Generative artificial intelligence (AI), autonomous systems, and privacy-enhancing computing are three technology trends gaining momentum in banking and investing in 2022, according to Gartner, Inc. These trends will continue to grow over the coming next two to three years, contributing to the growth and transformation of financial services organizations.
“While growth is the top priority, the need to manage risk, optimize costs and increase efficiency also requires new technological innovations,” said Moutusi Sau, VP Analyst at Gartner. “Generative AI enables bank CIOs to offer technology solutions to the business in pursuit of revenue growth, while autonomous systems and privacy-enhancing computing are long-term solutions that offer new options for business transformation in financial services.”
IT spending by banking and investment services firms is expected to grow 6.1% in 2022 to $623 billion globally. The largest spending category is IT services, which includes consulting and managed services and accounts for 42% of the industry’s total IT spending, or $264 billion. The fastest growing category is software, with spending expected to rise 11.5% to $149 billion.
The three emerging technologies identified by Gartner collectively contribute to a company’s management, growth, and transformation goals and have demonstrated use cases in banking and investing.
Trend 1: Generative AI
Gartner predicts that 20% of all test data for consumer use cases will be synthetically generated by 2025. Generative AI learns a digital representation of artifacts from the data and generates innovative new creations which are similar to the original but do not repeat it.
In banking and investment services, the application of Generative Adversarial Networks (GANs) and Natural Language Generation (NLGs) can be found in most scenarios of fraud detection, trading prediction, data generation synthetic and modeling of risk factors. It has potential due to the ability to take customization to new heights.
Trend 2: Autonomous Systems
Autonomous systems are self-managed physical or software systems that learn from their environments and dynamically modify their own algorithms in real time to optimize their behavior in complex ecosystems. They create an agile set of technological capabilities that support new demands and situations, optimize performance, and defend against attacks without human intervention.
Currently, autonomous systems are mostly software-based in the banking context. However, humanoid robots are emerging in intelligent branch offices which are examples of hardware-based autonomous systems that cater to customers and customers. They could be applied in self-help debt management, personal finance assistants and automated lending. Roboadvisors are essentially low-level autonomous systems, although there are still trust issues due to their high level of automation.
Gartner predicts that by 2024, 20% of organizations that sell autonomous systems or devices will require customers to waive the learned behavior indemnification clauses of their products.
Privacy Enhancing Calculation
Privacy Enhancement Computing (PEC) secures the processing of personal data in untrusted environments, which is increasingly critical due to changing privacy and data protection laws, as well as growing consumer concerns. It uses various privacy protection techniques to help extract value from data while meeting compliance requirements.
Gartner predicts that 60% of large organizations will use one or more privacy-enhancing computing techniques in analytics, business intelligence, or cloud computing by 2025.
Within financial services, data plays an inherent role in all efforts to analyze, compute and monetize data. PEC adoption is on the rise in use cases such as fraud analysis, intelligence operations, data sharing, and anti-money laundering.