Applications of Machine Learning in Finance Sector

Applications of Machine Learning in Finance Sector

Machine learning in Insurance sector

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Machine Learning is a model which gives successful and correct answers to problems based on past experiences. The ML model is widely used in almost every sector. Its versatility, and ability to read huge amounts of data makes a powerful tool for companies that want to excel in their business. Artificial intelligence allows machine learning to give better decisions, that always better than the success rate of humans.

How the model is created?

A machine learning model is a simple computer program that has its logic. This logic is developed by giving some prior knowledge about the system. The model also gets data points as inputs. The model learns from these inputs and creates a pattern for success using the initial data. As more data is fed, the more accurate its results get. This is one of the main reasons that machine learning is widely used in the finance sector. The finance system has been around for many years. Banks that were established in the early 20th century still serve customers today. As a result, the amount of data that they have is huge.

The process of creating an ML model is long. The computing power of the system must also be high, which reduces the training time of the system. So a powerful computer would take less time to analyze all the data that it has.

Here are certain applications of Machine learning in the Financial Sector-

Loan application – The model can be used to filter out applicants that can cause fraud or loss to the institution. The model, by reading the customer’s profile can guess with a certain probability that he/she will default their loan. The model also takes the person’s financial history into account, using which it can tell whether the loan should be approved or not.

Fraud Detection-

Machine learning in Insurance sector can be used to detect frauds such as identity theft and forged documents. The model can successfully predict whether the signatures are correct, or whether the person is using a false identity.

Risk management-

Allows companies to assess the risks in the steps they take and the investments they make. Using forecasting technique, the model can predict to some extent whether the market will go up or down. The model also helps companies recognize current market trends, which the company should pursue.

Digital Assistance-

Machine learning based chatbots are quite common these days. These digital assistants reply in real time, giving customers initial help towards the problem they are facing. Such chatbots can be used anywhere- in a website, or even at a shopping mall.

Not only in Finance But Machine learning in e-commerce industry also has many applications. The e-commerce companies use the model to get guaranteed leads and achieve a good conversion rate. Many e-commerce giants already use their own models of ML to successfully predict what their customers would want. With all the existing data, the model can also successfully predict the customer’s choice.

 

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