The financial industry has been hugely impacted by technology in the past few years. In fact, an entire legion of Quants has been formed who use programming techniques and quantitative analysis to find and exploit opportunities in capital markets.
While FinTech is still highly regulated, the industry is full of small startup companies trying to disrupt the space using the latest technologies, data science, and more. One example is Cane Bay Partners. While this is true, you must learn more about the impact of data science on the FinTech industry, which is described below.
Credit Risk Scoring
Your credit score is a statistical analysis that predicts your creditworthiness. It’s based on your past credit performance and details. A lender uses the value to determine if you should receive a loan from their establishment. Usually, banks will implement complex statistical methods to figure out a person’s credit score. However, thanks to data science, more advanced techniques are now available, including machine learning algorithms, which provide more accurate estimates thanks to the larger number of data points considered.
With data science, lenders receive a holistic view of someone’s creditworthiness. That’s because all data is considered. Because Cane Bay Cares, the experts can provide more insight and information about the technology used when determining your credit rating.
Fraud Detection and Prevention
Each year, fraud cases cost the financial industry more than $80 billion. Individuals and institutions see the potential repercussions of fraudulent transactions. Because of this, fraud detection is considered a top priority for most executives in the FinTech space.
Right now, fraud detection is based on specific rules, like flags that are triggered because of the IP address, ATM, or location of a transaction. However, the entire process can be improved rather than relying on a finite number of transactions. Thanks to data science, it is possible to determine how probably a transaction is fraudulent based on certain patterns in the existing available data.
This type of technology improves overall accuracy and can be used with live data. It also means that FinTech companies are equipped to take action when needed and more effectively.
Asset Management and Portfolio Optimization
Asset management and portfolio optimization are key elements handled by various FinTech institutions. Thanks to the increase in the use of big data, institutions can now analyze all types of financial data, allowing them to create asset management models based on various machine learning principles rather than relying on the old-fashioned, low-tech statistical models. This has also resulted in the availability of Robo-advisors. With these, the software is used to help with the automation of asset allocation decisions, helping to reduce risk while improving returns and offering other benefits.
As you can see, data science has a huge impact on the FinTech industry. Understanding what these benefits are and how it is used will help you see the important role it plays. Being informed and knowing the impact of data science can help you better understand the significant role it has in this industry.