Ways Big Data Creates a Better Customer Experience In Fintech

Big Data provides data that fintech companies can leverage to build customer profiles. Through segmentation, these institutions can easily understand customer wants, needs, and expectations. They can also use this information to analyze consumer behavior and create tailored services.     

Data analytics fintech provides crucial information financial institutions need to build a robust risk assessment strategy. This allows businesses to identify potential risks fast and avoid them or immediately find the appropriate mitigation strategies.  

Fraud is a cause for concern in the banking industry, especially now that mobile banking takes a center stage. However, fintech businesses can use big data and machine learning to build fraud detection systems that uncover anomalies in real time. They will detect illicit activities such as suspicious transactions, logins, and bot activity. 

Start-ups and established fintech companies can use big data to understand the changing financial industry. With access to previous data, these companies can monitor purchasing behavior and predict future trends. As a result, they can make crucial decisions that elevate customer experience, based on these facts. 

Changing consumer preferences and the need to capture market share drove financial institutions to embrace multi-channel service delivery. To ensure their customers have a satisfactory experience, financial businesses will use big data analytics to tweak their services across various platforms to suit a customer’s needs. They will also use historical and real-time data to identify possible customer challenges.    

Data science in fintech has influenced customer experience in more ways than one. Thanks to it, the financial industry can now:

Customer likes and dislikes shift depending on need. Historical financial big data helps businesses scrutinize evolving customer behaviors, allowing them to come up with invaluable products and services that streamline banking processes.   

An excellent example is how the Oversea-Chinese Banking Corporation (OCBC) designed a successful event-based marketing strategy based on the high amounts of historical customer data they collected.

Thanks to big data, Fintech businesses can access real-time data that shows how users interact with their products, the average time spent on the portal/system/app, and the most-used features.

With such information, these businesses can assess two product versions to see which offers a superior UI/UX design. Additionally, they understand in-depth the differences between the products and how they affect the customer experience.

Big data evaluates customer satisfaction rates from survey results. For instance, it helps financial institutions identify the rate of and reasons for customer churn, helping them devise newer ways to keep their audience interested in their services. Also, it has been used in the management of product and feature requests, as well as in analyzing customer support ticket trends.

Financial companies can provide accurate credit ratings based on the number of missed or delayed payments, how much money a customer owes, and how promptly they make payments.

Big data for financial services in conjunction with digital technologies such as machine learning has proved fruitful in the detection of suspicious activities. They prevent various types of sophisticated fraud and elaborate hacking attempts.

Deutsche Bank is one such financial institution that is taking advantage of big data analytics to identify techniques used in money laundering, secure the know-your-customer processes, and prevent credit card theft.

With insights from big data, fintech companies can measure the success of their efforts geared toward providing a positive customer experience. By measuring ROI, they can identify where to improve and what to focus on.   

The Fintech Sector is Exploding Due to Big Data