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 processes are needed for data exploration, training, model selection, data preprocessing, missing data handling, evaluation, and feature engineering.
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 processes are needed for data exploration, training, model selection, data preprocessing, missing data handling, evaluation, and feature engineering.
Amongst these, the BFSI category contributed the highest revenue to the market in 2019. Financial organizations are using this platform for various applications, such as anti-money laundering, customer churn predictions, credit risk scoring, and efficient fraud detection. Additionally, this platform also assists organizations in providing personalized products and services, which, in turn, leads to higher sales and lower churn rate. Geographically, Europe and North America are expected to contribute the highest revenue to the AutoML market in the coming years.
This will be due to the huge investments being made in Canada, the U.S., the U.K., Germany, and France. Furthermore, technological advancements, well-developed IT infrastructure, and surging use of emerging technologies are also propelling the regional market to new heights. On the other hand, the Asia-Pacific (APAC) region is predicted to register the fastest growth in the market in the forthcoming years, owing to the soaring investments being made in the IT sector, growing adoption of advanced technologies, and increasing implementation of government initiatives aimed at facilitating the faster development of the artificial intelligence (AI) technology in the region.
Thus, the market will exhibit rapid expansion in the coming years, mainly because of the rising requirement for advanced technologies and effective fraud detection solutions among enterprises all over the world.
This will be due to the huge investments being made in Canada, the U.S., the U.K., Germany, and France. Furthermore, technological advancements, well-developed IT infrastructure, and surging use of emerging technologies are also propelling the regional market to new heights. On the other hand, the Asia-Pacific (APAC) region is predicted to register the fastest growth in the market in the forthcoming years, owing to the soaring investments being made in the IT sector, growing adoption of advanced technologies, and increasing implementation of government initiatives aimed at facilitating the faster development of the artificial intelligence (AI) technology in the region.
Thus, the market will exhibit rapid expansion in the coming years, mainly because of the rising requirement for advanced technologies and effective fraud detection solutions among enterprises all over the world.
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