Naturally Intelligent: Embedding operational AI in financial services
There is much discussion in the banking and financial markets sector these days about Artificial Intelligence (AI). “Robo-Advice” in particular is generating a lot of hype in the industry, with a swathe of new funds pushing their AI-based programmes to end investors, promising excellent returns. Investment Banks are also increasingly looking at how predictive analytics and machine learning can improve profitability by providing assisted decision-making in the sales/trading environment.
The challenge for banks is how to do any of this in a differentiated way, particularly as many - with their legacy architectures and organisational structures - aren't ideally set up for integrating AI-based systems. With other complexities in terms of end users, asset classes, instruments, risk and regulations, what are the implications - and practicalities - of banks trying to operationalise AI?
In this paper, 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 and exploring the choices firms need to face in order to overcome hurdles in implementation. Speaking with Rael Cline of MediaGamma, Jonty Field at Quantitative Brokers, Chuck Ocheret at NEX Optimisation, Massimi Morini at Banca IMI Intesa San Paolo and Software AG’s Michael Zeller and Charles Platt, they build a picture of how firms are operationalising AI to achieve new approaches to service and develop truly digital business models.
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