%0 Journal Article
%T Stacy: A Voice AI Agent Conducting Risk Assessment for Small Business Insurance
%A Muhammad Imran Sajid
%J Open Journal of Applied Sciences
%P 834-853
%@ 2165-3925
%D 2025
%I Scientific Research Publishing
%R 10.4236/ojapps.2025.154056
%X At present small business insurance operates with outdated analog methods for underwriting operations. The paper introduces Stacy which represents a groundbreaking voice AI agent for transforming insurance risk evaluation procedures. The consultation approach adopted by Stacy replaces tedious paperwork with spoken interviews which produce vital risk data from business owners in their normal dialogue. The integrated solution derived from Trillet AI conversation abilities and Make.com workflow management and data storage functions behaves similarly to expert underwriter systems. Stacy goes beyond question-asking because she pays attention to conversations while tailoring her questions according to business types and previous responses to perform immediate risk evaluations. Standard underwriting assessments occur after calls through system processing that classifies risks to produce automated decisions without needing human involvement. The results from testing indicate that the combination of time reduction in processes and better risk assessment quality alongside higher customer satisfaction is achieved. The implementation of Stacy advances insurance operations toward their most intelligent expression. Future versions of the system may possibly apply predictive risk modeling techniques alongside automation of regulatory requirements and cultural adaptation features to turn human-dependent underwriting processes into data-generated and data-aware scientific decision-making. Voice AI systems show evidence that they transform insurance operations beyond basic automation to a complete redefinition of insurance processes.
%K Agentic AI
%K Voice AI
%K Insurance Underwriting
%K Risk Assessment
%K Large Language Models
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=141691