Etiqa Insurance scales generative AI across customer and staff workflows

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Etiqa Insurance scales generative AI across customer and staff workflows

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Etiqa Insurance Singapore, part of the Maybank regional financial group, has scaled generative AI across both customer-facing and internal operations, growing chatbot usage 1,233% (from 300 to 4,000 monthly threads in one year) and achieving 44% autonomous query resolution on its customer service channels. "Over the past year and a half, Etiqa's AI strategy has evolved, shifting from traditional machine learning and intent-based systems towards generative AI systems designed for real-time, natural language engagement," said Dennis Liu, Chief Technology Officer at Etiqa International Holdings. The shift marks a deliberate departure from earlier RASA-based bots limited to predefined conversation flows. Etiqa has trained generative AI on proprietary knowledge bases and historical customer interactions, enabling contextually aware, personalised conversations. The RASA foundation already reduced live chat escalations and built the operational and data infrastructure necessary for advanced AI adoption. Etiqa's earlier operational wins validated AI's potential while exposing the limits of task-specific tools. The E-CLEVA video-assisted claims service reduced vehicle damage assessment and approval time by up to 80%, through real-time interaction between claimants and surveyors. The company also automated travel delay claims using AI-powered straight-through processing (STP) and integrations with PayNow and MyInfo, enabling instant approvals. Looking ahead, Etiqa has two generative AI chatbots planned for 2025: a customer-facing chatbot designed to improve query resolution rates and reduce human handoffs, and an internal GenAI assistant to empower sales advisors, enhance product training, and streamline needs analysis. The next-generation GenAI chatbot is projected to increase autonomous resolution rates by over 40%, freeing customer service teams to focus on complex queries. The team is also piloting Vision LLMs to automate claims document reviews, with projected reductions in processing time of up to 50%. Etiqa tackled three challenges during AI transformation: adopting a digital-first mindset across the organisation ("think big, start smart, fail fast, learn fast"), progressively replacing legacy systems tied to core operations, and addressing AI talent shortage through training, graduate onboarding, and hiring data scientists and AI ops engineers. As deployments expanded, Etiqa introduced governance frameworks to ensure compliance, scalability, and long-term sustainability, with quality monitoring based on usage and post-interaction customer feedback. Source: iTnews Asia, 2025