Sage Wohns, CEO at Agolo"In one word: automation. Financial firms will begin automating more complicated and high value processes. We've seen success in automating the back office functions, which focused on efficiency and costs. Learnings will now proceed up the value chain to internal functions like research and communications to result in better customer experiences and enable strategic decision making."
Evan Schnidman, CEO and Co-Founder at Prattle"2017 will see AI, and more specifically, machine learning, continue to propagate at asset managers and investment banks. This will increasingly take the form of traditional analysts being replaced by hybrid financial/quantitative professionals with a broader range of technology experience.
These “quantamental” analysts will leverage data and AI solutions to become more efficient, thereby conducting better research at lower costs. This is vitally important across capital markets as shrinking margins continue to collide with a financial world awash in large amounts of data that humans simply can’t break down without technology solutions.
In particular, the MiFID II regulatory framework across Europe looks to be forcing investment banks to cut costs and improve research quality, meaning technological solutions like AI-guided research are vital. Just as hedge funds began to adopt AI in 2015-2016, other asset managers and investment banks will follow suit through 2017 and beyond."
Rahul Mewawalla, CEO at Zenplace“2017 will be an exciting year as financial institutions look at how AI and machine learning can enable banks to become more competitive in other industries like real estate which are a focus area for banks and insurance companies.
Priority fintech sectors such as the $55 billion property management industry are using AI and machine learning to increase returns, lower costs and improve the overall owner and tenant experience for the 50 million rental properties and 100 million tenants in the U.S. Ecosystem players like mortgage bankers, payments, P&C insurers, private banking and wealth management are now working together with technology-led property management companies to better serve their clients."
Ian Foley, CEO & Founder at AcuteIQ“2017 will see more banks start to tap into their data for machine learning. Initially, banks will experiment on using machine learning to improve their business operations (e.g. credit analysis, customer acquisition), but will be hesitant to build consumer-facing applications (e.g. customer service bots) due to concerns about performance and reputation risk.
New entrant fintech firms will be the prime movers in applying machine learning to consumer-facing applications. By the end of 2017, we will start to see consolidation among many of the new entrant fintech firms, with their single purpose products fitting into a couple of broader banking platforms.”
Ramesh Mahalingam, CEO and Founder at Vizru"AI driven workflows will be the only way for traditional banks to leapfrog the competition from new, nimble breed of banks built around innovative technology such as Blockchain and business models such as peer-to-peer payments.
The emerging new shareconomy demands banks to reassess their role where products and services need to be increasingly personalized and real-time, that can only be delivered by AI-driven digital ecosystem that can dynamically and continuously learn, reason and solve problems in real-time. Furthermore, AI driven workflows will play an instrumental role for banks in the future to deliver immersive customer experience."