We looked 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. The outcome is Augmented Finance -- an investor’s guide to how AI is pulling apart and breaking down the financial services industry. We estimate the economic impact of AI on financial firms globally, finding nearly 20% of costs potentially reduced through implementations, equivalent to $1 trillion by 2030.
AI is not a panacea nor a single thing. It's math, data and software, searching for the right use case. In this dive, we looked at conversational interfaces, biometrics, workflow and compliance automation, and product manufacturing in lending, investments 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. And 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.
In the US alone, 2.5 million financial services employees are exposed to AI technologies. There is potential cost savings of $490 billion in front office, $350 billion in middle office, $200 billion in back office, totaling $1 trillion across banking, investment management and insurance. Not surprisingly, many firms talk about AI, but very few actually hold intellectual property in the space. And the best performer -- Bank of America -- is still leagues behind the GAFA. Talk about Black Swan risk!
In mapping out the future of AI in financial services, we saw several routes. One potential path is that AI tech companies like Amazon and Google continue to add skills to their smart home assistants, with Amazon Alexa sporting over 20,000 skills already, outcompeting finance companies and stealing their clients. Another potential path is the example of China, where tech and finance merge (e.g., Tencent, Ant Financial) to build full psychographic profiles of customers across social, commercial, personal and financial data. And last, but increasingly tangible, is the path is towards decentralized autonomous organizations that are built by the crypto community to shift power back to the individual, with skills made from open source component parts.