5 Ways Big Data In Fintech Is Creating A Better Consumer Experience

big data help fintech and improve customer service

Positive consumer experience is the most valuable thing critical to any business’s longevity. It assists build a brand reputation, enhances a company’s visibility, and boosts customer loyalty, which translates to expanded incomes. 

Statistics show that 93% of clients will offer repeat companies when they encounter a positive customer experience. For these causes, fintech businesses actively seek opportunities to nurture better customer experiences.

And Big Data is one such fantastic opportunity! 

Big Data is the collection and processing of vast volumes of various data types, which financial organisations use to gain insights into their business operations and make critical company conclusions.

This article focuses on big data in the financial enterprise, its role, and how it allows fintech businesses to protect their clients and improve the customer experience.

The Role Of Big Data In the Fintech Industry

We have seen considerable advancements in the financial industry’s service provision thanks to big data. 

Big data in fintech is crucial in delivering essential content that impacts service delivery. For example, through meaningful data insights, financial institutions can offer personalized services and predict customer behaviour. They can also predict industry trends, assess risks, and make strategic stages to boost the customer experience.

How Big Data Helps Fintech Startups To Better Serve Their Consumers

Fintech analytics helps companies in the financial and banking industry offer good services by:

1. Enhancing Risk Assessment

Data analytics provides crucial information financial organisations need to build a robust risk assessment strategy. This helps companies quickly determine potential threats and avoid them or immediately find the appropriate mitigation strategies.

2. Enhancing Security

Fraud is a cause for concern in the banking industry, particularly now that mobile banking is taking centre stage. Nevertheless, fintech companies can use big data and machine learning to create fraud detection systems that uncover anomalies in real time. They will detect illegal activities such as suspicious transactions, logins, and bot activity.

3. Improving View Of Consumer Profiling

Big Data provides information that fintech businesses can leverage to build customer profiles. These organisations can easily understand customer wishes, needs, and expectations via segmentation. They can also use this data to analyze consumer behaviour and build tailored services.

4. Personalizing Service With Chatbots

Companies in the Fintech industry can harness the power of big data to personalize chatbot client service. AI-powered chatbots will access raw data to respond to client questions accurately and directly to the point.

5. Predicting Future Market Trends

Start-ups and founded fintech businesses can use big data to comprehend the changing financial industry. These companies can monitor purchasing behaviour and forecast future trends with historical data. As a result, they can make essential decisions that elevate customer experience based on these points.

6. Ensuring a Seamless Multi-channel Experience

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.

How Can Big Data In Fintech Influence The Consumer Experience?

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

1. Scam detection

In meeting with digital technologies such as machine learning, big data for financial services has proved fruitful in detecting suspicious activities. However, they contain different types of refined fraud and elaborate hacking attempts.

Deutsche Bank is a financial organisation that benefits big data analytics to determine techniques used in money laundering, secure the know-your-customer processes, and control credit card rip-off.

Learn more about “Why Business Intelligence is Critical In Strategic Business Planning”

2. Analyze consumer behaviour to offer new services

Consumer likes and dislikes shift depending on necessity. Historical financial big data helps companies monitor evolving client behaviours, allowing them to create invaluable products and services that facilitate banking operations.    

An outstanding example is how the Oversea-Chinese Banking Corporation (OCBC) created a successful event-based marketing plan based on the high amounts of historical client data they gathered.

3. Credit ratings

Financial organisations can give correct credit ratings established on the number of skipped or postponed payments, how much money a client owes, and how promptly they make payments.

4. Analyze client satisfaction survey results

Big data considers consumer satisfaction rates from survey results. So, for example, it helps financial organizations identify the rate of and reasons for client churn, allowing them to devise unique ways to keep their audience interested in their products. Also, it has been used in the management of product and feature requests, as well as in analyzing consumer support ticket trends.

5. Better UI/UX using A/B testing

Thanks to big data, Fintech companies can access real-time information demonstrating how users interact with their products, the average time spent on the portal/website/mobile app etc., and the most-used features.

Fintech companies can assess two product versions with such data to see which suggests the best UI/UX design. Also, they comprehend in-depth the differences between the products and how they impact the client experience.

6. Measure the ROR (rate of return) from delivering a better consumer experience

With insights from big data, fintech businesses can estimate the success of their efforts toward delivering a good consumer experience. By measuring ROR (rate of return), they can determine where to enhance and what to concentrate on.


Big data is actually improving and changing the Fintech industry. It helps access big data volumes that could be used to improve a customer’s user experience in retail banking, investments, online trading, and other financial operations. Nevertheless, choosing BI and ETL solutions cannot be over-emphasised to take full benefit of big data’s powerful capabilities.

ETL and BI solutions make dealing with enormous volumes of data accessible. They help system integrations and build reliable data pipelines that provide actionable insights. Also, they assist fintech firms in predicting market trends and driving profitability.

Let’s discuss how we can create the perfect ETL & BI solution for your business. 

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