Artificial Intelligence (AI) has revolutionized industries worldwide over the past decade, and its impact on banking and finance is becoming increasingly significant. With generative AI models taking the technology to new levels, the financial implications of AI are bigger than ever. AI-powered systems have a profound impact on predictive analytics, algorithmic trading, and personalized financial advice, leading to increased efficiency, security, and decision-making while reducing costs.
AI Adoption by Fintech Startups and Big Banks
Fintech startups are reaping the benefits of AI long before traditional financial institutions finish exploring it themselves. The increasing flexibility of AI systems and the public’s ability to integrate them into customized solutions is resulting in the birth of whole new industries and use cases. A recent report by PwC estimates the potential contribution of AI to the global economy will be $15.7 trillion by 2030. Startups have been at the forefront of AI development, with tech giants like Microsoft and Google pouring millions of dollars in investments and resources. Big banks, such as JP Morgan, Royal Bank of Canada, Citi, UBS, and Wells Fargo, are also leading the adoption of AI.
AI in Post-Trade Operations and Trading Venues
In post-trade operations, AI adoption is still in the early stages, as most central securities depositories and central counterparties rely on legacy technology infrastructures. However, some data reporting service providers and trade repositories are now developing AI solutions such as anomaly detection and automated data extraction from unstructured documents. Stock exchanges and other trading venues are also applying AI to detect irregular and potentially malicious trading activity. AI can currently improve trade execution performance, optimize hedging and quoting decisions, and automate brokers’ responses to client requests.
Smart Banking and the Role of Fintechs
Fintech has become its own category of financial services and a rival to traditional banks. Investment in fintech has grown from $61.1 billion in 2015 to $238.9 billion in 2021. Smart banking requires more than just technology; it also requires the right strategy and processes. Banks can adopt one of two approaches to compete with digital-first fintech: developing tech in-house or onboarding it from a dedicated supplier. Building tech in-house is expensive and time-consuming, and banks may struggle with fleet-footed development and process iteration. Fintechs often use agile frameworks and short “sprint” efforts to make progress quickly. There is an opportunity for main street banks to start tipping the scales in their favor by partnering with fintech to quickly integrate technology and focus on their advantage of brand recognition and a sense of security.
AI, Regulation, and the Future of Banking
AI promises to enhance marketing and decision models and improve efficiency in content generation. However, regulators are concerned about the potential for AI to perpetuate unlawful bias and discrimination. Financial technology developers and users need to explore and take advantage of the benefits of AI while avoiding fairness-based enforcement actions. A recent partnership between NatWest Group and the University of Edinburgh to create the Centre for Purpose-Driven Innovation in Banking aims to focus on
“challenge-led” research and innovation to improve how data is used to benefit bank customers, students, researchers, and policymakers. The center will combine business insights from NatWest Group with the university’s research, data, and social science expertise to co-create data-driven, novel solutions for the future of banking.