Over 83% of the global population owns a smartphone. This means that banks and fintech corporations can use enormous amounts of data to enhance customer experience, understand market trends, and make fundamental changes accordingly. Most of the data you find online is shared willingly by users. Hence, using it is legal and can help you modify your business strategies and operations. The fintech market has grown dramatically over the years. People have stopped visiting banks and prefer managing their finances through feature-packed and intuitive fintech applications. Fintech solutions offer innovative financial solutions to customers. This is why they have started drifting away from traditional banking methods and adapting to the fintech culture.
What is Big Data?
Big Data is a massive and high-volume collection of datasets that constantly grow exponentially with time. The data is so massive and complexly arranged that it is nearly impossible to measure and present in numbers. It can't be managed, analyzed, and visualized through traditional data management tools and methods. Only highly skilled data scientists can work with Big Data through complex algorithms.
How Does Big Data Affect the Fintech Industry?
Fintech companies provide borderless financial services with real-time, instantaneous, and secure data transfer. It makes financial interactions between customers and businesses seamless and frictionless. As we mentioned previously, fintech companies use data to improve customer experience.
Hence, the ways through which Big Data helps companies improve customer experience and develop trust:
1. Risk Management
Risk management is an important part of any financial service. Analyzing the risks involved in every business process, operation, and service is important for the success of every fintech business model. Big Data analysis can save business executives from making wrong investment decisions. It also shows what operations, processes, and decisions might be fruitful in the long run based on historical data. Data analysis also helps highlight customers showing signs of trouble on your fintech platform.
2. Fraud Detection
Detecting fraud is an important part of every risk management process. Fintech companies have to ensure that any entity doesn't defraud them. Credit and debit card fraud is one of the most common frauds faced by banking and fintech services. In 2018, such frauds accounted for over $14.7 billion in losses to financial firms globally. Therefore, even the slightest risk of fraud can lead to severe consequences.
Data scientists and engineers can use various AI and ML algorithms to detect and flag potential frauds before they occur. They can also closely analyze customers' behavior and quickly alert company representatives if they detect something unusual, like purchases that don't fit the profile or belong to the mentioned location. Such purchases can be stopped midway and sent for review.
3. Compliance
Technologies like AI and ML can help fintech services track transactions and keep things in order. Analysts can use data-driven methods for analyzing and detecting irregularities in financial transactions and push notifications for immediate response. They can also predict potential anomalies in financial systems and help fintech companies take preventive measures before the issue escalates.
4. Automation
Fintech companies are required to provide their customers with 24/7 assistance to answer the queries of their customers. But, if your financial service has thousands or millions of users, it's impossible to handle everyone's queries personally through a customer support agent. Therefore, many successful fintech services use AI-enhanced chatbots to provide 24/7 interactivity. They can answer basic queries, and if the issue is complex, they can forward the query to an available customer support agent.
Through robotic automation, fintech companies can improve customer experience and interaction by allowing AI-powered bots to handle basic and repetitive tasks without human intervention or input. By doing so, companies are able to reduce errors and assign other complex tasks and queries to their team members.
5. Segmentation
Every successful fintech service offers various features based on the requirements of its target audience. Hence, they perform data-based segmentation to know their customers better and provide them with custom fintech services. Apart from checking credit scores and other variables, segmenting your customers can also help you market your services to the right section of your target audience. You can categorize your customers based on the following parameters,
· Online behavior
· Employment
· Financial history and state
· Family
· Demographics
Segmentation can help you get high-value customers to purchase your financial products.
6. Sentiment and Behavior Analysis
How customers interact online with your fintech service tells a lot about their preferences. This helps business executives make profitable decisions and offer services and features that customers truly require. Customers prefer using fintech services that understand their needs and expectations. Hence, fintech companies can use data-driven methods to know their customers better through sentiment and behavior analysis. You can use the data and insights extracted through these methods to provide customers with personalized offers. By providing custom fintech services, you'll not only improve user experience, but your company's overall credibility and reliability will also improve significantly.
Conclusion
Fintech is one of the next big technological trends, and it'll make financial processes a lot smoother, hassle-free, and frictionless. But, creating fintech apps and software can be difficult, especially if you're running a startup that doesn't have enough funds to begin with. In that case, we recommend outsourcing your app and software development projects to the US’S Best fintech software development company. They have a team of highly skilled fintech experts and developers who develop dependable digital products for some of the most high-profile clients and brands.