How AI will Impact Growth Strategies in Financial Services- Part 2 AI Myths

Not everyone gets a second byte at the apple, but I have been among those fortunate enough to. As a card-carrying member of that club of entrepreneurs who have had successful exits, I was left to indulgently wonder: what’s next? Both for me, and the future of my field? Robotics has always been a passion, given my backgrounds in engineering and business, and so, building upon that, my natural conclusion to that existential question was quick and simple: AI. After all, the man-machine marriage is inevitable. As Ray Kurzweil puts it: we are already there – how do you feel when you leave your iPhone home? 

Knowingly or not, we are all transitioning to a digital economy – where bits and bytes represent more and more of the way people communicate, conduct business make decisions and - most importantly - socialize. The key ingredient in this transition is the ability to get large quantities of (relevant) data, the ability to process it and the ability to come up with insights or knowledge that can help a firm – whether it is in acquiring new clients, testing products and services, hiring staff or deciding on a growth strategy. This is evident in market capitalizations. The top 5 US tech firms were valued at more than $3 Trillion USD cumulatively; leaving behind all traditional companies in 2017(1). While AI is affecting the financial industry, why has it not succeeded (especially in Capital Markets) as much as it has in consumer marketing, online businesses, social media and retail? There are a few reasons: 

1) The first response when you go to any banker or analyst is –will I lose my job? This fear of being dis-intermediated is not to be taken lightly. The question to me is not “will AI replace my job?” – but “how will AI transform it?” 

2) The industry is successful with record profits. The financial industry has had a record growth spurt since 2008, so they are doing so well that they are not really looking to disrupt currently working models. They are not willing to take new risks. 

3) AI innovation requires rapid iteration which needs to tolerate mistakes. The financial industry does not tolerate mistakes well. 

However, there are pockets of successful AI adoption. Some of the most successful money managers have been using machine learning and quant computing (earlier name for AI) in their investment processes and have already shown great success in doing so. 

While AI adoption is new and has a lot of promise, one must remember that - at its core -it is a tool that needs to be used to serve some corporate, social or individual purpose. It’s not an end to itself, as I’ve discussed in previous posts. AI is set to transform the financial industry as is already evident in various applications: from digital banking to running machine learning algorithms to target the right set of prospects. Here’s how you can make the most of it: 

1) Partnerships: Don’t do it in-house – instead, partner with startups and innovation platforms to develop solutions using ML and AI tools to help solve business problems. Doing POC’s and pilots is a good process to inculcate innovative solutions to real business problems. 

2) Iterate, iterate, iterate: Do not expect the first implementation to be successful. Sometimes it takes many iterations to finally ask the right questions. Do you have the right data set? Is the tool modeling behavior correct or providing the right insights? Are the right problems being solved using ML as opposed to simple programming and automation? There are various components of AI, NLP, machine learning, deep learning etc. A company may start with a simple solution for simple problem and then iterate. Barclays Rise program to promote FinTech startups is one good example, as is Jet Blue’s Innovation Lab and Ideo’s effort to move from just design thinking and conceptualization to actual implementation of products and services and subsequently their go to market activities for their clients. 

3) Talent: Trying to have your current Analyst, MD of Banking or CTO do their day job and be deeply immersed in AI is setting yourself up for failure. To support AI properly, you must acquire talent that is relentless, can engage in design thinking with the right domain knowledge and is also willing to fail, and - more importantly - learn from those failures. 

Of course, all of this requires corporate sponsorship and the right environment. While Silicon Valley firms inherently have the funding and breathe the right ethos, firms in other financial capitals of the world – New York, London, Hong Kong, Tokyo - have a mandate to focus on adopting innovation on their business activities at hand. 

The disruption to the financial industry is coming and it is not from outside threats like we first encountered with wealth management platforms like Prosper, Evestment, Betterment (some of which achieved significant success), but from within the enterprise where firms will partner and implement cutting edge AI/ML tools to solve for growth, scalability and efficiency. If we are smart, when it happens, we’ll be card carrying members of the AI early adopters club. 

WORK CITED 

(1) Shaulova, E., & Biagi, L. (n.d.). Digital Economy Compass 2018. Retrieved from https://www.statista.com/study/52194/digital-economy-compass/ 

ABOUT THE AUTHOR 

Jayesh Punater is a successful Entrepreneur, Investor, Fintech Strategist and Thought Leader. He focuses on bringing innovative technology and business models to the fintech industry. Mr. Punater is the Founder and CEO of Nucleus, a FinTech studio and venture investment platform. Nucleus invests in start-up and advanced stage firms and provides operating capabilities, as well as talent and strategic advice. 

Besides Nucleus, he sits on the Board Member of First AI, a machine learning platform for credit investments, is on the Advisory Board of Adaptive Management, an alternative data marketplace as well as an analytics tool to help make better investment decisions. He is a member of the Advisory Board of Thales, a technology-based brokerage firm, member of the Advisory Board of Turner Investments, a member of the Economic Club of NY, and a member of C2C which is a peer CEO organization. 

Prior to Nucleus, Mr. Punater founded Gravitas from his apartment in 1996 and the business grew organically under his leadership to a global firm of 300 employees, providing Collaborative Outsourcing (his pioneered model) and a full front-to-back technology and services platform to clients managing more than $1.2 Trillion in AUM. In 2017 Gravitas was sold to a European publicly listed firm. 

Mr. Punater is a graduate of Arizona State University with a BSEE and a minor in Economics and has also taught an entrepreneurship MBA class at Fordham University. He enjoys traveling, swimming, chess, practicing mindfulness and visualization. Mr. Punater lives in New York City with his wife who is a mindfulness ninja and coach, and two sons who are 11 and 8 years old