The opportunity to grow financial services business through artificial intelligence (AI) is closer than you think.
AI, machine learning (ML) models and predictive analytics are revolutionizing business just as the PC did in the early 1980s. The technologies that enable these are already established at low levels within financial services organizations.
Analysts see real value in using intelligent technologies; Tractica has estimated the market for AI systems for enterprise applications could increase from US$202.5 million in 2015 to US$11.1 billion by 2024.
Sarj Nahal, equity analyst at Bank of America Merrill Lynch, has estimated that the adoption of robots and AI could boost productivity by 30% in many industries, while cutting manufacturing labor costs by 18-33%.
AI, as the operationalized model of these technologies, can handle data sets that humans cannot. It can find patterns within this information with speed and precision. Leaders in the space are already taking advantage of these abilities to build more elegant risk modeling algorithms. Traders can make fewer, better-informed choices whilst seeing a more complete picture of the market.
AI is developing at a breakneck pace, but its potential and implications – including issues around decision-making – create challenges that firms need to address before they can embed AI within their organizations.
In the paper “Naturally intelligent: Embedding operational AI in financial services,” Dan Barnes and Mike O’Hara of The Realization Group investigate the real-world applications of AI within financial business today, taking use cases from experts in the field build a picture of how firms are operationalizing AI to achieve new approaches to service and develop truly digital business models.
Download the white paper to learn how you can make AI work in a live environment.