Top Big Data Applications in the Fintech Industry

Data is clearly now the most asset for any business in any sector. It is fundamentally changing how businesses operate and strategize. Hence it comes as no surprise to see that businesses are making significant investments in technologies that help convert raw data into actionable intelligence. But to what end, you ask. For starters, intelligence could help them to anticipate market shifts and understand customer preferences in detail. This is especially true in the Fintech sector. And given that security is paramount in this sector, businesses are starting to feel the pressing need for solutions to help them navigate such a market, The ability to effectively collect and interpret this massive amount of data is no longer a luxury. It has now been established as a core competency. Thankfully, a mighty solid solution is found in the form of Big Data.

In this blog, I will walk you through some of the most compelling use cases of big data in the FinTech world. This will help you have more informed discussions with your big data services provider.

What's Big Data Got to Do with FinTech?

Big data brings forth transformative potential for the sector. This potential manifests in several ways, such as more sophisticated risk management and hyper personalization of financial offerings. Oh, and did I mention that increased operational efficiency through automation and much stronger compliance with changing regulations are also among the benefits? What big data really does is provide deeper insights into customer behavior. This is conducive to more targeted marketing and better customer experience. Not only that, but the tech also fortifies cybersecurity and can facilitate the development of new financial solutions when used strategically.

Big Data in FinTech: Top Use Cases You Ought to Know

FinTech is transforming thanks to big data, which enables quicker and more intelligent decision-making.  Real-time analysis of large datasets enables businesses to better manage risk, detect fraud, and customize financial services.  Regulatory compliance, algorithmic trading, credit assessment, and client segmentation are important use cases.  In addition to improving operational effectiveness, these advances give businesses a competitive edge in providing customized solutions.  Let's examine the Big Data applications that are having the biggest impact on contemporary FinTech.

• Enable Insurtech: Big data has much to do with this one. Insurtech needs this tech to modernise traditional insurance practices. Traditionally, insurance companies assessed risk using broad categories such as age and previous claims data. However, big data enables Insurtech companies to collect and analyze granular datasets. This means insurers can create highly personalized risk profiles for individuals and groups. This results in more accurate underwriting. In turn, premiums can be priced more fairly based on actual individual risk rather than broad averages.
• Reduced expenses: Big data brings to FinTech the ability to detect inefficiencies and redundant processes by analyzing massive amounts of operational data. The insights thus gained also helps with streamlined workflows and automation of repetitive tasks. The automation, as you can imagine, reduces the need for manual intervention, thereby lowering human error and associated costs. Improved fraud prevention is also a critical way of cost reduction, of course.
• Enhanced efficiency: Many FinTech services require immediate responses. So big data helps here by processing and analyzing massive amounts of data in real time. This capability enables instant loan approvals, fraud alerts, and so much more. All of it translates into a significant competitive advantage for FinTech companies over traditional financial institutions. Plus, the analysis of system logs, performance metrics, etc., allows FinTech companies to anticipate potential system failures or performance issues.
• Access to a bigger audience base: Big Data enables FinTech companies to serve a much wider range of customers. You see, traditional credit scoring generally relies on a limited financial history, which prevents many individuals and small businesses from obtaining credit. But with big data in their operational arsenals, FinTech companies can include additional data sources such as mobile phone usage and utility bill payments. This results in a more comprehensive and accurate credit risk profile for people with "thin-file" or "no-file" histories. The result? Significantly better access to loans and other critical financial services. 

Final Words

Ready to put big data services to work for your FinTech business? Then I recommend that you start looking for an expert service provider ASAP.