{"ID":2857820,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.07645","arxiv_id":"2510.07645","title":"Banking Done Right: Redefining Retail Banking with Language-Centric AI","abstract":"This paper presents Ryt AI, an LLM-native agentic framework that powers Ryt Bank to enable customers to execute core financial transactions through natural language conversation. This represents the first global regulator-approved deployment worldwide where conversational AI functions as the primary banking interface, in contrast to prior assistants that have been limited to advisory or support roles. Built entirely in-house, Ryt AI is powered by ILMU, a closed-source LLM developed internally, and replaces rigid multi-screen workflows with a single dialogue orchestrated by four LLM-powered agents (Guardrails, Intent, Payment, and FAQ). Each agent attaches a task-specific LoRA adapter to ILMU, which is hosted within the bank's infrastructure to ensure consistent behavior with minimal overhead. Deterministic guardrails, human-in-the-loop confirmation, and a stateless audit architecture provide defense-in-depth for security and compliance. The result is Banking Done Right: demonstrating that regulator-approved natural-language interfaces can reliably support core financial operations under strict governance.","short_abstract":"This paper presents Ryt AI, an LLM-native agentic framework that powers Ryt Bank to enable customers to execute core financial transactions through natural language conversation. This represents the first global regulator-approved deployment worldwide where conversational AI functions as the primary banking interface,...","url_abs":"https://arxiv.org/abs/2510.07645","url_pdf":"https://arxiv.org/pdf/2510.07645v1","authors":"[\"Xin Jie Chua\",\"Jeraelyn Ming Li Tan\",\"Jia Xuan Tan\",\"Soon Chang Poh\",\"Yi Xian Goh\",\"Debbie Hui Tian Choong\",\"Chee Mun Foong\",\"Sze Jue Yang\",\"Chee Seng Chan\"]","published":"2025-10-09T00:35:08Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.AI\"]","methods":"[\"Large Language Model\",\"LoRA\"]","has_code":false}