As customers begin to use more online banking services, their expectations have increased and changed. In years past, customers were happy with basic online account management that let them view details for existing accounts.

Now, customers want to have the ability to send money to a variety of accounts, access credit card rewards, and customize their account settings from anywhere. They look for a bank that has the features they need and the customer service they deserve, especially as they travel and spend online in more ways than before.

As big data in digital banking gets smarter and faster, banks are brainstorming more ways to market their services and help their customers make better financial choices. Banks can increase new sign-ups and customer retention by investing in engaging, relevant features that take advantage of the wealth of data available on consumers.


What Are the Benefits of Digital Banking?

Customers have a wide range of needs depending on the services they’re accessing, their lifestyles, and the technology available to them. Digital banking reduces in-person staffing and customer service costs and gives customers easier access to payment systems.

The added convenience of digital banking makes it easier for customers to pay their bills on-time whenever they remember, instead of dealing with paper forms or phone calls. This can reduce late payments and fees, boosting customer satisfaction and trust.


1. Reducing Fraud

Customers trust that banks will protect their accounts, and banks can improve and advertise their security efforts to attract and retain customers. In recent years, big data has become a key part of modern fraud detection algorithms. By using machine learning to teach AI programs about customer trends scraped from big data, banks can detect and flag transactions that are unusual and likely to be fraudulent.

Customers don’t like dealing with false alarms, so banks have to get the financial services analytics company to keep false positives to a minimum. When customers feel their account information is securely protected, they are less likely to close credit cards or take other actions to reduce their reliance on a bank.

2. Customer Shopping Habits

The link between consumers’ habits and their banking needs is a critical example of the relationship between digital banking and big data. Groceries, gas, bills, and other expenses reveal even more about a customer’s life than their general demographic features.

Many banks already track customer sales data and use that to provide better recommendations for financial services. However, big data can supplement this information and provide more insight into what customers buy using cash or competitors’ credit cards.

With data analytics in financial services, there is huge potential for customized marketing campaigns based on customer shopping habits.

Individuals with high income and more discretionary spending can be sent emails advertising a prestigious credit card, while individuals who aren’t using their cards often can be sent emails with special offers encouraging them to use their cards more.


3. Solutions for Every Location and Device

Even tech-savvy customers who predominantly use mobile apps and websites will occasionally need in-person services. Currency exchange services, ATMs, and other cash needs must be relatively nearby for a customer to continue using a particular bank as their primary provider.

Big data strategies for financial services can inform company decisions about where to build brick-and-mortar locations. If a majority of customers live in the suburbs but work and shop in the city, then banks may find that small downtown locations are just as valuable as suburban ones.

Big data can also provide insights on the types of devices customers own and which devices they use to access mobile services and websites. By investigating which devices customers are and aren’t using to access services, banks can discover which versions of their apps are worth investing more in.


4. Better Credit Card Rewards

Credit card points and rewards have been a part of banking services for years, but they are still not used as frequently as they could be, even as online shopping and mobile app usage have become more popular. Smarter digital banking with big data must include tangible perks for customers to increase perceived and actual value of services.

Banks can also use big data to tweak their cash back percentages and other reward criteria to meet the needs of their target demographic. For example, young urban professionals without cars won’t benefit from bonus points on gas purchases, so banks need to offer a different perk to attract that demographic.

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5. Predicting Customer Questions

The use of data analytics in banking can provide insights as to what services customers will need next, which can also predict the questions they have. Banks can use cutting-edge data mining to predict questions customers are likely to have and even point them toward relevant written FAQ pages while customers are using the service.

By predicting customers’ questions and addressing them in advance, banks can reduce the amount of resources they spend providing phone- and chat-based customer service. It can also improve customer satisfaction by sharply reducing or eliminating the amount of time customers spend waiting for help.

6. Mortgage Marketing

Young people tend to put off buying their first home until after age 35, but this trend can still vary based on economic factors. Big data can inform financial institutions of which customers are actually searching for homes, regardless of age and other factors.

Since customers don’t want to receive too many marketing emails or in-app notifications for offers, it makes sense for banks to use big data to only show services likely to be of interest to a particular customer. However, existing customers may turn to another lender for their mortgage needs unless they have a trusting relationship with their current bank and have a reason to believe that their current bank provides the best service and value.

This requires proactive and carefully-tailored marketing that advertises the best rates and loan options to customers whose big data suggests they are ready. Marketing can be tailored even further to educate first-time homebuyers, who may have lower financial literacy or knowledge of mortgages simply because they haven’t experienced the process yet.


7. Smarter and Forward-Thinking Digital Banking

Getting the most out of big data requires a multi-faceted approach and a complex data analytics system. All sizes and types of financial institutions have unique needs, and data science experts can provide customized solutions that incorporate data safely and securely.

Syntelli Solutions is a leader in modern big data, AI, and predictive analytics for financial services and other industries. We have a track record of success with small and large clients alike, with projects ranging from basic open source migration to in-depth reworking of CRM systems. Contact us today to learn more about our team and services.





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