Think of a world where you never have to visit a bank, where all the financial services are merely the touch of a button away. The applications of big data in fintech today is advancing at a rapid pace with the financial sector being one of the biggest contenders.
It is now possible to get verifications done through your phone’s fingerprint scanner. There are already algorithms in place which are capable of analyzing your financial history and suggest the best deal for you.
And as we further advance into the big data tech-driven world, banking will turn into a very convenient service.
Roadblock to complete digitalization
While we are progressing at a rapid pace towards a fully digital world, there are a few hurdles that we are yet to conquer for complete use of big data in fintech.
1. Information Gap
There is a lack of reliable info about potential browsers and customers. To determine whether a customer is eligible for certain financial products, these banks would go through his transaction history and comprehensive fiscal record. This led to the disqualification of many small Indian MSMEs and individuals for those particular products.
Those who did qualify faced a long and tedious process of documentation. Since several different types of documents were required and often took weeks of manual processing.
2. Perfect Data Set
As the penetration of smartphone devices increases, banks now have a greater opportunity to get more customers. As powerful machine learning algorithms have evolved, it has become very easy to analyze the data that is collected from various sources to deliver applications that have immense potential.
These algorithms can analyze the digital footprints to create reliable and predictive models that can help derive important about their financial creditworthiness.
With a combination of big data, these Fin Tech companies can now rely on real-time insight to make important decisions, for example, evaluation of loan application. It is also beneficial for customers and they can now rely on its insights to decide which financial products should that
take up.
Enter Big Data in Fintech
Big data has a major role to play in the success of Fintech. Various cognitive touch points under big data like relationship analysis and language comprehension are a few ways in which Fintech is leveraging the power of big data.
One of the sectors that have seen a positive effect from big data is lending and credit scoring. Traditionally, credit scoring was based on basic financial based on all the financial transactions done by an individual in a financial space. But with big data, now aspects like willingness, ability, behavior and many more have been taken into consideration as well. Financial services companies are heavily leveraging big data and slowly making their move to digital channels to acquire more customers.
Analytics solutions are a great way of helping financial firms in offering contextual and personalized engagements, increasing opportunities of cross-selling and upselling.
Looking at the bigger picture, it’s safe to say that big data spells smoother calculations for financial institutions on how to progress further.
3 ways big data in Fintech can revolutionize financial institutions
The financial sector has become one of the biggest consumers of big data recently. This is how big data is changing the financial world-
1. Better actuarial decisions
With the use of big data and predictive analysis, the industry has become much more consolidated and competitive. This has enabled Fin Tech to take on big and consolidated banks. One of the biggest advantages that big data provides Fin Tech companies is predictive analytics. With the use of predictive analysis, brands can now set more accurate borrowing terms, which are financially beneficial to the customer with a low-risk profile. It also helps reduce the risk of dealing with unnecessary risk borrowers without setting appropriate terms.
2. Value to customers
Big data has now become a go-to, in order to offer better value to the customers. The financial sector is no exception.
Many customers have often expressed concerns about companies having access to their data. However, these companies only use the data to better serve them. In a report by Accenture, it was reported that customers were willing to let companies use their data if it helped them while they were seeking loans.
3. Securing Funding
In an economy that is cash-strapped, funding can be an issue. Big data isn’t only important to provide value to the customers. It is also a very useful tool when for Financial Tech firms to expand.
When expanding, Financial Tech organizations are in need of significant capital. And they have faced numerous challenges over the years. After the financial crisis of 2008, many institutions were reluctant to offer financial assistant to startups to grow their operations. Companies need to provide reliant business plans to acquire the capital they need. Big data analytics gives small lenders a great opportunity to showcase their skill to the investors. This, in turn, has helped many brands to secure funds that would not have been available to them otherwise.
Looking for ways to use big data to expand your business? Contact us at Datahut, your big data experts.