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Importance of Data Science and AI in Banking and Finance Industry



Importance of Data Science and AI in Banking and Finance Industry

Image by Gerd Altmann from Pixabay

The banking and finance industry are some of the prominent sectors that use innovative tech and data science and Artificial intelligence extensively.

Do you remember when we had used your cheque book or paper form at the bank branch for financial transactions?. We don’t think it is used by the majority of people nowadays. The major percentage of people prefer transactions in digital form that saves their time from visiting the bank branches physically. Banking facilities such as ATMs, mobile applications are more in trend for using the banking facilities by people or organizations.

Consumers prefer the digital functionalities of the banks that are mostly based on data science and AI (artificial intelligence). It makes it convenient both for the institutions as well as the customers which saves a lot of time and money at both ends.

In this article, we will look at the importance of data science and AI in banking and financial institutions. Therefore there is a huge demand for data scientists and AI development that enables the banking ecosystem to run smoothly.

Role of data science and AI in banking:

The financial sector uses the most cutting-edge technology to serve its customers. The important role of the above-stated technology in banking is explained through the following points.

1. Open banking

An application interface is used for financial transactions on apps like PayPal, banking applications, credit or debit card payments, etc for sharing the data. The inclusion of API lets third-party users to cater several features that are not possible with a single mobile app. Using the API with third-party applications following the legal rules and regulation of the law of the land ensures making productivity both for the customers and the third-party applications.

Data science is the tech that carefully analyzes the data and arranges is the most appropriate order for maximum efficiency. The summary generated by data science detailed invention helps in better decision making and increasing the profit margins.

2. Mobile banking

The advent of the unfortunate disease covid-19 around the world brought whole strata of misery among the people. Later who declared covid-19 as pandemic and most parts of the world came to halt. When most of the cities are under strict lockdown all our banking needs are served by mobile banking and its applications.

The majority of banking and financial institutions offer mobile banking or online banking for serving their customers without their actual visit by themselves. Mobile banking caters to exclusive features of the banks that can only be served by the banks through their smartphone app or website. Facilities such as instant bank account opening, expenditure analysis, pre-approved loan facilities, etc are some of the quintessential features offered by the mobile banking services to the customers.

3. Sales

There is still human invention needed to perform sales and performance but with the inclusion of AI and machine learning, we have seen a significant rise in sales of banking as well as financial services. Banking on artificial intelligence with Machine learning provides deep insights of customers that massively improves the sales number. It correctly predicts the customer purchasing interests, improves communication, predicts facilities, etc that aids in the growth of overall sales. With the intelligent analysis of data, bonkers know the right person and time to target and convert an aspired customer into an engaged one.

Related: Python for Data Science

4. IT operations

The main work of machine learning and AI is to log files and system analysis which ultimately filter out the errors found after careful analysis. The functions that are used repeatedly during the banking operations and require less human inversion are automated with the help of AI and data science innovative tech solutions. It also does a complete routine scan of the system in a periodic manner so that future errors can be terminated and system downtime can be reduced. The level of workload managed by the financial institutions can only be operated well by an efficient tech of machine learning and AI innovations.

5. Low cost of maintenance

Reducing the cost of operations in the banking sector is one of the important goals of the sector. The cost of input for human resources is quite expensive to be taken care of. Therefore to solve this problem contemporary tech is included in performing repetitive banking operations. Whereas the human resource is utilized for performing more challenging and dynamic operations. Therefore the use of AI and machine learning saves a significant amount of money for these institutions that are utilized in expanding the businesses.

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