Financial is one of the fastest-growing fields there is. Fintech is the use of computers and state-of-the-art technology to assist in banking and finance. Fintech is used in many areas such as fundraising, non-profits, education, retail banking, and investment management. Its use helps to improve and streamline the delivery of financial services to consumers. Despite some regulatory problems, fintech is growing and includes applications such as lending apps, investment apps, peer-to-peer apps, payment apps, and roboadvisors. A major part of the operation of fintech is the use of data science.
Data Science
The method used to collect and study massive amounts of structured and unstructured data is called data science. In today’s technology-driven world, the amount of data in use continues to increase at an incredible level. From 2019 to 2021, the volume of data on the internet nearly doubled, going from 41 trillion gigabytes to 74 trillion. That number is projected to hit 181 trillion by 2025.
Data science is useful in many different fields that require the monitoring of large amounts of information. Fintech entrepreneurs such as David Johnson Cane Bay Partners rely heavily on this branch of science in their day-to-day work.
Data Science Used in Fintech
Modern technology continues to evolve and develop at a fast rate and fintech collects more and more data from sources such as balance sheets, income statements, and numerous other financial documents Known as Big Data, all of this information requires thorough analysis to be useful. This is where data science comes in using these principles called the three Vs:
- Variety – Data technologies have to process many different kinds of data such audio, video, social media posts, and raw numbers.
- Volume – The amounts of data involved in fintech are so large that traditional methods cannot possibly process them efficiently. The special techniques of data science are necessary.
- Velocity – The speed with which data is processed is vital. In order for information to be up-to-date processing must occur in real-time.
Using the three Vs, data science allows fintech to keep up with all of its information processing requirements.
Benefits of Data Science for Fintech
Using the methods of data science to handle big data, has many benefits for fintech. Some of these are:
- Improving safety and security
- Improving service quality
- Making a faster and more informed decision
- Making experiences better for the customer
- Meeting the expectations of customers
Data science uses special algorithms to perform the incredible tasks of processing mountains of information. This is useful for risk analysis, fraud prevention, customer behavior analysis, and predictive analytics. It can also be used to improve marketing campaigns, allocate credit, and streamline interactions with customers in both sales and support roles.
The world of finance has always involved big numbers in terms of monetary values. As computers and the internet became commonplace, the amount of data needing to be collected and processed has increased astronomically. For fintech to do this incredible job requires specialized methods. This is the job of data science.
