Since its inception, AI has experienced at least two major hype cycles with resulting winters of disillusionment. Although after the first “winter”, many financial firms deployed a number of successful applications, by the 1990s, AI went into its second winter of disillusionment as realization set in that these systems were harder and more costly to build and maintain than first anticipated. AI appears to be entering a new phase where interest is surging again. An example of this is the sharp increase in the commercial use of AI, also known as machine intelligence, such as IBM’s Watson. As another indicator, the vast majority of respondents to the 2014 Future of the Internet study anticipate that robotics and machine intelligence will permeate wide segments of daily life by 2025 with huge implications for a range of industries. Will the latest surge of AI applications in the financial services fall short again or will they this time truly transform the financial services industry?
Users are increasingly exposed to customized context-sensitive information and advice derived by systems that collect and analyze users’ past actions, often with the users not aware of this happening. The implications for the financial sector is that by tracking users’ habits, activities, and behavioral characteristics, financial data and products can be personalized to meet and anticipate each user’s unique and changing needs. This makes it practical for each user to have his/her own digital personal financial assistant in the following venues.
Because of the increased customized automation, the financial institution can offer more personalized services in near real-time at lower costs. We already are starting to see a number of successful new applications that provide hints as to where the industry may be heading. Consider the following examples of applications that are being developed and deployed:
Data-driven management decisions at lower cost could lead to a new style of management, where future banking and insurance leaders will ask the right questions to machines, rather than to human experts, which will analyze the data to come up with the recommended decisions that leaders and their subordinates will use and motivate their workforce to execute.21
AI tools which learn and monitor users’ behavioral patterns to identify anomalies and warning signs of fraud attempts and occurrences, along with collection of evidence necessary for conviction are also becoming more commonplace in fighting crime.
As businesses begin to rely more on data-driven AI applications, these new applications lead to new business issues, security, and privacy concerns, including:
Most likely all of the above will be qualities that will determine which financial institutions’ products and services will prevail in the marketplace.
Another concern for financial institutions is how regulators will respond and supplement guidance on use of AI. Federal financial regulators have issued extensive supervisory guidance on use of information technology generally and security, privacy, vendor management, and resiliency specifically which require financial institutions to assess the risk and develop adequate controls. As the number of AI applications increases, regulators are likely to focus more on the use of AI and identify deficiencies in controls.
Because of the significant potential benefits, there is probably no turning back, there will be increasing automation of financial services, often employing AI technology. However, these new AI applications introduce a number of business, security, and privacy issues that will have to be addressed if they are to succeed in the marketplace. It will be important to ensure that these intelligent applications are developed in a way that they will provide the desired benefit and that the user can trust the advice and services provided. It will be important to be able to detect and isolate infected or malicious AI programs immediately, and develop effective policies and laws for governing their development and use so that personal information is safeguarded and not misused. This includes technology and policy with respect to what constitutes liability, how to best audit these systems, and how to design and control AI systems for human safety.
3AI is India’s largest platform for AI & Analytics leaders, professionals & aspirants and a confluence of leading and marquee AI & Analytics leaders, experts, influencers & practitioners on one platform.
3AI platform enables leaders to engage with students and working professionals with 1:1 mentorship for competency augmentation and career enhancement opportunities through guided learning, contextualized interventions, focused knowledge sessions & conclaves, internship & placement assistance in AI & Analytics sphere.
3AI works closely with several academic institutions, enterprises, learning academies, startups, industry consortia to accelerate the growth of AI & Analytics industry and provide comprehensive suite of engage, learn & scale engagements and interventions to our members. 3AI platform have 16000+ active members from students & working professionals community, 500+ AI & Analytics thought leaders & mentors and an active outreach & engagement with 430+ enterprises & 125+ academic institutions.