Rob Delaney, VP at VC firm Carrick Capital Partners, shares some predictions and hopes for his portfolio companies as they navigate through the economic storm caused by the Covid-19 pandemic. What's changing about our industries? What needs to change about the way we handle data? How are strategic priorities shifting? Rob shares his valuable perspective on these and other topics in this episode. Want to learn more about how to get started deploying AI in your business? Download Emerj's free guide here: emerj.com/beg1

Today's interview is with Aki Ranin, Cofounder of Bambu, a robo-advisor platform based in Singapore. Bambu has raised millions to expand in Asian and American banking markets. Aki is also an adjunct lecturer on AI and machine learning at Singapore Management University. In this episode, he breaks down where AI fits into the world of robo-advisors and is frank about where AI isn't needed. For quick insights, download Emerj's AI in Financial Services Cheat Sheet: emerj.com/fin1

Building a scaleable and productive AI product for the enterprise is not easy. Our guest this week helps listeners think through how to go about it successfully. Suhas Uliyar, VP of Product Management for Digital Assistant AI, Mobile, and Integration at Oracle, discusses why security and scale are key to building AI products that will actually deliver value at large companies. If you're interested in building AI products for the enterprise or want to get started with AI at your company, be sure to download our Beginning With AI Guide at emerj.com/beg1.

Our guest this week has a unique perspective on how technology priorities are changing in financial services as the pandemic unfolds: Sébastien de Brouwer, Chief Policy Officer at the European Banking Federation. We speak with him about how the financial services industry is struggling during the crisis, as well as which jobs will ultimately survive and which will not. If you want to discover how some of the largest companies in financial services are investing in AI, join our new Emerj Plus membership at emerj.com/plus

At this time, many strategic initiatives are being put on pause. The initiatives that tend to still have momentum are related to either driving efficiencies or reducing risk. And when it comes to risk, few are greater than regulatory risk. This week, we interview Yinglian Xie, CEO and co-founer of DataVisor. Yinglian discusses how AI fits into the compliance landscape in financial services. If you want to explore more AI use-cases across financial services and see what the big players in the sector are doing, you can use our AI Discovery tool with Emerj Plus. Learn more at emerj.com/plus

During the pandemic, there has been more emphasis than ever on "low-hanging fruit" AI applications and use-cases. Fraud detection is one of these use-cases. There will be an uptick in financial crimes as happens during economic crises. This week, we speak with H.P. Bunaes, General Manager of Financial Services at Datarobot, which focuses on AutoML. H.P. speaks with us about how fraudulent payments often happen and can go undetected, as well as how AI could play a role in detecting them. He also discusses how to deploy AI applications for fraud detection in financial services. To learn about how we map the ROI of AI in financial services, watch our short 2-minute video on our AI Opportunity Landscape research at emerj.com/fs1.

The coronavirus is dominating the news, and we figured it was important to cover it as it relates to AI in financial services. This week, we discuss what chatbot adoption will like look during and after the pandemic. Our guest is Nat Cartwright with Finn AI. She speaks about viable use-cases for AI in customer service and where she thinks those priorities will become more important as we start to pull out of this economic moment we see ourselves in. We also put together a report on AI priorities as they relate to coronavirus, the AI Business Continuity Action Plan, and we're giving it away free with the first month of Emerj Plus at emerj.com/ap1.

One of my favorite presentations last year was one I gave at an event called PayThink in California. I came to learn that there are more events about payments than almost any other topic in financial services. This week, we interview the CEO of Deserve, Kalpesh Kapadia, about the future of payments. He discusses which aspects of how we pay for things will be different and explains how AI plays a role in payment fraud. For more on the applications of AI in financial services, be sure to download our AI in Financial Services Cheat Sheet at emerj.com/fin1.

We are changing the name of our podcast to AI in Financial Services. In this episode, Dan explains why and discusses how the show will address the coronavirus pandemic and how it affects innovation in financial services. 

While a lot of people are excited about customer-facing applications in financial services, right now, the ROI of AI comes down to fraud detection and compliance use-cases. That's what this episode is about. We interview Hani Hagras, Chief Science Officer of Temenos. Hani speaks with us about the present and future of AI for compliance, including where banks can reduce risk and how AI could help. If you're interested in how we track AI ROI across different industries, you can learn more about our AI Opportunity Landscape service at emerj.com/fs1.

When it comes to adopting AI applications, the team lessons are almost always better understood by the vendors than by the banks. This week, we speak with Sasha Caskey, CTO of Kasisto. He speaks with us about what he's learned from working with teams that get it right and teams that don't. He also provides a particularly interesting insight about the importance of having "nurturing" data scientists. If you haven't downloaded our Beginning With AI Guide, it includes some of our best takeaways about how to get started with AI from dozens of interviews over the last few months. You can download it at emerj.com/beg1.

Our guest this week, Madhu, works at one of the top 10 Australian banks. He has a lot of experience applying AI in customer service. Madhu speaks about how to grow an AI team, when to hire data scientists, when to hire someone to lead those data scientists, and what kinds of talent needs to be there to help guide data scientists.  If you're interested in learning more about our AI Opportunity Landscape work in the financial services industry, watch our video at emerj.com/fs1.

Our focus this month on AI in Banking is on building a successful data science team. This week, we speak with Jan Veldsink, who heads up AI for compliance at Rabobank.   He discusses how to educate cross-functional AI teams, answering questions about how to get subject-matter experts and data scientists on the same page and how to measure the success of AI teams.   If you're interested in getting started with AI at your bank or financial institution, be sure to download our Beginning With AI PDF guide at emerj.com/beg1.

Almost any time we engage with financial institutions, chatbots are at least part of the conversation. There are not many credible chatbot companies that are focused explicitly in banking, but Kasisto is one of them. Our guest this week, Sasha Caskey, is CTO of Kasisto. Sasha talks about starting small with chatbots and reasonable expectations for them in banking. If you're interested in mapping the full landscape of AI applications in financial services, be sure to watch our AI Opportunity Landscape video at emerj.com/fs1.

Our guest this week, Paul Barba, heads up AI efforts at Lexalytics. I visited their headquarters as part of our AI in Montreal piece we released about 2 years back. Paul speaks with us about how NLP can layer value on top of conversational interfaces, as well as the limits of chatbots and NLP in finance. For more on what NLP can and can't do in business, be sure to download our 9-page guide, Unlocking the Value of NLP in Business, at emerj.com/nlp1.

This week, we interview Madhu, who works on conversational interfaces at one of the four largest Australian banks. He speaks today about the phases of deployment for bringing a chatbot to life in financial services. It involves more phases than people might presume, but they are important to understand. If you have an interest in the broader AI opportunity landscape in banking, you can learn more about how we can help at emerj.com/fs1.

This month, we start a brand new theme: chatbots in banking. Nothing is more hyped in banking than chatbots, so we want to shed some light on what's actually happening with chatbots in the banking industry and what really isn't.  Our guest this week is Scott Nowson, AI Lead at PwC, Middle East. Scott talks about the three phases of building a chatbot from scratch. Scott was also one of the first to review our Getting Started With AI Report. If you're looking to apply AI within your business, our Getting Started With AI report is a distillation of our best AI adoption insights from over 50 interviews with executives in the enterprise and at AI vendor companies. You can learn more about it at emerj.com/a1. 

This week, we interview Jan Veldsink, head of AI for compliance at Rabobank. He's been using AI and advanced statistics to detect fraud at Rabobank for nearly ten years. He shares with us some practical near-term applications of NLP in compliance, as well as his ideas on where NLP can add more value to banking in the future. This is our last episode in January's series on NLP in banking. If you want to take action on the ideas we've talked about this month, be sure to download our guide on NLP use-cases at emerj.com/nlp1.

This week, we speak with a fan favorite guest from our AI in Industry Podcast: Dr. Charles Martin of Calculation Consulting. Charles talks about the challenges of applying natural language processing to wealth management, including what's working and what's not with AI in wealth management. He has a lot of experience applying AI in the enterprise, and I think you'll enjoy this particular episode quite a bit. If you're interested in NLP and where it can be used in your business, download our NLP use-case guide at emerj.com/NLP1.

We speak this week with Greg Council, VP of Marketing and Product Management at Parascript, an AI-enabled search and discovery vendor selling into the financial services sector. In this episode, Greg discusses what NLP can and can't do in the banking industry. If you're interested in broad natural language processing use-cases and you haven't already downloaded our NLP use-case guide, you can do so at emerj.com/NLP1.

It's the first episode of the new decade, and we're kicking off with our theme for the entire month of January: natural language processing (NLP) applications in banking. Our first guest is Lee Smallwood, COO Markets and Securities at Citi. He was a trusted advisor for our most robust AI in banking research report. This week, Lee talks about front- and back-end NLP applications in banking, and I think he paints a great overall picture that will tee up the other three interviews for this month well. If you're interested in where NLP could fit in your business, download our Unlocking the Business Value of NLP PDF guide. It's the most succinct resource for figuring out where NLP would make a difference at your company. Download it at emerj.com/NLP1.

This is an excellent episode. We speak with Ritchie Ng, Chief AI Officer at Ensemble Capital. Ritchie goes into a topic we really haven't covered much in this series and which hasn't been a big focus of the podcast: hiring data scientists. That's hard when Google and Facebook are grabbing the top talent. Ritchie goes into how this should be done. If you're getting started with AI at your business, be sure to download our guide on beginning with AI, which outlines 3 critical steps to initially adopting AI that most companies end up getting wrong. Download it at emerj.com/beg1.

This week, we speak with Marek Bardonski, CEO of AI Rev. He was previously with Sigmoidal, where his focus was on AI for wealth management. When it comes to what banks can do that startups can't, it's make the most of the money they have on hand, and the future of wealth management and trading is potentially an area of edge for smart financial services firms and banks around the world. In this episode, Marek goes into what is and isnt possible with AI as it relates to trading in particular. Download our short guide, 3 Ways to Discover AI Trends in any Sector, if you're interested in finding high-ROI AI opportunities in your sector at emerj.com/t3. 

This week, we speak with Executive Director of AlgoDynamix, Jeremy Sosabowski, about how banks can leverage partnerships and vendors as opposed to building in-house AI talent. He also speaks to us about how banks can deal with some of their inherent weaknesses when facing up against the startup ecosystem. if you're interested in natural language processing applications in banking, be sure to download our NLP use-case guide at emerj.com/NLP1   Emerj.com/NLP1

In this episode of AI in Banking, Eigen Tech CEO Lewis Liu shares his thoughts on how banks can leverage their data, expertise, and deployable capital to compete and keep up with AI startups - and to stay relevant in the years ahead.  Lewis's original interview was part of our AI in Banking Landscape report. If you haven't yet downloaded your copy of the executive brief of this report, download it online at: emerj.com/b1

This month, we're focused on how banks can survive and thrive in an era of Ai disruption. Our first guest is Rob Delaney with Carrick Capital. Rob speaks with us about where banks can focus their own internal AI efforts if they want to compete with fintechs, whether they focus on customer-facing applications or internal applications. He also discusses what the future ecosystem looks like in terms of how finance is being transformed.

This is our final episode in our month-long series on AI for search and discovery in banking, and this week we speak with Dan Courtright, Senior Director of Management at Iron Mountain. If you've ever taken out a loan from the bank, you know that there is a lot of paperwork involved. AI-enabled search and discovery applications could help streamline loan processing and loan origination, as well as help underwriting,  assess applicant risk. Dan and I discuss these use-cases in more in the final episode of this month's theme. AI-enabled search and discovery is one capability of natural language processing, a type of artificial intelligence. For more NLP use-cases, download our latest resource at emerj.com/NLP1.

In this episode, we continue our theme on AI-enabled search and discovery in banking by interviewing Sheetal Rishi, Global Cognitive and Data Leader at IBM. She previously spent time McKinsey and Citi.  Sheetal speaks to us about which functional departments she believes there exists the most need for search and discovery applications in banking, and she discusses how the areas in which banks spend their money signals their motives for adopting AI technology.

This week, we speak with Luca Scagliarini with Expert System about a number of low-hanging fruit NLP applications within banking, including those for wealth management. He discusses where the advantage lies in terms of using NLP to decide on making investment decisions for clients. There's a lot of action in this space, and Luca does a great job of summarizing it. He also discusses where chatbots will go and how the customer interaction will change in the years ahead, including how customers will be able to use chatbots to take actions instead of just get simple questions answered.

This week kicks off our first episode in our month-long series on AI for search and discovery in banking. How can AI help us find data, find files, find documents within a bank's intranet? Whether we're looking for customer information, legal issues, or the right document, how can AI help? This week, we speak with Simone Bohnenberger-Rich of Eigen Tech about how banks can use AI to find documents that might require a review before the sunset date of LIBOR in 2021. This episode presents a great example of how AI for search and discovery can be used to maintain compliance and reduce risk.

This is our final episode in our series on building a culture of innovation in banks, our analyst episode in which Emerj CEO Daniel Faggella summarizes and adds insight to the interviews from this past month. In this episode, Daniel talks about the individual greatest factor in determining whether a bank has a culture of innovation or not: how well the C-suite can articulate an AI transformation vision.

This week, we speak with Mark Gazit, CEO of Thetaray, an AI vendor that focuses on financial fraud and anti-money laundering. Mark speaks with us from a vendor perspective about what kind of culture a bank has when it adopts AI the right way and what kind of culture it has when it adopts AI the wrong way. Mark also doubles down on the idea that the culture of innovation needs to be top-down, coming from the leadership team.

When banks, financial services companies, and even AI vendors servicing the banking landscape look to innovate in how they improve their customer experience, it's almost never because they want to service their most valuable customers today. It's almost always driven by what they know the next generation is going to expect. Whenever we do work for our clients, Millenials are almost always on the tip of their tongues. This week, we speak with Michelle Scarborough, Managing Partner of Strategic Investments and Women in Tech at BDC. from the perspective of both a banker and an investor about what innovation means for Millenials, as well as how banks can enable the innovation that will attract and retain this new generation of digital citizen.

This month's theme is the culture of innovation within banks. When we did our AI in banking Vendor Scorecard and Capability Map report and we asked bankers what the biggest barrier to AI adoption in banking was, the number one response was the lack of a culture of innovation within banks. And the question is: how do we change that? How do we cultivate that culture? In this episode, we interview Josephine Baliah, former Head of Client Experience Design at FirstRand Group, about having leadership that steps behind innovation. She talks about what the leadership can do and where it can be hired from.

This is the final episode of our September series on Strategic Recommendations for Bankers. My job this week is to connect the dots between some of the insights we got from our interviewees this month. This includes one common thread across interviews: banks have an underlying fear of the FinTechs popping up everywhere and eating market share.

This week, we speak with With Sebastien de Brouwer, Chief Policy Officer at the European Banking Federation, about where banking leaders should be focused when it comes to AI in banking. Sebastien discusses which areas of banking—customer experience, legal risk, positioning—banks might latch onto when allocating budget for AI.  

Our guest this week is Nishant Chandra, PhD and Senior Director of Data Products at Visa. Nishant speaks with us about how banks can pivot to play to their strengths in a future where the technology landscape is shifting under their feet. He uses some good examples from Apple and GE that can help banking leaders think through how their culture can change to make AI a positive and not a negative.

This week, we spoke to another of our research advisors: Lee Smallwood, COO of Markets and Securities for Citi North America. Lee speaks with us about the dynamics of AI talent: finding the right talent and growing the right talent. How can a bank attract the right young people, train the right people within their organization, and martial them to success with AI in the future? How does a bank compete with Google, Facebook, and other AI-focused giants for AI talent? We answer these questions in this week's interview.

This month we focus on strategic recommendations for AI in banking. We're bringing back our research advisors for our AI in Banking Vendor Scorecard and Capability Map report, and this week, we speak with Ian Wilson, former Head of AI at HSBC. Wilson shares some of his thoughts as to what bankers should be thinking about when it comes to AI. Specifically: 1. Why is all the investment and attention around AI focused on risk? 2. What banking leaders should do to prepare for when that emphasis shifts away from risk.

It's the final episode of our month-long series on AI for the customer experience in banking. This week, Emerj CEO Daniel Faggella breaks down the insights from this month's interviews and colors them with data from our AI in Banking Vendor Scorecard and Capability Map report. In this episode, Daniel draws a picture about what the data says about AI for customer-facing applications in banking and barriers to adoption for AI in customer service.

This week we're joined by Sasha Caskey, the CTO of Kasisto. Kasisto is the highest-rated conversational interface vendor in our AI in Banking Vendor Scorecard and Capability Map report. Caskey discusses the future of where conversational interfaces fit into banking, including the automation of repetitive tasks. She also talks about the challenges of personal assistance, and how the real revolution in terms of market share may not come from established banks, but entirely digital banks and entirely digital currencies.

This week, we speak with Sindhu Joseph, CEO at CogniCor. She drops a quote in this interview that I really love and that I think hits on this month's theme well: "People don't need banks. They need banking." Joseph discusses how banks will have to transform to meet consumer expectations that are set by big tech. She talks about how one could hypothetically build a bank for 10% of the cost that banks run on today, and what that means for large banks. Finally, Joseph talks about how the banking workforce will change in response to artificial intelligence. For more on how AI is transforming banking, download the Executive Summary Brief of our AI in Banking Vendor Landscape at Capability Map.

The theme for the entire month is AI for the customer experience in banking. In this episode, we speak with Yinglian Xie, CEO at Datavisor. Xie sheds light on how users will expect to have "zero-step" authentication, the "friction-free" future of banking. Xie paints a picture about how the experience consumers have with big tech (such as a Facebook app) can be transferred into banking. She gives a sense for how backend data can have a strong effect on how well banks can serve customers on the front end. Xie also talks about the value of new data sources as banks shift into the digital world.

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.