Follow Us











Startup Sectors

Women in tech







Art & Culture

Travel & Leisure

Curtain Raiser

Wine and Food


This is a user generated content for MyStory, a YourStory initiative to enable its community to contribute and have their voices heard. The views and writings here reflect that of the author and not of YourStory.

AI's role in aiding the Finance Industry

AI's role in aiding the Finance Industry

Monday February 11, 2019,

4 min Read

Lets take a brief look at the journey of AI through the Financial Industry and whether or not its incorporation has proved to be beneficial.

As intelligence is believed to be a gift by nature. The ethical argument continues about whether the human intelligence is to be replicated or not, technological advancement in Artificial Intelligence, a rather complex but seamlessly interesting domain – has proved to be a rising factor among a number of industries, and Finance is one of them. AI started taking over the the Finance industry in the form of waves which only grew larger and ended up turning into tides, the AI Technology used now a days includes providing value-based business strategies, improving customer experiences, increasing revenue generation reduction of costs.

One interesting point that we can take from AI is that since it is an emerging entity known for its factor of success for many industries, the finance industry has thus also followed the footsteps others took and aimed towards increasing revenues and achieving business goals through it. From providing value-based business strategies, improved customer experiences, increased revenue generation and reduced costs, AI has been establishing itself as a significant technological advancement to achieving business success. 

But the secret behind this resurgence of AI is the Availability of Big Data.

The machine learning algorithms, more specifically, the deep learning algorithms, required enormous amount of data. Back when Artificial Intelligence was in its early stages there was a lot of data just lying around but there was not really any much use of it since the technology and infrastructure were not yet present to make any use of it. For example, lets take a supervised Neural Network with about 50 input attributes and 1 output perceptron and with three hidden layers containing 50 perceptrons each of which consits of 10,050 connections, now this network may require a hundred thousand or even more labelled data points for training since each connections weight would be needed to be optimized. To our luck, inexpensive and easily available hardware and network connectivity has allowed humans to produce more than 8 quadrillion Gigabytes of data by 2017. Many of the researchers and developers now a days have started using the freely available data to create databases that are known as "Open Databases" that are used for specific problems and have started crowd sourcing for labelling this data. The first of its kind of database was known as MNIST that was created in 1998 and since then, the largest database that has ever yet been created is ImageNet, one that was created in 2011. It is estimated that ImageNet contains of more than 14 million URLs from images, out of which more than about 10 million of them are hand-labeled for representation.

Through this achievement, the view of the top-level management towards AI is now shifting as people have witnessed its power that has been used to assess business areas poised to substantially benefit with the use of advanced analytics and have deployed it to produce the desired outcomes.

The biggest cut of AI's use goes to none other than Automation. As we all know, AI has gained a strong foothold in the organizations journey of achieving business success. But there are some important things to note that achieving this business success is not a so-easy-task, it does comes with a bucket load of ups and downs, the problem with the Finance industry is that it is a very volatile industry, the system handling it is expected to be robust and efficient, handling of data has to be done very carefully and that is where AI comes in to save the day, AI provides all of the important insights such as automation of results, robustness, astounding speed and accuracy in providing results, everything -- you name it. This is where many of the organizations realised how much they're missing on and how much more they could do with its power in their hands.

Some of the wide spread uses of AI in Finance are in the following sectors:

Stock Trading

Regulatory Intelligence

Financial Planning Services



Lending and Loan Management

Financial Security

Customer Service

Sales and Financial Products

Hedge Funds

The most important factor of achieving business success for an organization is to rely on smart growth strategies. If interested, you can take a detailed look at how the use of AI in Finance can help turn traditional businesses into a stand out enterprise.