Big Data's Significant Role In Fintech

Data Banking

Fintech covers a range of financial fields such as retail banking, investments, and lending and thanks to the mobile and internet innovations of late is a thriving sector. Offering improvements which drive customer satisfaction and education in an area previously inscrutable and dictated by gigantic inflexible corporations, fintech is helping put the power back in the hands of the individual. A significant component of this technology, Big Data plays a major role in the breakthrough revolutions coming out of the fintech sector, and as data scientists and analysts hone their skills and receive ever-improving quality data, so the consumer profits.

Big Data Uses in Fintech

Included in the revolutions that fintech and Big Data provide are better means of assessing credit scoring. Considering the majority of the world’s population is not scored in credit bureaus, and even when credit bureaus are the primary method of scoring the systems often rely on irrelevant information, it’s a relief to know that newer lenders are focusing on Big Data from sources such as social media to assess credit worthiness. In fact, some institutions believe they can determine an individual’s personality through social media data analysis for higher loan acceptance rates and reduced default rates.

Another noteworthy use of Big Data in fintech is in banking APIs, providing online communication with banking institutions that provide third parties with information about customers. This data sharing is an essential part of many of today’s business processes and offers both businesses and consumers the advantage of necessary information sharing without tiresome form-filling and fact checking that would otherwise be required. And of course, fintech tools are also incredibly useful in financial trading, not only because Big Data aggregation promises a better market understanding, but they’ve made the markets accessible to the layman and provide financial education and advice for a much reduced, if any, cost.

Not All Big Data is Equal

It is necessary, however, to understand that not all Big Data is equal. Today’s data scientists and analysts are looking for smart data that cuts through the mess and white noise and offers real insights and value. Plenty of time and resources could be wasted on the myriad pieces of extraneous data that are continually extracted from social media, wearable tech, IoT applications, and the likes, but employing a quality over quantity data extraction and analysis process drives better fintech innovations that are more reliable and productive. Though we’re still in the early years of smart data, many organizations are responding to the need for quality data and employing new methods for advanced collection.

The Big Risks of Big Data & Regulating Fintech

With the developments in data collection and analysis, we’re also seeing steady improvements around data privacy and security. Considering the vast amounts of sensitive data available it’s no wonder consumers and businesses alike fear data theft, privacy infringements, and information fraud, but top fintech innovators are building protections into their applications which better guard both personal and professional data and its accessibility. Moreover, governance programs are being developed to help organizations properly manage the data they collect, while governments are beginning to put regulations in place to ensure necessary compliance and security.

Fintech regulation, however, is a work in progress as independent territories struggle with the challenges faced by a financial arena which extends across borders. Entire Countries may enact specific regulations to be adhered to by fintech organizations, but this doesn’t necessarily safeguard citizens as fintech evolves into a global industry. Some jurisdictions such as Australia, Singapore, and the U.K. have implemented strategies such as a “regulatory sandbox” framework which allows for limited testing over a restricted time after which existing regulations must be followed, while others are creating fintech councils which help address necessary legislation and compliance.

Today, data is a high-value commodity, and though we’re flooded with it, it isn’t always put to use in the most appropriate and valuable ways. Thanks to shrewd data scientists, quality filtering tools, as well as supple regulatory bodies, Big Data holds much promise and is consistently driving fintech’s worth.

By Jennifer Klostermann

Robots

How DSPs can Improve Straight Through Processing Rate in RPA Implementations by up to 82%

Robotic Process Automation Digital Service Providers (DSPs) today are well placed to take advantage of next-generation technologies like Robotic Process Automation (RPA), Machine Learning, and Artificial Intelligence. As most of the smart DSPs have already ...
Security Cloud

The Problem with Cyberhygiene

Cyberhygiene Dangers It is a quirk of human nature that we have a hard time contemplating abstract notions of danger, especially when it is introduced to us by others. In the simplest of examples, imagine ...
Simplifying and Streamlining Cloud Management with AI

Simplifying and Streamlining Cloud Management with AI

AI Cloud Management Software with artificial intelligence capabilities layered with cloud computing can allow businesses to improve their data management, visualize insights that represent patterns in information, deliver a better customer experience, and optimize their ...
Paperspace

10 Influential Cloud Gaming Platforms of 2021

Cloud Gaming Platforms The cloud gaming niche is becoming popular for the same reasons services like Netlflix, Hulu and YouTube also are: the user only requires access to the internet to enjoy gaming technology and ...
Ronald van Loon

The Future of Work: Confronting One of the Biggest Challenges of the Next Decade

The Future of Work Technologies like artificial intelligence (AI), machine learning (ML), and automation in all of its forms can augment human workers and enable them to pivot to more valuable work, and perform their ...
12 Cybersecurity CEOs On What Each Learned Leading During The Pandemic

12 Cybersecurity CEOs On What Each Learned Leading During The Pandemic

Cybersecurity CEOs’ lessons learned from navigating the pandemic provide a valuable framework for leading and growing a business through anxious, uncertain times. How each cybersecurity CEO responds to the challenges of keeping employees safe, customers ...