In case you’re unfamiliar with the term, “fintech” is a combination of the words “finance” and “technology”. It refers to any tech tools used in the financial industry, such as apps for managing stock portfolios. Data science is an increasingly big part of how fintech operates, and here are the major ways it plays a role in the development of fintech tools.
Financial Planning
Say you want to utilize a financial planner, like Cane Bay Partners, to help you start making smarter choices with your money. It’s very likely that your consultant is going to use data science, particularly when working on your taxes. Tax consultants work with the information they have available to them, so having more information is going to make their job a lot easier. Data science also means that human error is all but eliminated from the process of working on taxes or 401ks. Financial planning can become an exact science thanks to algorithms and data points.
Virtual Advisors
Because investing has become a much more common practice in recent years, it’s becoming more common for people to invest without the help of a financial advisor or risk analysts. However, without that added advice and assistance from an expert to drive your choices, you’ll end up making some avoidable errors. Thanks to data science, AI technology means that there are algorithms that can essentially act as a financial advisor. These “robo-advisors” are driven by data and insights that can result in incredibly well-calculated decisions.
Fraud Detectors
With any kind of financial decision comes a level of risk, and most people are aware of the risk of fraud that comes with banking and fintech operations. The advancement of data science in that industry, however, means that fraud detection is becoming increasingly easy to detect and prevent. Credit card fraud, in particular, is becoming less common, even without having to deal with stacks of paperwork. Data science also allows banks to assess risk more accurately, accumulating and analyzing levels of data that would never be possible otherwise. Financial processes through fintech will only guarantee greater levels of customer satisfaction as data science continues to be utilized.
Customer Retention
Data is incredibly useful for both predicting customer behavior and for taking feedback and utilizing it for future interactions. Fintech means that more and more customers will be utilizing online portals or apps to conduct financial business. This in turn means that more customers are giving up large chunks of data in return for easier banking or investing process. Businesses that are capitalizing on this valuable commodity are guaranteed to learn something useful about their customers.
Data analysts can take what is learned from interactions and turn it into successful marketing campaigns and, eventually, better customer retention. Instead of a depersonalized experience conducted by robots, customers should see positive changes to their financial advising or banking experiences. Data science has the ability to transform businesses and make for a fintech sector that is better attuned to what customers want and how to give it to them.
