Internet of Things and Machine Learning Banking Business Model Using Neuro Fuzzy Technique

Traditional banking methodology is changing due to the Internet of Things (IoT) and Machine Learning (ML). The Internet of Things and Machine Learning has given birth to the thought process of smart home and smart city. Bank must come up with respective changes in its working, analysis and services phenomenon to meet the smart customer needs. This article aims towards the implementation and utilizations of the IoT and ML business model in the banking ecosystem with a neuro-fuzzy tool. The business model addresses security, digital marketing, strategies to reach to offline customers, advisory board, quality assurance, product analysis and hiring or outsourcing external services in a collaborative manner. Banks have to redesign the business model with respect to meet the opportunities of IoT and ML. With the help of ML, the bank finds new ways of pre-approved lending with its products and earns profits. IoT and ML will suggest those customers who can be offered any banking product. These kinds of offerings will open new sources of income for banks and its sister concerns. Also, it will help in bad debt reduction. The ML model is fed with 957 random data and the model is performing well with an accuracy level of 73.5% on the platform of python.