Banking On Big Data: Why Banks Need To Explore Their Options Now

Why is Big Data so important for modern banks and the financial services industry in general? Data has always been important for banks - just think about how much data they need to process to manage basic transactions - but what is changing now?

The big difference is that banking used to be a very personal industry. Customers knew their manager and they banked at a physical branch on a local street. This is all very different today. Not only are there many modern banks without any branch network at all, but even those traditional banks with branches have switched their attention to a much more online app-focused banking experience.

I commented on this on Twitter recently with a bank manager who said there was no longer any personal interactions with customers in her bank. I commented that my last experience of a manager personally helping me was a decade ago – and online banks were already around back in 2012.

So what is Big Data and why does it matter for banks, especially in this era of banking that is less focused on human interactions and focused more on bank apps and websites?

Big Data is just a catch-all term to describe a volume of structured and unstructured data in various formats – usually it’s constantly growing. The main properties that distinguish Big Data from data in a regular database are attributes such as volume, velocity, variety, value, and veracity. So, this is data from multiple sources in multiple formats that is growing rapidly and also being updated frequently.

It’s fairly easy to imagine some scenarios where drawing data from across the bank into a format that can be analyzed in real-time would help the business:

• Customer insights: modern banks are helping customers to make more of their money by understanding their spending. For example, a customer can set a limit on how much they spend each month on restaurants or taxis. This kind of insight can also help the bank to offer specific products to customers when they may need them – investment advice for customers with extra cash or a personal loan to avoid overdrafts for example. Data can create insight into how to serve the customer better exactly when the customer needs help or advice.
• Segment customers: banks can group customers into different segments so it becomes easier to manage processes such as marketing. For example, a customer that has consistent trouble with debt is unlikely to want or need advice on crypto trading – it may even be unethical to offer trading options to customers that are in difficulty.
• Risk and fraud: by analyzing customer behavior it is easier to highlight inconsistent spending patterns and therefore potential fraud. Suspect transactions can be highlighted and checked in real-time with customers.
• Loyalty and feedback: banks can also gauge how customers are feeling about service by monitoring social media networks and feedback surveys. Customers often express their views on service and banks can capture this to analyze the sentiment and views of their customers.

Even these four suggestions are just the start of this journey. Any bank that is thinking into the future will want to start considering how data and customer interactions can start being at the heart of all bank processes.

Big data is an essential tool for banks in 2022 – for improving service, efficiency, and getting closer to customers. It cannot be ignored or left for future investment. This is the future of banking right now.

Banking is an industry that has always been filled with data. We have already written about why Big Data in banking is set to explode. Moreover, the COVID-19 coronavirus pandemic has offered data analysts some great opportunities to study Big Data trends across the world. Read more about Big Data in a time of pandemic.