FinTech is a particularly "heated" issue in the world of finance, where big data is being used., FinTech, or financial technology, refers to technical innovation in the financial industry and might include technology applications in retail banking, financial literacy, online trading, peer-to-peer lending, and other sectors.
What makes Big Data “BIG”?
The concept of gathering data to improve consumer experiences isn't new. From small-town greengrocers to big-city bankers, bits of data have long been used to build a better image of their clients. The “BIG” in big data, on the other hand, offers firms with a treasure trove of consumer information that has the potential to turn the financial world on its head.
Watch this video to understand: What is Big Data?
The value of big data will increase as the Internet of Things (IoT), mobile technology advances, and improved authentication mechanisms become available.
As a result, fintech firms will continue to spend heavily in data science departments in order to focus on data collection and processing. So, formerly underbanked and underserved audiences now have access to new financing opportunities.
Big data has three distinct V Characteristics:
Volume – Traditional technologies are incapable of processing the massive amounts of data that a big data platform must handle.
Velocity - Data must be processed in real-time, which is a necessity for the majority of enterprises.
Variety - A strong big data platform should be able to handle a variety of data formats, including unstructured data such as audio, tweets, status updates, and videos.
( Also Read: Big Data Applications in Daily Life )
What is Big Data In Fintech?
Big data in finance refers to the petabytes of structured and unstructured data that may be utilized by banks and financial organizations to predict consumer behavior and develop strategies.
The financial sector creates a large amount of data. Structured data is information that is maintained within a company to give crucial decision-making insights. Unstructured data is accumulating from a variety of sources in ever-increasing numbers, providing considerable analytical potential.
(Also Read: What is Financial Analysis )
Emerging fintech is using big data to forecast client behavior and generate sophisticated risk evaluations, setting them apart from traditional financial institutions. Disruptive fintech and challenger banks can react to a changing market thanks to the speed of real-time data.
They may flip to aggressive methods at any time, leaving the major banks struggling to stay up. Big banks are like strong diesel-powered tanks, whereas data-driven fintech is like electric scooters that can leap over potholes and take sharp turns.
Fintechs can make better judgments and provide more personalized consumer experiences thanks to their capacity to handle big data volumes. Fintechs may utilize big data to understand their consumers on a one-to-one basis, rather than guessing or covering their backs with cautious risk assessments.
Benefits of Big Data in Fintech Industry
Emerging Fintechs can benefit from big data analysis in four ways:
Fintechs may utilize big data to develop thorough user profiles and precise client segmentation strategies, allowing them to customize their services to their specific demands. Individualized services may be provided using sophisticated modeling approaches that take into account an individual's risk perception, age, gender, money, location, and even relationship status.
While fraud is a prevalent problem in the digital banking sector, big data may assist fintech in developing accurate fraud detection systems by detecting any odd transactions. Fintechs may also use digital applications to keep consumers informed about security concerns and secure their money.
Improved Risk Assessments
Fintech businesses that specialize in big data analytics may integrate data from a variety of sources to guarantee that no stone is left unturned. Fintechs can operate with more financial certainty, manage cash flow, and give consumers competitive rates thanks to improved risk assessments. The way banks think about risk is changing as a result of predictive analytics.
( Also Read: Predictive Analytics - Techniques and Applications )
Unmatched Customer Service
Forget about dialing numbers and waiting hours to talk with an account manager. Fintechs may use big data to establish a digital trail of a customer's financial behavior, spot possible problems, and give consistent assistance.
Fintechs may also use data and forecasts to propose the correct services/products depending on their clients' specific spending habits.
Chatbots, Bots, and Robotic Process Automation
Chatbots use artificial intelligence to enable interaction 24 hours a day, 7 days a week. These intelligent Chatbots may assist consumers in a number of ways, including handling transactions, providing vital information, and handling transactions.
RPA improves the user experience by allowing bots to undertake repetitive (and labor-intensive) tasks without the need for human interaction. It not only reduces mistakes but also frees up team members to deal with more complicated issues and deliver better customer support.
( Also Read: Robotic Process Automation )
Use of Big Data in FinTech to develop strategies
Importance of Big Data in FinTech Industry
Big data is in high demand in finance for a variety of reasons:
Lack of Personal Connection with the customers.
Users expect to be able to address their problems without having to go to a bank office, but this makes gathering information on clients more difficult. Mobile gadgets can be of assistance.
They let companies gather many sorts of information, such as geolocation, the most common user interactions, user behavior, and browsing history. This information may then be utilized to make up for a lack of face-to-face connection with clients.
FinTech's social media footprint is growing.
Users make purchases and engage with companies using social media, which is no longer only a platform for connecting with friends and family. Examining user behavior on social media is critical for FinTech firms to gain insights and apply them when selling products or services. Insurers, for example, may create unique plans based on social media data, and banks can use social media data to create credit scores.
( Also Read: Applications of AI in Finance )
Expectations of customers are shifting.
Customers want businesses to not just meet their requirements, but also to anticipate and surpass them. This is impossible without consumer information. To provide tailored offers for clients, a FinTech company should collect data from numerous channels such as their mobile app, website, wearables, social media, and smart devices.
The client experience has altered as a result of online banking. You no longer need to visit physical sites or wait days for transactions to be completed. Fintechs have developed cross-border financial services that enable real-time data sharing. It allows buyers and sellers to conduct business without friction.
Fintech has driven conventional players to adapt by allowing for more personalized alternatives in financial services. Fintech firms may be more nimble and respond rapidly to changing market conditions since they are founded on contemporary technological platforms.
FinTech is becoming increasingly competitive.
The FinTech sector is quickly expanding, attracting an increasing number of entrepreneurs, startups, and established businesses every day. The ability of a FinTech product to deliver a service is critical to its success in this competitive industry.
Big data enables businesses to optimize their operations in real-time and provide their customers with the finest services possible based on hard facts.
Reduced operating expenses allow firms to dedicate resources to marketing and decrease pricing for customers, allowing them to stay ahead of the competition. As a result, FinTech companies must automate their operations in order to save money, and big data insights can assist.
( Also Read: Importance of Data Science in Finance )
Watch This video on Big Data and Analytics in Finance:
The fintech sector is quickly changing. All financial institutions' client experiences and expectations have altered as a result. Customers may now have a more personalized and tailored experience thanks to artificial intelligence, machine learning, and big data.
Customer experience has evolved into a differentiator and a primary driver of customer expectations. Fintech has been able to steal consumers away from traditional financial institutions as a result of this.
One of the reasons for the growing acceptance of fintech businesses and non-traditional financial institutions, according to industry analysts, is the better client experience.