Jeraelyn Ming Li Tan
2025
Banking Done Right: Redefining Retail Banking with Language-Centric AI
Xin Jie Chua
|
Jeraelyn Ming Li Tan
|
Jia Xuan Tan
|
Soon Chang Poh
|
Yi Xian Goh
|
Debbie Hui Tian Choong
|
Foong Chee Mun
|
Sze Jue Yang
|
Chee Seng Chan
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track
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.
2024
MalayMMLU: A Multitask Benchmark for the Low-Resource Malay Language
Soon Chang Poh
|
Sze Jue Yang
|
Jeraelyn Ming Li Tan
|
Lawrence Leroy Tze Yao Chieng
|
Jia Xuan Tan
|
Zhenyu Yu
|
Foong Chee Mun
|
Chee Seng Chan
Findings of the Association for Computational Linguistics: EMNLP 2024
Search
Fix author
Co-authors
- Chee Seng Chan 2
- Foong Chee Mun 2
- Soon Chang Poh 2
- Jia Xuan Tan 2
- Sze Jue Yang 2
- show all...