Examples of Machine learning in Finance Industry

Have we ever thought about why we get upcoming song suggestions on Spotify based on our interests? All this is happening because of one trending technology called - Machine Learning !!!

There are various sectors who have adopted the usage of Machine learning to get the most advanced outcomes. Retail, healthcare, transportation, finance, logistics and many more industries are those who have already welcomed ML in their business process.

Here in this article we are specially going to talk about the finance industry where to deal with large sets of data and manage them effectively top notch finance companies have built models with Machine Learning.

Let’s have a look at some of the examples of companies who have successfully adopted ML to optimize their business process:

JP Morgan chase and US bank:

We all are known with the giant name JP Morgan Chase which is the leading name who has adopted ML in real sense from the very early stage. They have built a system called contact intelligence system -COiN. Here ML Engineers have used unsupervised ML algorithms to process documentation for loan underwriting.

Machine learning has helped them to design a model which does extraction of more than 150 attributes from yearly business possible in fraction of seconds. Along with that they designed a travel expense management tool to cut off extra costs and reduce time for payment reimbursement process.

S&P Global $ Kensho:

They have used Machine learning to get insightful data of their business to make future decisions. A model developed by Machine learning engineers is called Kensho which gives simple and quick answers to most complex financial questions such as monetary policy changes, political events, economical reports, etc.

Cerebellum Capital:

For the purpose of streamlining investment processes cerebellum a hedge management firm has used ML technology for the smooth adaptation of processes. They have successfully with the help of Machine Learning found a process for taking investment decisions, testing and upcoming trending strategies.

Conclusion:

We have talked about the leading finance companies who have successfully adopted Machine Learning in their daily operations. Thus here we can say that today is the time when all the businesses can easily get in touch with Machine Learning Development companies to get customized models. Nowadays you can outsource ML engineers with a flexible hiring model and get most advanced solutions.