arXiv:2608. 02664v1 Announce Type: cross Abstract: Deploying ML models in regulated decision-making (credit underwriting, fraud detection, loan approval) requires demonstrating fairness and robustness to auditors without exposing model weights or customer data.
By Mohammad Nasir Uddin, Rahnuma Tabassum Orpita, Eklachur Rahman Bhuiyan, Asaduzzaman Anik
PixSim is an open‑source simulator that models Brazil’s Pix instant‑payment system, incorporating irreversible settlement, a regulated recovery mechanism (MED), downstream fund dispersal, and capacity‑constrained analyst review. Calibrated to Banco Central do Brasil data, the model reproduces the 2025 recovery rate within 0.006 and its decomposition within 0.02, and projects future performance under various policy scenarios. Benchmark tests show how staffing levels, alert expiry rules, and scorer quality affect recovery outcomes and false‑block harm.
By Bashir Zeimarani, Alireza Khatib, Somayeh Mousavinasr, Carlos Maur\'icio Serodio Figueiredo
The paper introduces PACE (Policy‑Attested Contract Execution), a framework that sits between large‑language‑model (LLM) based autonomous AI agents and on‑chain DeFi operations. PACE defines typed transaction intents, a deterministic policy verifier, and signed Policy Decision Records (PDRs) that cryptographically bind an approved intent, policy, and simulation report to the exact on‑chain execution bytes, providing replay and expiration protection. In evaluations across 40 tasks and six baselines, PACE achieves zero unsafe executions and zero false positives, outperforming unguarded agents by a large margin.
By Rabimba Karanjai (Larry), Yang Lu (Larry), Richard Williamson (Larry), Hemanth Hm (Larry), Prakhar Mehrotra (Larry), Lei Xu (Larry), Weidong (Larry), Shi
arXiv:2610.08869v1 Announce Type: cross
Abstract: Regulated credit scoring requires scores monotone non-decreasing in every exposure input. Deployed pipelines -- hand-crafted monotone aggregates feed...
By Yew Lee Tan
TokenBank is a financial infrastructure that uses structured contracts to manage the financial relationship between AI service operators and their users. The contracts cover service‑consumption rights, cash settlements for API‑price differences, financing based on future revenue, and protection claims for specified service failures. Evaluation on nearly 900,000 API requests shows that forwards can reduce average expenditure while increasing variability, and that financing can yield positive contributions under certain capital conditions.
By Cary Chang, Jialin Zhou
arXiv:2608. 09025v1 Announce Type: new Abstract: Financial agents can turn correct context into an unauthorized effect: a customer-facing commitment, trade, or deployed policy.
By Rui Tang, Qiangqiang Liu, Yichi Zhang, Youwei Wang, Xi Chen, Chen Dong