AI in Financial Services Podcast

We learned a lot about AI in risk-related banking functions, such as fraud, cybersecurity, compliance, and lending, in our AI in Banking Vendor Scorecard and Capability Map report. In this month's analyst deep dive, Emerj CEO Daniel Faggella discusses some of the insights garnered from the data in our report about why vendors selling products for risk-related functions have raised so much money and why AI is such a good fit for fraud and cybersecurity.

This week, we speak with Owen Hall, CEO at Heliocor, about the proliferation of what Hall calls "breadcrumbs," digital touchpoints that a user has with a bank. He talks about how these touchpoints are creating new opportunities for banks and, also, new risks in terms of fraud and cybersecurity. Hall also discusses how banks can leverage their brand, in contrast to other guests we've had on the podcast, who are less optimistic about brands as an asset.

This week on the AI in Banking podcast we interview Ohad Samet, CEO of TrueAccord, about the applications of artificial intelligence for debt collection. We discuss personalized messaging, collection forecasting, and the debt collection AI lessons that might be applied to other finance use-cases. This is the third episode in our month-long focus on risk-related AI functions in banking.   Subscribe to the AI in Banking Podcast: https://emerj.com/ai-in-banking-podcast/ Related article: https://emerj.com/ai-sector-overviews/artificial-intelligence-applications-lending-loan-management/

This week, we speak with Adam Hunt, CTO of RiskIQ, about how cybersecurity is shifting in the world of banking and financial services and why AI will be necessary to handle those changes. Fraud and cybersecurity startups selling to banks have raised more than vendors for any other business function, and we talk about why AI is such a good fit for cybersecurity in banking. Hunt also discusses how banks can secure AI talent in banking. Working on cybersecurity at a bank may not be as flashy as working on self-driving cars or working for Amazon, but there are things banks can do to attract AI talent they'll need to build and maintain cybersecurity systems.

This week, we speak with Gunnar Carlsson, co-founder of Ayasdi, one of the better-known anti-money laundering AI vendors and one of the highest ranking in our AI in Banking Vendor Landscape report. Carlsson pioneered his own branch of mathematics that eventually became the backbone of Ayasdi's AI software. We speak to Carlsson about methods of calibrating and understanding risk at banks, new sources of data and algorithmic approaches (and what they mean for banks), and the difference between supervised and unsupervised learning. Both machine learning techniques can be used to solve business problems in unique ways. Lastly, we discuss with Carlsson something of critical importance in risk-related functions: knowing your customer.

Former Head of AI at HSBC, Ian Wilson, discusses the importance of developing individual AI strategies for each business function in banks. He emphasizes the need for business leaders to drive AI initiatives, address challenges in implementing AI, and focus on risk reduction. Wilson also highlights the significance of the AI roadmap, addressing the comfort factor in AI deployment, and the current phase of AI adoption in banking.

Customer experience is what wins, according to Lee Smallwood, COO Markets and Securities Services at Citi. In this episode of the AI in Banking Podcast, we speak with Smallwood about how fintech companies are already using AI to improve the customer experience and how banks will likely have trouble competing with them on that front.  Smallwood, however, also talks about how banks can leverage their existing assets to retain market share in functions in which fintech companies don’t have the resources to compete, such as asset management. Learn what banks should be thinking about when it comes to developing winning AI strategies to compete with fintech startups.

Banks have several challenges to AI adoption. One of them is their legacy IT and data infrastructures which aren’t built or organized for machine learning. Nishant Chandra, PhD, Senior Director of Data Products at Visa, outlines how banks can transition their legacy systems to systems ready for AI. Chandra discusses the importance of leadership teams in cultivating a company culture necessary for adopting AI with any success, and he gives examples of times when he’s seen old systems hold a company back from adopting AI and when he’s seen leadership do the same. Discover how banks can overcome some of the pitfalls to AI adoption in this episode of the AI in Banking Podcast.

According to Sergey Gribov, Partner at Flint Capital, “banks are the ultimate commodity.” Fintech startups can offer banking services with leaner teams and better customer experiences using artificial intelligence. But banks need to differentiate themselves somehow from not just fintech companies, but other banks, especially as they decide which banking functions they want to focus on in the coming decade. Banks will almost certainly become leaner operations to stay in business, and they’ll need to make strategic decisions that direct their future.  In this episode of the AI in Banking podcast, Gribov offers a frank picture of the banking landscape in the coming years and how banks will need to respond to it.

The Emerj team discusses insights from our AI in Banking Vendor Scorecard and Capability Map report. Which banking functions are banks eager to automate with AI? Which functions are sucking up all of the venture capital funding? Which AI capabilities are all hype? Emerj CEO Daniel Faggella and lead analyst Raghav Bharadwaj break down what our data tells us about the future of artificial intelligence in banking in this episode of the AI in Banking Podcast.