arXiv AI
Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech
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arXiv AI
Jul 3
Artificial Intelligence-Enabled Accounting Information Systems and Fraud Detection in Nigeria's Financial Services Sector: The Moderating Role of Natural Language Processing
arXiv:2607. 01257v1 Announce Type: cross Abstract: The rapid digitalisation of financial systems has improved operational efficiency and financial inclusion while simultaneously increasing exposure to sophisticated forms of cyber-enabled fraud and electronic financial misconduct.
arXiv AI
Jun 19
FFinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming
arXiv:2606. 19887v1 Announce Type: cross Abstract: Existing safety benchmarks target general adversarial scenarios but miss finance-specific risks.
arXiv AI
Sep 18
Governance-as-Code: Translating EU AI Act Technical Requirements into Executable Compliance Pipelines for Generative AI Systems
The paper introduces Governance-as-Code (GaC), a framework that translates the EU AI Act’s technical requirements into 43 machine‑checkable acceptance criteria across six compliance modules. GaC runs within a CI/CD pipeline, producing Article‑indexed audit evidence and providing actual Rego policy code. The authors validate GaC on two enterprise deployments, showing it reproduces manual audit findings—including three penalty‑triggering violations—while reducing audit labor by about 75%.
arXiv AI
Sep 2
Incremental Risk Assessment of Progressive Elder Financial Scams via Instruction-Tuned Small Language Models
The paper presents a cumulative turn‑based risk assessment framework for detecting financial scams targeting older adults, which aggregates conversational turns and updates risk estimates at each step. A multi‑turn dialogue dataset covering investment, charity, and tech support scams is created, with annotations for risk level, score, rationale, and safety recommendation at every cumulative stage. Four small language models (Phi‑4, LLaMA‑3.2, DeepSeek‑R1, Qwen3) are fine‑tuned; Phi‑4 and LLaMA‑3.2 outperform others in turn‑aware risk estimation, demonstrating that compact models can effectively support incremental scam detection in resource‑constrained, privacy‑aware deployments.
Hugging Face Trending Papers
Jul 12
Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows
LLMs are now proposed for fraud detection, scam investigation, content moderation, and other trust-and-safety workflows. Much of the public literature still evaluates them as models, with less attention to their behavior as components in operational pipelines.
arXiv Machine Learning
Jul 14
ERP Data Provisioning Financial Control Testing
arXiv:2607. 09712v1 Announce Type: new Abstract: Financial control testing increasingly depends on representative enterprise resource planning (ERP) data in quality environments, yet direct production copies expose personal, supplier, banking, and commercially sensitive records.