mlsanityData to 14 Oct 2026

Banking Done Right: Redefining Retail Banking with Language-Centric AI

arXiv 2510.07645 ↗First posted 9 Oct 2025cs.CL cs.AIcited by 1

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 14 of its 41 references that are in the map. First posted on arXiv 9 Oct 2025.

Builds on

14 of 41 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024TradingAgents: Multi-Agents LLM Financial Trading Framework28 Dec
  2. 2024Large Language Model Agent in Financial Trading: A Survey26 Jul

Other references · 12

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  3. 2024Understanding the planning of LLM agents: A surveycited by 421
  4. 2023Large Language Models in Finance: A Surveycited by 226
  5. 2023Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attackscited by 194
  6. 2024Revolutionizing Finance with LLMs: An Overview of Applications and Insightscited by 90
  7. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunitiescited by 83
  8. 2025Advanced Real-Time Fraud Detection Using RAG-Based LLMscited by 7
  9. 2024Opportunities and Challenges of Generative-AI in Financecited by 6
  10. 2025Responsible Innovation: A Strategic Framework for Financial LLM Integrationcited by 2
  11. 2015"`They brought in the horrible key ring thing!" Analysing the Usability of Two-Factor Authentication in UK Online Bankingcited by 1
  12. 2025Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulationcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026Helping Customers in Distress: An LLM-powered Agent that Converses, Probes, and Routes
  2. 2024FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models
  3. 2026FiMI Banking: A Sovereign Model for Indian Retail Banking
  4. 2026BankMathBench: A Benchmark for Numerical Reasoning in Banking Scenarios
  5. 2025Fin-Ally: Pioneering the Development of an Advanced, Commonsense-Embedded Conversational AI for Money Matters
  6. 2026FraudBench: Stress-Testing Policy-Grounded Banking Agents Against Adaptive Fraud
  7. 2025VERAFI: Verified Agentic Financial Intelligence through Neurosymbolic Policy Generation
  8. 2026FinToolBench: Evaluating LLM Agents for Real-World Financial Tool Use