Machine Learning in Banking Market Expected to Reach $21.27 Billion by 2031

According to a new report published by Allied Market Research, titled, “Machine Learning in Banking Market," The machine learning in banking market size was valued at $1.33 billion in 2021, and is estimated to reach $21.27 billion by 2031, growing at a CAGR of 32.2% from 2022 to 2031.

In recent years, machine learning has been adopted by various banks for strategic decision making, customer insights, and understanding consumer purchasing behavior, and improving the digital transaction experience. For instance, in 2019, Government of India announced the rapid digitalization of the banking sector as part of the Digital India initiative that is expected to stimulate financial inclusion. RBI further promoted its policy of Secure and Informed Digital Banking. Moreover, Allied Digital Services Ltd., a publicly-traded global IT solutions, services, and master systems integration company, officially announced the launch of its new FinTech product  FinoAllied, which is an ML-powered conversational banking platform, that comes with built-in banking services and transactions fully ready to be offered to the customers through various digital channels of the banks. Allied Digital sources claim that FinoAllied could be helpful for small and mid-size banks that are struggling in their digital transformation.

On the basis of application, the credit scoring segment dominated the market in 2021. This is attributed to the fact that machine learning in financial industry can expand a lender’s customer base to cover the so-called credit invisible people with thin or no credit histories and those whose credit scores are not accurate reflections of their risk. Therefore, these are the major growth factors for the machine learning in banking market for credit scoring.

Region wise, North America attained the highest growth in 2021. This is owing to growing pressure in managing risk along with increasing governance and regulatory requirements to improve personalized banking and to provide better customer service. In addition, rapid digitization in financial firms all across the region and adoption of machine learning among banks to monitor data for unusual transactions to detect and prevent fraudulent activities and to keep end users accounts secure drive the machine learning in banking market growth.   

The COVID-19 pandemic had resulted in a positive impact on the machine learning in banking sector since most of the banks and other financial institutions readily adopted technology during the pandemic. Machine learning was one of the most widely adopted technology by banks worldwide during the pandemic. Therefore, the COVID-19 pandemic had a positive impact on the machine learning in banking market trends.

Key findings of the study

• By component, the solution segment led the machine learning in banking market in terms of revenue in 2021.
• By enterprise size, the large enterprises segment accounted for the highest machine learning in banking market share in 2021.
• By region, North America generated the highest revenue in 2021.

The key players profiled in the machine learning in banking market analysis are Affirm, Inc., Amazon Web Services, Inc., BigML, Inc., Cisco Systems, Inc., FICO, Google LLC, Mindtree Ltd., Microsoft Corporation, SAP SE, and SPD-Group. These players have adopted various strategies such as product development to increase their market penetration and strengthen their position in machine learning in banking industry.