During the 45th episode of the Fintech Impact podcast, Jason Pereira sits with Daniel Faggella, CEO of Emerj. Daniel well known consultant in the Artificial Intelligence space and shares his thoughts current and future implementations of AI in the financial industry.
Show Notes:
- :30— Introduction of Daniel Faggella, CEO of Emerj
- 3:20— The AI trends we are seeing now and how they are adding value to fintech.
- 4:30— Artificial Intelligence can be valuable by finding patterns of sourcing financial fraud.
- 6:33— Why noting the differece in transactions is more useful than setting rules when spotting fraud
- 8:19— AI has its limits. AI can properly route customer service tickets to the correct person. However, it can´t navigate customer phone calls.
- 12:20—How AI is successfully being applied for loans and insurance underwriting to assess risk.
- 15:00— How we can find risk proxies to correlate risk and suss out patterns.
- 18:00— In insurance, the AI game changer will be implemented within the customer experience.
- 19:00— How the proliferation of AI will change business´s and their customer experience.
- 20:00— There are still many opportunities to implement AI like in the process of onboarding new customersI.
- 22:00— AI will complement the way we deal with customers and create sales funnels. Salesforce is just the tip of the iceburg.
- 26:20— There aren´t as many indicators for success in using AI in wealth investing as there are in banking and insurance.
- 27:08—Trying to predict trading in a way that can be implemented with AI is risky business. It would be similar to trying to predict the world.
- 29:30— Trading data is generally not all encompassing, and therefore, it is hard to implement AI in this area.
- 31:00— The AI community is full of collaboration, and in general, this is good.
- 32:00— However, AI is a big power game, and it can be worrying.
- 33:34— It is easy to get pessimistic about the evolution of AI and our species.
- 34:00—AI requires data architecture to improve performance. AI also requires IT people to collaborate with data scientists which can many times be difficult to moderate.
- 36:20— AI doens´t implement like IT
- 37:38— AI is a big cultural change for many companies
- 38:12— The hopeful transition of AI technology: Easy, Cheap, Ubiquitous
3 Key Points:
1. Artificial Intelligence is taking the main stage in many industries and has many opportunistic applications.
2. However, trying to implement AI technologies into the trading world would mean that an all encompassing data-set would need to exist or in other words, you would have to be able to predict the world.
3. Though there are several fields to implement AI to reap benefits such as customer service and insurance underwriting, implementing AI in trading is a unsurmountable task.
Tweetable Quotes:
- ¨Being able to coax out patterns of normal is one big, and certainly, fruitful application [of AI].” –Daniel.
- “AI doens´t implement like IT.” – Daniel.
- “With AI, we are talking about a probabilitic understanding of things” –Daniel.
Resources Mentioned:
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