In a recent interview at MachineCon 2023, Sravan Kasarla, the Chief Data Officer for Thrivent, a purpose-driven company offering insurance, investments, and financial advice, shared his insights on the emergence of generative AI in the financial services industry. He discussed the opportunities, risks, and regulatory aspects associated with the adoption of this technology.
The Shift to Generative AI
Kasarla began by acknowledging that generative AI is disrupting every industry, not just financial services. He noted that financial services companies have been analytically driven for a long time, with statistical modeling and machine learning playing crucial roles in pricing and risk assessment. He sees generative AI as the next step in this evolution.
Opportunities and Use Cases
Kasarla identified several “no regrets” use cases for generative AI in financial services. He sees significant potential in processes that involve risk assessment and evaluation, such as underwriting. Generative AI can provide comprehensive summaries for decision-makers, enhancing the efficiency and accuracy of these processes.
In addition, Kasarla highlighted the potential of generative AI to improve client experience. It can enable better recommendations, generate marketing content, and facilitate regulatory compliance. For instance, as an insurance company, Thrivent has to respond to insurance commissioners in all 50 states and other regulators. Generative AI can automate these tasks, improving overall productivity.
Regulatory Aspects and Governance
When asked about the regulatory elements of AI, Kasarla acknowledged that regulations have always shaped the innovation and application of technology. He believes that the governance of AI will evolve to be multi-dimensional, focusing not just on privacy and liquidity, but also on observability and responsible AI.
Kasarla sees regulations as a means to channel the energy and innovation power of generative AI for the betterment of society. He compared the emergence of AI to the advent of software, noting that disruptive technologies like these often lead to the creation of new regulations.
In conclusion, Kasarla’s insights provide a comprehensive overview of the role of generative AI in financial services. He emphasizes the potential of this technology to enhance risk assessment, improve client experience, and facilitate regulatory compliance. However, he also acknowledges the need for regulations to ensure the responsible and beneficial use of AI.
