Prediction of Client Term Deposit Subscription Using Machine Learning

The majority of the banking industry’s income is often derived from long-term deposits which are subscribed by the clients. Understanding clients’ behaviour and attributes is crucial for banks for their growth in sales. To help with this, marketing tactics are used to target new clients producing a lot of information about client traits and other important features. In recent years, it has been found that a variety of data analysis techniques can be used to analyse the customer’s traits along with the factors that have a big impact on consumers’ decisions to subscribe to term deposits. Bank deposits are among the important challenges faced by a financial institution. It can be challenging to anticipate a customer's likelihood of becoming a depositor by analysing associated data. According to current estimates, the finance and business sector has suffered as a result of the crisis economic and the economy's ongoing collapse. As a result, banks are struggling to attract consumers because of the economic crisis. Marketing is regarded as a practical tool. The banking sector is trying to get customers to consider term deposits. Recognizing the objective of the company. The main aim is to predict a term deposit subscription by a customer according to the history data analysis of the client’s behaviour. The data has been explored thoroughly and then a model in been built using ML Algorithms to predict the desired subscription. The algorithms are being compared, and the best accuracy given by the algorithm has been proposed as the best for prediction.