AMBER – ABBS Management Business and Entrepreneurship Review

S. Srihari ¹, S. Huxley ², Ajitha Savarimuthu ³

Affiliations
1 ITM Business School, Student, Chennai, Tamil Nadu, IN
2 Visiting faculty, ITM Business School and AVP Indium Software, Chennai, Tamil Nadu, IN
3 Associate Professor, Acharya Bangalore Business School, Bangalore. Karnataka, IN

Abstract

In today’s world, banking sector is crucial to the modern economy. As the primary supplier of credit, it provides money for people to buy cars and homes and for businesses to buy equipment, expand their operations, and meet their payrolls. The credit cards, debit cards, and checking accounts that banks make available facilitate all kinds of everyday transactions. They also help drive e-commerce, where cash is of little use. With banking products becoming increasingly commoditized, Analytics can help banks differentiate themselves and gain a competitive edge. Machine learning forecasting for banking enables more accurate reporting by automating credit risk testing for both banks and customers. By evaluating a consumer’s financial history, recent transactions, and purchasing patterns, machine learning can make accurate forecasts of future spending and income. Predictive analytics helps banks distinguish between the various portfolio risks effectively, by optimizing the collections process. It helps banks segregate risky customers from the risk-free ones. This can help banks devise actions and strategies to achieve positive results. Predictive Analytics is a stream of advanced analytics which uses new as well as historical data to forecast activity, behaviour, and trends to predict the future. This involves data mining, modelling, employing statistical analysis techniques, and automated machine learning algorithms to make the predictions. It helps organizations discover business issues in real time and address them at the right time to get the best outcomes

Keywords

Banking Sector, Modern Economy, Machine Learning Forecasting, Credit Risk, Predictive Analytics, Positive Results, Data Mining, Statistical Analysis

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Ajitha Savarimuthu ¹

Affiliations
1 Associate Professor, Acharya Bangalore B-School, Bangalore, IN

Abstract

One of the most audacious business people of his era was Dhirubhai Ambani. He became more optimistic and intelligent in handling business as he gave himself permission to take more calculated risks in life, which allowed him to grow as a person. Dhirubhai Ambani had to take various chances, such as leaving his nation for employment, quitting his position to launch a business, changing the direction of his company from selling spices to yarn and forging new commercial ventures like petrochemicals. Mr. Dhirubhai Ambani was a remarkable individual who always valued hard effort, creative and problem-solving, which helped him become India’s most successful businessman, a true ‘rags-to-riches’ tale. Anil Ambani, previously one of the richest individuals in the world, has nevertheless has lost $42 billion wealth. Anil Ambani was able to transform himself from the richest man in the last century to the poster child for the phrase “riches to rags” Anil Ambani, once the sixth-richest billionaire in the world with $42 billion in assets, informed a UK court in 2020 that his net worth had fallen to zero and that he became a pauper to Chinese banks. The case enlightens on fail of family business on the second generation due to lack of managerial skills and overconfidence on diversification.

Keywords

Raise, Downfall, Rags to Riches and Riches to Rags

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