While we are surrounded by tremendous amounts of data, both structured and unstructured, not all companies have caught up to the brave new world around them. However, 59.5% of those who have seized the opportunity and implemented a Big Data project report that this allowed them to reduce expenses. Furthermore, 79.8% of them state that the project resulted in better decision making and/or advanced analytics.
So, how can Big Data serve the financial services and banking industry? Let’s find out.
What Drives Entrepreneurs and Bankers to Implement Big Data in Financial Services?
The banking industry’s revenues in the global Big Data and analytics market amounted to 13.6% of its total revenues in 2018. This makes the industry the leader in the market. Why?
In banking, Big Data is already there. Financial services providers are already collecting tons of data and metadata about their clients (how much they get, when and how much they withdraw, what they buy, etc.). The only difference is whether they mine it to gain benefits from it. Obviously, benefits is the main drive here.
As for the perks of Big Data in financial services, they depend on the specific use case. But to give you an overview of potential benefits, they include (but are not limited to):
- Decreasing expenses;
- Improving employees’ productivity;
- Discovering hidden insights (both into your clients and your organization);
- Powering automation;
- Decreasing human error risks;
- Detecting potential fraud, and more.
4 Big Data Use Cases in Banking & Financial Services
The full potential of Big Data is yet to be seen. However, we can already see what the technology is capable of thanks to Big Data use cases in banking and financial services. Below, you can take a look at four of them.
Obviously, information about your customers is the most valuable data out there, and Big Data solutions can mine it to create more precise customer profiles. These profiles can provide you with insights into your customers’ individual behavior and general behavioral patterns for a certain segment.
Understanding your customers using Big Data comes with two more perks. First, you can understand how they make decisions to impact the process and sell more efficiently. Second, you can even detect when a customer is about to leave to prevent this from happening.
Thanks to Big Data banking organizations can also benefit from foreseeing what your customer wants to acquire next based on their previous behavior. Based on the prediction, your app/website can automatically offer the desired product/service. Overall, this improves the upselling and cross-selling efficiency as customers are more likely to give in to your offer.
Once you segment your customers into categories based on the profiles, the possibilities for your organization are almost boundless. For instance, Big Data will help you reveal segments that are usually underserved. You’ll also be able to design marketing messages that are more optimized and resonate with the segment stronger.
Apart from this, Big Data insights into card usage and transactions can help you design personalized loyalty programs. If you see that the customer often buys groceries in one chain of supermarkets, you can offer him/her cash back in that chain.
Business Process Automation
Sometimes, Big Data is seen as an analytical tool only: you ‘feed’ the data to it and get charts, tables, and insights. Whereas Big Data is capable of that, it’s not limited only by such use cases. In fact, it can power your solutions and automatically determine what they do next, just like with that example of upselling and predictive analytics.
With Big Data, finance can benefit from solutions that perform certain tasks based on the collected and processed data on the internal organization level. For instance, it can be the case for customer onboarding and know-your-customer tasks, as well as risk assessment. The perks are obvious: little to no human involvement means lower human error risks and reduced costs, combined with higher productivity.
Employee Performance & Management
Once you relieve your employees from some of the mundane tasks (thanks to automation), they’ll have more time to perform the duties that can’t be automated yet. Thus, Big Data can do miracles for their productivity.
You can also apply Big Data analytics to your employees’ behavior to gain insights into when they are not productive and why. Using the results, you can optimize the environment and eliminate distracting factors or other obstacles.
Of course, the Big Data opportunities don’t stop here. The technology can also power better fraud detection based on individual behavioral patterns, for instance. So, are you ready to unlock the potential of Big Data?