Machine learning in Finance - Present and Future Applications

If you think seeing, hearing and learning is a trait of human beings only, then probably you have not been introduced to the concept of machine learning yet. Computers can also see, hear and learn just like their human counterparts. Machine learning in the simplest terms means that a computer is able to learn automatically from its experiences without being programmed again and again or any kind of human intervention. It has automated jobs that were earlier thought could be done by humans only.
It is wise to work smarter than to work harder. Forward-looking financial service companies have started relying more on machine learning leading to its enhanced use in the finance sector. It has many advantages which have attracted financial institutions to embrace machine learning technology in huge numbers. Mention can be made of:

  1. Improvement in decision making capability
  2. Improvement in customer experience.
  3. Enhanced efficiency in utilization of resources
  4. Automation of tasks

Also Read: Everything You Need To Know About Machine Learning and Deep Learning

Prevention of frauds

Protecting clients from fraudulent activities is one of the major challenges which financial institutions often face. Machine learning goes one step further and provides data security by out-living the brains of criminals. It keeps a sharp eye on every transaction of account, large cash withdrawals, continuous attempts to make a transaction and prompts alerts immediately. Moreover, it can also increase the number of steps to perform an operation in order to delay transaction until a human brain makes a decision. In doubtful cases, the transaction is often declined.
As criminal minds are becoming smarter, computer systems are also being designed in the same manner to tackle them.

Providing Aids in Trading Services

Machine learning has aided investors by making accurate investment predictions. It allows them to place an order when the stock reaches a particular price and sell when drops below a certain limit. Thus, it has eliminated the role of brokers up to some extent.

Managing The Risk

Since machine learning technology can analyze huge chunks of data, it helps in preventing fraud investors from securing loans. It checks the financial status of the applicant and whether he/she holds multiple accounts. These operations simplify the task of investment managers and bankers for whom it was not possible to check such minute details and only covered the static portion of the application.

Assistance in Customer Service

Based on the reviews received from the customer side, machine learning can be used to pre-determine whether a customer is going to continue the services or abandon them. With these valuable insights, it becomes easier to improve the services and satiate the customer as well.


Portfolio Management

Robo- advisors have eradicated the need for a human helper who would give the best-suited advice to the consumer. Users enter their desired goals such as having savings of Rs 6,00,000 when they retire at the age of 60 and robot-advisor presents the whole range of investments the user can make. In the upcoming future, related applications would be considered more reliable.

Enhanced Security

In addition to passwords as the security key, facial recognition and speech recognition could be used to do away with loopholes in security.
Machine learning allows one to analyze huge chunks of data in a few seconds or minutes. On the one hand, it provides faster and accurate results but on the other hand, it also requires additional time and resources to train it effectively. Therefore, the need of the hour is to combine machine learning with artificial intelligence to deliver fruitful results.
Related Article:

  1. 7 Key Skills Required For Machine Learning Jobs
  2. What is The Easiest Way To Learn Machine Learning?

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