Banks and Investment firms are expected to spend over $600 Billion on Technology services in 2022, according to Gartner. Generative AI, the next phase of Artificial Intelligence is gaining traction in Banking services. The other major tech trends impacting Banking are Autonomic Systems and Privacy-Enhancing Computation.
IT spending by banking and investment services firms is forecast to grow 6.1% in 2022 to $623 billion worldwide. The largest category of spending is IT services, which includes consulting and managed services and accounts for 42% of total IT spending in the sector at $264 billion.
What is Generative AI?
Generative Artificial Intelligence (AI) is a relatively new buzzword in the field of Artificial Intelligence. This disruptive tech is one of the most impactful emerging technologies and trends of 2022 and beyond, according to Gartner.
Generative AI refers to AI techniques that learn a representation of artifacts from the data and use it to generate brand-new, completely original artifacts that preserve a likeness to original data.
Gartner forecasts by 2026, generative AI will create 50% of the new website and mobile app code using machine learning models. It could automate 60% of the design effort for new websites and mobile apps.
To know everything about Generative AI, check out the ITVibes report here.
Trend 1: Generative AI
Gartner predicts that 20% of all test data for consumer-facing use cases will be synthetically generated by 2025. Generative AI learns a digital representation of artifacts from data and generates innovative new creations that are similar to the original but does not repeat it.
In banking and investment services, application of generative adversarial networks (GANs) and natural language generation (NLG) can be found in most scenarios for fraud detection, trading prediction, synthetic data generation and risk factor modeling. It has potential because of the ability to take personalization to new heights.
Trend 2: Autonomic Systems
Autonomic 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 technology capabilities that support new requirements and situations, optimize performance and defend against attacks without human intervention.
Currently, autonomic systems are mostly software-based in the banking context. However, humanoid robots are emerging in smart branches
Humanoid robots are examples of hardware-based autonomous systems that cater to clients and customers. They could be applied in autonomous debt management, personal finance assistants and automated lending.
Robo-advisors are low-level autonomic systems, although there are still concerns about trust.
Trend 3: Privacy-Enhancing Computation
Privacy-enhancing computation (PEC) secures the processing of personal data in untrusted environments — which is increasingly critical due to evolving privacy and data protection laws, as well as growing consumer concerns. It uses a variety of privacy-protection techniques to allow value to be extracted from data while still meeting compliance requirements.
Gartner predicts that 60% of large organizations will use one or more privacy-enhancing computation techniques in analytics, business intelligence or cloud computing by 2025.
The adoption of PEC is on the rise in use cases like fraud analysis, intelligence operations, data sharing and anti-money-laundering.
