Payment Networks

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1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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CausalLoss-Fin: Attributing Financial-Agent Loss to Decisions and Infrastructure Faults
Sep 22, 2026Abhishek SharmaStrategic Agents Payment Networks
Guixu: Valuation-Driven Data Discovery for Autonomous AI Agents with On-Chain Attestation
Aug 8, 2026Yifan Wu, Yuchen Peng, Jiaqi Chai +4Data Science Agents Autonomous Agents
Zhejiang University · The State Key Laboratory of Blockchain and Data Security; Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
SeqLLM: Augmenting LLMs with Behavioral-Sequence Modeling for High-Stakes Decisions at WeChat Pay
Aug 4, 2026Guilin Li, Jiaxing Zhang, Matthias Hwai Yong Tan +2Large Language Models(Llms Sequence Modeling
Shanghai Jiao Tong University China
Empowering Credit Risk Detection in Weixin Pay with Billion-Scale Deep Graph Learning
Aug 3, 2026Xin Liu, Xiyuan Chen, Chenglong Wu +3Graph Representation Learning Credit Risk Prediction
Tongji University Shanghai, China · Tencent Inc. Shenzhen, China
402Pilot: An x402 Decision Layer for Autonomous Agent Micropayments
Aug 2, 2026Yin Li, Yanbo He, Boo-Ho Yang +5Payment Networks Dynamic Pricing
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · MOVENSYS Inc., Seongnam-si, Republic of Korea · Schneider Electric, Shanghai, China +2
A Decision-Centered Reference Architecture for Trustworthy Agentic Commerce
Jul 20, 2026Dimitrios S. SfirisAgentic Commerce Payment Networks
AspectSoft, Xanthi, Greece
A RFID Based Campus Wide Payment System
Jul 19, 2026Miraj Uddin Chowdhury, MD Khairul Islam PrimePayment Networks
Department of Computer Science and Engineering · International Islamic University Chittagong · Chittagong
Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents
Jul 16, 2026Shiyu Ying, Xuejie Cao, Yingfan Ma +4Payment Networks Coding Agents
Ant Group
Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commerce
Jun 23, 2026Filippos Ventirozos, Matthew ShardlowAgentic Commerce Payment Networks
Manchester Metropolitan University Manchester, United Kingdom
Compliance-Scored Best-of-N Guardrail Orchestration for Multimodal Document Generation in Payments Dispute Defense
Jun 1, 2026Nataraj Agaram Sundar, Tejas MorabiaStreaming Guardrails Guardrail
eBay Inc. San Jose, CA, USA
Fraud Type Decomposition and the Observation-Mechanism Taxonomy:Class-Specific Detection Limits in Payment Networks
May 29, 2026Gaurav DhamaFraud Detection Payment Networks
Causal Label Recovery in Payment Networks
May 28, 2026Gaurav DhamaPayment Networks Detection Performance
Mastercard
The Fundamental Limits of Fraud Detection in Card Payment Networks
May 26, 2026Gaurav DhamaFraud Detection Payment Networks
Mastercard
Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report
May 25, 2026Satadru Sengupta, Tamunokorite Briggs, Ivan MyshakivskyiAi-Native Contracts
HireNimbus
iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning
May 11, 2026Kaicong Huang, Weiheng Oh, Thomas Guggisberg +1Payment Networks Automatic Identification System
Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY USA 12180. · Capital District Transportation Authority, 110 Watervliet Avenue, Albany, NY USA 12206.
The Payment Heterogeneity Index: An Integrated Unsupervised Framework for High-Volume Procurement Oversight and Decision Support
May 9, 2026Kyriakos ChristodoulidesPayment Networks Heterogeneity
Philips University, Department of Computer Science, Nicosia, Cyprus · Novel Intelligence, London, UK
Beyond Task Success: Measuring Workflow Fidelity in LLM-Based Agentic Payment Systems
May 7, 2026Donghao Huang, Joon Kiat Chua, Zhaoxia WangPayment Networks Production Agentic Systems
School of Computing and Information Systems, Singapore Management University, 80 Stamford Rd, Singapore 178902, Singapore · Research and Development, Mastercard, 4250 Fairfax Dr, Arlington, VA 22203, USA
Compliance-Aware Agentic Payments on Stablecoin Rails
Apr 30, 2026Kenneth See, Xue Wen TanPayment Networks Compliance
1Monetary Authority of Singapore · 2Infocomm Media Development Authority
Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering
Apr 13, 2026Vladimir StantchevPayment Networks Metadata
SRH University Heidelberg, Germany · PRESIDIO Group, Sofia, Bulgaria

Sep 22, 2026, cs.AIJ/K move · Enter open · S save

CausalLoss-Fin: Attributing Financial-Agent Loss to Decisions and Infrastructure Faults

Abhishek Sharma

Strategic Agents Payment Networks Infrastructure Decisions Financial Question Answering

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When an agent handling a payment exception loses money, the agent-step attribution methods this paper compares against will name one of its actions. They will do so even when a settlement message was dropped and the agent never had a chance: they intervene on agent actions and do not expose infrastructure faults as intervenable variables, so every dollar they explain is charged to a decision. We take a benchmark whose fault process is explicit and replayable, decompose each episode's realised delivery schedule into named, individually repairable messages, and intervene on both the agent's choices and the infrastructure's. A telescoping identity splits any policy's loss exactly three ways: an infrastructure effect, a policy differential against the best implementable policy, and a reference-policy residual. Two of the three can be negative, so none is a share; Shapley then divides the first into signed allocations over individual messages. One result is structural and needs no corpus: an agent-only baseline identifies no infrastructure cause, because its model contains no variable that could name one. What 545 planted episodes across 3 policies measure is the size of that consequence. It misfiles 100% of infrastructure episodes and charges $114,383.40 to the agent. Repairing what it names recovers 0.0% of the available loss; repairing a minimal sufficient set recovers 100.0%. Scoring messages one at a time is not merely imprecise: 27.8% (95% CI: 23.3--32.3%) of episodes do not decompose additively. We evaluate deterministic programmatic policies rather than language-model agents, which is what makes replay exact and which limits external validity to stochastic agents. The prevalence figures are properties of this generator, not field rates.

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