The global automated machine learning (AutoML) market reached a value of $269.6 million in 2019, and it is predicted to generate a revenue of $14,511.9 million by 2030, exhibiting a CAGR of 43.7% from 2020 to 2030 (forecast period). The burgeoning requirement for efficient fraud detection solutions, personalized product recommendations, and growing significance of predictive lead scoring are the major growth drivers of the market. With the increasing internet penetration, the incidence of fraudulent activities is soaring, thereby fueling the requirement for fraud detection and prevention solutions. According to the World Bank, around 57.0% people all over the world had access to the internet in 2019. Moreover, several organizations are adopting conventional machine learning methods and big data for detecting and preventing fraud. However, the dataset tends to be highly skewed and imbalanced in terms of negative and positive classes. Thus, in order to obtain accurate results, several pr...