Applications of AI and Machine Learning in Banking Solutions

With the advent of recent advancement in technology, banking sector has entered into a new era of innovation. Big data and cloud computing has changed the face of business and banking solutions. The new technologies have opened diversified endeavors for the aspirants in the field of banking sector. Globally, approximately 59 Zettabytes of data is expected to be generated in the year 2020. Out of which major chunk of data comes from the banking sector wherein customer information, transactions, online purchasing, selling, etc. is being stored and analyzed. With this enormous data in banking sector; data processing, storing, analyzing has become a herculean task. Lately, Artificial Intelligence and Machine Learning have been recognized as the most beneficial in providing banking solutions by enabling decision making capabilities to provide competitive advantage. The recent development and enhancement in computational intelligence has catered to the rising demands of banking industry in various areas like customer retention, fraud detection, loan calculations, insurance, risk management, etc. The online markets and online platform has largely contributed to the databases of banking sector by enriching them with lots and lots of data. The data needs to be preprocessed and stored to maintain its quality for data analysis and processing. The data must provide improved and quick services to deal with the competitive market scenarios. In this paper, various banking sector applications have been explored where Artificial Intelligence, Machine Learning and Big Data Analytics are used for various banking solutions. The paper discusses and categorized various AI, ML and BDA models on the basis of business analytics methods.