Kensho’s artificially intelligent investment analysis platform is one of the largest AI acquisitions in history, selling to the S&P for $550 million. But that is merely a harbinger of what is to come. Over $1 trillion of today’s financial services cost structure is exposed to replacement by machine learning and AI. When will this age of AI finally arrive? What are the implications for the industry – and for the rest of us?
We are excited to share with you our keystone industry analysis to answer these questions with rigor and detail in two thematic parts. The first focuses on “Machine Intelligence”, and is a primer that explains how artificial intelligence works, what is motivating the revolution in neural networks, providing examples of technology and top players, and highlighting the potential future of the software. The second is about "Augmented Finance”, and is an investor’s and operator's guide to how AI is pulling apart and breaking down the financial services industry. We look at the applications of AI across the front, middle and back offices of banks, investment managers and insurance companies, highlighting a rich ecosystem of sophisticated software. We estimate the economic impact of AI on financial firms globally, finding nearly 20% of costs potentially reduced through implementations.
This 84 page analysis is available below.
For paying clients, we provide this analysis in two longer parts with more detailed estimates. If you are an institutional investor or financial organization, contact us to speak about enterprise access.
In US alone, 2.5 million financial services employees are exposed to AI technologies. Potential cost exposure of $490 billion in front office (distribution), $350 billion in middle office, $200 billion in back office (manufacturing), totaling $1 trillion across banking, investment management and insurance
In the front office, the most promising applications focus on integrating financial data and account actions with software agents that can hold conversations with clients, as well as support staff
In the middle office, as regulations become more complex and processes trend towards real-time, artificially intelligent oversight, risk-management and KYC systems can become very valuable
In product manufacturing, we see AI used to determine credit risk using new types of data (e.g., social media, free text fields), take insurance underwriting risk and assess claims damage using machine vision (e.g., broken windshield), and select investments based on alternative data combined with human judgment
Many firms talk about AI, few actually hold intellectual property in the space, which creates Black Swan risk in the industry under winner-take-all dynamics
Selected Charts & AI Market Maps
Are you a financial enterprise or institutional investor interested in our help with the intersection of Artificial Intelligence and the financial services industry? Reach out to learn more.