Using Big Data to Cater to Millennials in Banking

How to Capitalize on Revenue When Targeting Millennials

Mike OrtmannAugust 7, 2017

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The banking industry has been going through an evolution in recent years, capitalizing on big data to garner predictive insights in order to open new markets and vastly improve the customer experience to reduce churn and upsell existing clients. However, the banking industry is nowhere near finishing its transformation and is now looking towards growing profitability by catering to the needs and wants of millennials.

According to, “all banks are aware of the importance of catering to the needs of the millennial generation. This tech-savvy cohort is set to dictate the direction the banking industry will take over the coming years and decades.” So, what exactly are the banking needs of millennials?

Catering Banking Needs to Millennials 

While there are two main services that are vital for millennials when it comes to banking, success will be derived by understanding and predicting the most optimum methods that attack and engage them. First, millennials not only want, but expect, a complete omni-channel experience with no limitations or boundaries. They want to access their bank account from anywhere at any time. They want it available on their phones, tablets, and computers. They want to be able to make transfers and pay bills on the go. They need their banking to cater to their busy lifestyle.

To go along with their busy lifestyle, they also want help managing their money because managing money on a daily basis can be quite time consuming. states “as far as millennials are concerned, it has been claimed that members of this generation are not interested in micro-managing their money on a day-to-day basis. Millennials could be more likely to rely on their bank for support and advice when they come to address real-life problems and challenges, such as managing cash flow, saving and budgeting.”

However, in order for banks to deliver the customer experience millennials expect, they will need to ensure the real-time quality of their data. When a millennial makes an online deposit, it should reflect on their mobile app immediately. When a millennial makes a withdrawal at an ATM it should reflect on their online portal right away. When a millennial receives budgeting advice from a bank, it needs to actually fit within their budget.

Without quality data, millennials may experience a wide variety of issues. Those issues can include late payments, misstated financial statements, or bad money management advice, leading to dissatisfied customers, customer churn, and ultimately loss of revenue. So how should banks ensure the quality of their data?

Big Data Quality 

Confidence in predictive analytics on big data is being burdened and undermined by an age old problem – poor quality data. Lost confidence in using unfiltered and unchecked big data leads to flawed decisions that blur the goal of growing market share and revenue with innovative insights. Big data quality requires a different approach and a solution that spans both relational databases and data lakes is paramount to success in delivering quality data. Whether that data be for financial transactions that must be 100% accurate or for predictive analytics it’s imperative that checks and balances are in place.

The solution should help banks ensure all of their systems are in sync. It should ensure that a transaction passes from one process point to another within a specific time period, ensuring that all customers banking information stays up to date across all channels.

To learn more about ensuring data quality, download this eBook.

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