FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations

arXiv:2506.11635 · cs.CR, cs.AI · Submitted 2025-06-13 · Read on arXiv

cs.CR, cs.AI

Submitted: 2025-06-13

Updated: 2026-08-29

Code: https://github.com/namebrandon/Sparkov

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 9× in this paper · explained in 1 episode
• Explainability — 8× in this paper · explained in 3 episodes
• F1 Score — 8× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Ensemble Learning — 6× in this paper · explained in 2 episodes
• Alert Fatigue — 4× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Feature Engineering — 3× in this paper · explained in 3 episodes
• Prompt Engineering — 3× in this paper · explained in 4 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Heterogeneous Graph — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Concept Drift — 1× in this paper · explained in 4 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fraud Investigation Assistant — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• Cyber Sentinel: Exploring Conversational Agents in Streamlining Security Tasks with GPT-4
• Unleashing the potential of prompt engineering for large language models
• Elephants Never Forget: Testing Language Models for Memorization of Tabular Data
• Towards Optimizing the Costs of LLM Usage
• Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
• RouteLLM: Learning to Route LLMs with Preference Data

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