learn to change the way you interact with your customers.
Modern marketing strategies must have access to the same data to create better customer experiences and drive campaign results. Without it, campaigns are poorly targeted and send the wrong message to the wrong customers.
With integrated data and recommended products from Machine Learning, marketing programs can deliver personalized messages to your customers that show them you know about their needs. This leads to better ROI and more satisfied customers.
Your front-line staff can also benefit from knowing more about their customers. The 360-degree view of a customer is vital to every conversation they have. This needs to be powered by the same data used in scorecards and dashboards. Your front-line needs to know all the products and services a customer has before they can have intelligent conversations.
Closing the Loop
Whether you send an email, a letter, make a call or have a face-to-face visit, customer interactions create new data about your customers. Most of this information will not be available in your normal IT environment, so it is important to consider how this information will be integrated with your other customer data.
Did this marketing campaign produce results? How does onboarding affect retention? If your marketing and sales data is in a different place than your other customer data, these questions can be impossible to answer.
Solve Your Data Issues and Leverage Your Data
It’s time to solve your data problem once and for all – take control of your data by integrating, making it accessible and actionable.
Financial institutions need help –luckily you don’t have to do it all alone. Find a partner to help solve your data problem. Just don’t be one of the many that keep falling behind. The need to be agile with data will only increase.
Ready to take control of your data problem once and for all?
FI Works is here to help. Not only do we provide sophisticated software, we understand banking data. We are here to help community and regional community 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.