There have been very few technological innovations that have impacted the finance industry, like Big Data. The traditional days of customers visiting local banks have been replaced with a wide range of diverse online products, as well as some use of in-branch services.

The banking industry experienced a significant transformation with the emerging digital changes. Abundant data sources are now available to financial businesses, enabling companies to gain a better understanding of their customers and create a more personalised service.
As more structured and unstructured data is generated by customers through loan applications, credit limits or online transactions, Big Data analytical tools are being utilised to create clear actionable insights. As an example, the Bank of America was one financial organisation that applied social media data to determine service issues with their customers that impact overall customer retention. When the bank used big data to assess thousands of comments on social media, they discovered lots of misinformation regarding purchase limits which potentially impacted their customer attraction and retention. Being capable of discovering customer issues quickly before they grow further is a powerful tool that big data technology can provide.

Businesses in the finance industry use several big data technologies such as artificial intelligence, machine learning and natural language processing. In a continuously increasing competitive market, businesses need to integrate innovative technology to gain a more competitive edge. A survey by Capgemini suggested that over 60% of financial businesses believe that Big Data analytics provides a significant competitive advantage and over 90% believe that successful big data measures will determine the leaders of the future.

The restrictions implemented from the pandemic have placed more emphasis on the digital services offered and available to their customers. While the transition to digital is nothing new, the impacts of the last year have accelerated this movement to new and innovative services. As physical branches reduced their hours or temporarily closed, many financial services have moved online. Without the support of big data tools, banks have become overwhelmed by the high volume of new applications and enquiries. Customers that experience delays or waiting times could potentially move to an alternative bank that offers better customer service.

Banks need to remain focused on assessing all factors before offering credit to a customer or approving a loan. Using relevant customer data with big data technologies improves this process and enhances overall risk management. The more data credit risk management solutions available, the more accurate the credit scoring will be.

The transition and rise of digital have brought a higher incidence of fraud as many face-to-face transactions have been replaced with online services. HSBC uses machine learning and AI to explore potential fraud in various ways by checking IP addresses and monitoring irregular transactions. But customer service remains the top priority for deploying big data technologies. During the pandemic, the bank experienced a significant rise in customer enquiries, and chatbots became vital communication tools. Using Natural Language Processing technology, chatbots can convert text and connect it to established patterns to deliver relevant answers. The text is fed through machine learning tools to determine concerns or challenges faced by their customers.

Standard Chartered Bank uses big data to gain more insights into customer behaviour and target them with specialised services and deals. With real-time data and analytics, valuable information is generated from regular transactions.

As the Economist declared a few years ago, the world’s most valuable resource is no longer oil but data. There is a definitive need for financial businesses to embrace the benefits of big data moving forward. The global market for big data analytics is forecast to increase by an annual rate of over 22% until 2026. Financial businesses are more aware of the necessity of integrated big data tools into certain areas of their business. Big data tools are continuing to influence the financial landscape and support customers issues, increase retention rates and reveal specific insights about customer behaviour.