Machine Learning is the ability of computer systems to learn and adapt according to situations without any additional programming by human beings. It is a form of Artificial Intelligence where a system can analyze a set of data and generate results according to their experiences from past events. The main purpose of this invention was to give the machines the ability to do the thinking and deducing solutions to problems without any human intervention.
The information generated from the analysis of data is more accurate and can help in predicting future outcomes of decisions made by human beings for example creation of future work plans in industrial production for reducing expenses. Machine learning as technology has many applications. Human beings use it to perform various tasks. It has taken over various sectors like healthcare, retail, and manufacturing.
Out of all the sectors, Finance is relatively a new area and has improved a lot due to the adoption of machine learning.
Machine Learning in the financial industry can be used for various purposes which are listed below:
1. Financial consultation:
Machine learning helps customers and financial institutions in taking various financial decisions. The automated system helps clients in managing their financial portfolios. They use a statistical system of identifying the best financial instrument which the client should invest in for greater profits. The investment process becomes easy and more efficient.
2. Financial Trading:
Machine Learning even helps a trader by making the investment process automatic. A trader can invest in various shares and financial instruments using the automatic software which trades on the behalf of the trader. Traders who invest in small quantities can give instructions to the program related to the time, type and amount of investment. The software, in turn, invests in the securities and adapts itself with past experiences.
3. Fraud detection:
Financial fraud is one of the serious concerns of the financial industry. Machine Learning can help in combating the problem as it can detect fraud by scanning a large set of data and can even inform the financial institutions regarding any unusual activity on time. The AI-based technology can automatically detect the identity of the person committing the fraud which makes it easier to nab the culprit.
4. Useful for the fulfillment of loan applications
Banks can use the technology in order to quickly identify the identity, credit score and previous financial track record in order to complete the process of fulfillment of loan applications.
5. Useful for insurance companies:
Machine Learning can also be used by insurance companies as the software can go through a mountain of data in order to complete the loan application of an individual. Moreover, the identity of an individual, information regarding financial transactions and medical history can be quickly verified using AI-based technology. The completion of the process is possible with fewer errors and within the limited time frame.
6. Predicting future financial outcomes:
Banks and financial institutions are mainly affected by policy changes and other events that can have an impact of their working. AI-based technology can predict such situations and notify the industrial leaders on time for taking appropriate action. Critical events can be predicted easily based upon past events by the system working on the principles of Machine Learning.
Therefore, Machine Learning in the financial sector is reshaping the entire economy. Banks, financial institutions and even customers can benefit from the adoption of the technology.
