Market Trends of Automated Machine Learning Industry
The BFSI Segment is Driving Market Growth
- AI and ML technologies are increasingly adopted in the banking, financial services, and insurance (BFSI) industry to enhance operational efficiency and improve the consumer experience. As data gains more attention, the demand for machine learning BFSI applications grows. Automated machine learning can produce accurate and rapid results with enormous data, affordable processing power, and economical storage.
- Machine learning (ML)-powered solutions also enable finance firms to replace manual labor by automating repetitive operations through intelligent process automation, increasing corporate productivity for chatbots, paperwork automation, and employee training gamification, among others. Machine learning is expected to be used to automate financial processes.
- After the pandemic, financial institutions showed increased interest in reaching and assisting customers through digital channels. Various digital solutions, including chatbots, account opening and management support, and technical assistance, witnessed a surge in adoption within the finance sector, especially in fintech corporations like Posh. Tech, Spixii, and numerous others now provide intelligent chatbots designed to facilitate essential customer-facing functions for banks.
- HDFC Bank uses an AI-based chatbot, "Eva," built by Bengaluru-based Senseforth AI Research. Since its launch in March this year, Eva (which stands for Electronic Virtual Assistant) has addressed over 2.7 million client queries, interacted with over 530,000 unique users, and held 1.2 million conversations. Deutsche Bank announced a multi-year innovation partnership with NVIDIA to accelerate the use of artificial intelligence (AI) and machine learning (ML) in the finance sector.
- Banks must improve their services to offer better customer service with the rising pressure in managing risk and increasing governance and regulatory requirements. The rising number of bank fraud cases is expected to increase the adoption of AI and ML. Some fintech brands have been increasingly using AI and ML in different applications across multiple channels to leverage available client data and predict how customers' needs are evolving, which fraudulent activities have the highest possibility to attack a system, and what services will prove beneficial, among others.
- In FY 2023, the Reserve Bank of India (RBI) reported more than 13 thousand bank fraud cases across India, an increase compared to the previous year. It turned around the previous decade's trend. Such increases in bank fraud may further generate market demand.
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North America to Hold a Significant Market Share
- North America is expected to hold a substantial share of the market owing to the robust innovation ecosystem, fueled by strategic federal investments into advanced technology, complemented by the existence of visionary scientists and entrepreneurs coming together from across the world and recognized research institutions, driving the development of automated machine learning (AutoML).
- Various governments, including state and local governments, handle enormous quantities of citizen data, which used to be stored on paper and processed manually. However, as artificial intelligence (AI) and machine learning technologies provide faster and more accurate data-gathering and processing methods, governments can focus on more complex and long-term social and cultural issues. Further, an increase in commercial applications for federated ML is expected to drive the demand for AutoML.
- According to the Government of Canada, artificial intelligence (AI) technologies promise to enhance how the Canadian government serves its citizens. As the government investigates the usage of artificial intelligence in government programs and services, it ensures that clear values, ethics, and rules guide it.
- While the United States is trying to establish AutoML supremacy, Canada is also gearing up for such developments. For instance, in April 2023, ePayPolicy launched Payables Connect, the latest addition to its insurance payment and reconciliation products suite. It leverages ePay's existing integration and machine learning technology to automate the reconciliation, design, and payment of due payables completely.
- Though Canada is still in the initial phase of deploying automated machine learning across various industries, some factors, including the rising need to automate the finance sector and the emerging educational interest among students, are expected to drive market growth.
- The region's AutoML market is changing due to the cloud; serverless computing allows creators to get ML applications up and running quickly. For instance, in October 2023, according to AWS, US cloud computing infrastructure investment exceeded USD 108 billion.
- Moreover, many organizations of different sizes are transforming from traditional to digital modes of business. This transformation creates a hybrid cloud market because of the benefits, like reduced total cost of ownership (TCO), high security, flexibility, and agility. IBM stated that 89% of IT leaders are expected to move business-critical workloads to the cloud, and the growth in digitization drives all. Such expansion in cloud solutions may further propel the market’s growth in the region.
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