Big Data in the Financial Services Sector

July 27, 2020

Financial Services

Big data is a blanket term used to describe the innovative technologies used for the collection, organisation, and analysis of structured and unstructured data. Big data technology allows users to work on complex information to generate meaningful conclusions and findings. Big data is known for its veracity, velocity, and value.

The financial services sector is an intensive data-driven industry that manages enormous volumes of sensitive data. The entire finance sector calls for intensive data analytics for the benefit of customers and the financial services providers It helps the financial service providers to exploit the rich data sets they have collected over the years and deliver compelling use cases.


Impact on the Financial Services Sector

The impact of big data on the financial service domain is promising. Data is the most critical asset of financial organisations and they have found ways to leverage this data. Studies have shown that 71% of banking and financial market firms that use information and big data analytics have a competitive advantage against their peers. It affects the way consumers access their finances, investments, payments, and other aspects served by financial service providers.

The primary financial services include big data include banks, credit unions, credit card companies, insurance companies and Fintech companies. Big data affects the way these providers detect the most suitable products for their customers based on their usage and history and develop new products to meet evolving demands. The customers get the most appropriate products, while the financial service providers do not waste a lot of time, money, and effort to reach the required conclusions. A win-win for both!


What is Driving the Change?

The changes in the increased use of big data stem from a variety of factors. The increase in customer expectations is a critical factor. The customers’ interaction with their financial service providers is becoming more digital. Customers expect top-quality customer services, better and personalised products, and round-the-clock services, leading to companies leveraging the user data through big data technologies.

With the rapid increase in the use of Internet of Things, advanced authentication techniques, and open architecture, access to a large volume of input data is used to generate meaningful and valuable output. Many banks and Fintech companies are using big data to offer exceptional data-driven services, including online transactions, digital investment advice and banking applications. Big data provides fierce competition to financial institutions and forcing them to adopt new big data technologies.

Financial service providers are required to use big data to meet regulatory requirements. The government regulations force financial institutions to provide detailed data to the regulators, making them rely more on big data. Another critical factor driving the transition towards big data is the need for security. Customers expect their banks and financial institutions to keep their data safe and secure and prevent cyber-security threats and other frauds.


Use Cases

There are several uses of big data in the financial industry. Most significantly, big data is used for risk management. Big data helps analyse customer behaviour and provide deep insights. It assesses the risks of identity frauds, card frauds, and insurance frauds and reacts to them instantaneously. The big data technologies monitor customer behaviour and identify fraudulent transactions as soon as they stray away from the customers’ pattern.

Big data is also used in credit risk and liquidity risk management. The analysis of data provides insights on cash flow to manage the liquidity more efficiently, while the data regarding customers transaction history, payments history, public information, and IoT data helps to manage credit risk for the lending organisations.


Benefits and Challenges of Big Data

The implementation of big data technologies in the financial services sector, undoubtedly, holds numerous benefits for both the customers and the financial service providers. The providers practise more focused and personalised marketing, customer servicing, and customer cultivation. They manage risks better with faster identification and assessment. The customer receives a targeted and more efficient experience and innovative products such as home and car insurance in combination with IoT, personalised wealth management services, personal financial management, and algorithmic trading. Big data helps the financial service providers in improving their business efficiency which reduces the operational costs.

Big data technologies come with challenges. The time and money burdens associated with big data are substantial. The massive unstructured data used in big data technologies is hard to interpret and time-consuming. The current technology is inadequate to process the high volumes of high-velocity data. Maintaining the security of big data and meeting the tenacious regulatory requirements poses several other challenges to the use of big data by the financial service providers.