Financial Decision-Making

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Financial decision-making examines how individuals, firms, and computational systems make choices about investments, budgets, lending, and advice when outcomes are uncertain, delayed, and consequential. Approaches include statistical and machine-learning forecasts, portfolio optimization, reinforcement and inverse reinforcement learning, and language-model agents using retrieval, memory, or constrained generation. Researchers evaluate decisions with market returns and risk measures, simulated long-horizon tasks, point-in-time financial data, causal analyses, and studies of how people interpret and respond to advice. A central challenge is that strong predictions or fluent explanations do not ensure robust, well-grounded decisions, while personalization, changing market conditions, and limited outcome-based evidence complicate safety and evaluation.

Latest papers

38 papers1 paper in the last four weeks, down 80% on the four weeks before. 0.0% of all new papers.

S $^2$ -MAS: A Society-Scale Multi-Agent Simulation Framework with 500 Million Household Persona Agents
Oct 20, 2026Yang Li, Yike Wang, Di Wan +18Agent-Based Modeling Human Behavior Simulation
The University of Hong Kong · Faculty of Business and Economics, The University of Hong Kong · HKU Business School Shenzhen Research Institutes, The University of Hong Kong +6
Agent Memory with Episodic Retrieval for Financial Decision-Making
Sep 23, 2026Nuoyue Xu, Jiang Liu, Wenxuan Huang +3Multi-Agent LLM Systems LLM Agent Memory
University of British Columbia · University of Science and Technology of China · Fudan University +1
Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Making
Sep 21, 2026Hasibur Rahman, Benjamin R. Cowan, Smit DesaiAI-Assisted Decision Making Human-AI Decision Making
Northeastern University, Boston, Massachusetts, USA · University College Dublin, Dublin, Ireland
Trustworthy FinAInce: Unpacking How AI-Mediated Financial Advice is Judged
Sep 17, 2026Aryan Ramchandra Kapadia, Eshwar Chandrasekharan, Koustuv SahaTrust in AI Human-AI Decision Making
University of Illinois Urbana-Champaign, Urbana, IL, USA
Are LLMs Good Financial User Simulators? Multi-view Investor Logic Alignment (MILA)
Sep 14, 2026Jiajie He, Jiangyuan Hong, Xintong Chen +2LLM Evaluation Human Behavior Simulation
1Hithink Research
The Analyst in the Prompt: Role, Retrieval, and Memory Biases in LLM Financial Analysis
Sep 2, 2026Ahmed Asaad, Amr Mohamed, Yang Zhang +1LLM Evaluation LLM Auditing
Durham University Business School · MBZUAI & Ecole Polytechnique · Ecole Polytechnique +1
Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron
Aug 24, 2026Sahong Park, Suhwan Park, Hoyoung Lee +8LLM Decision-Making Financial Decision-Making
Hankuk University of Foreign Studies Yongin, Republic of Korea · UNIST Ulsan, Republic of Korea · LG AI Research Seoul, Republic of Korea +4
GRPO for Financial Advice Generation: Outperforming Commercial LLMs under CATE Evaluation
Aug 12, 2026Ofir Ben Shoham, Shrutendra Harsola, Vignesh Subrahmaniam +3AI-Assisted Decision Making LLM-as-a-Judge
Intuit
Financial Numerical Prediction and Allocation as Token Generation
Aug 10, 2026Xu Ouyang, Moontae LeeQuantitative Finance Financial Forecasting
University of Illinois Chicago
Observational Policy Ranking for SMB Financial Guidance from Multi-Action Accounting Logs
Aug 10, 2026Shrutendra Harsola, Vignesh Subrahmaniam, Vikas Raturi +7Causal Effect Estimation Conditional Average Treatment Effect Estimation
1Foresight-AI, Intuit
How Simple Can It Get? From Interpretable Equations to Readable Rules for Financial Decision Making
Aug 10, 2026Adia Lumadjeng, Ilker Birbil, Erman AcarRule-Based Classification Interpretable ML
University of Amsterdam Amsterdam, the Netherlands
How People Evaluate AI-, Expert-, and Peer-Style Financial Advice
Aug 10, 2026Aryan Ramchandra Kapadia, Eshwar Chandrasekharan, Koustuv SahaHuman-AI Interaction Human-AI Decision Making
University of Illinois Urbana-Champaign, USA
Evaluating Investment Logic in Large Language Models: A Real-World Benchmark Towards Personalzied Financial Agents
Aug 6, 2026Yuanhong Jiang, Jingjie Zou, Zhenghong Lin +4Financial Decision-Making Financial Reasoning in Language Models
An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals
Aug 5, 2026Ramin PishehvarReinforcement Learning Portfolio Optimization
From Information to Delegation: Mapping Human-AI Financial Decision Making
Aug 3, 2026Iman Munire Bilal, Yingcan Carol Wang, Ajan Raj +5AI-Assisted Decision Making LLM Decision-Making
Stripe Partners · Stripe Partners, Imperial College
ShiJianBench: From Dialogue to Decision for Long-Horizon Evaluation of Investment Advisors
Aug 2, 2026Jie Gong, Maowei Jiang, Zhiwei Liu +14Financial Services Long-Horizon Agent Evaluation
School of Artificial Intelligence, Wuhan University · Nanjing Audit University · The University of Manchester +3
A Persona-based Rate Action Index
Jul 29, 2026Hayden Helm, Andrew DassoriPersonality Modeling in Language Models Time Series Forecasting
Helivan · Wavelength Capital
Fund2Persona: A Framework for Building and Refining Financial Advisor Personas from Fund Disclosure Data
Jun 29, 2026Suhwan Park, Hoyoung Lee, Zhangyang Wang +5Financial Services LLM Personalization
UNIST · LinqAlpha · University of Texas at Austin +3
When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis
Jun 28, 2026Hoyoung Lee, Suhwan Park, Seunghan Lee +15LLM Compression LLM Auditing
UNIST · LinqAlpha · LG AI Research +9
InvestPhilBench: A Multi-Layer Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy
Jun 24, 2026Mingguang Chen, Bo QuLLM Evaluation Finance
University of California, Riverside (UCR). · 2Illinois Institute of Technology (IIT).
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios
Jun 23, 2026Patara Trirat, Jin Myung Kwak, Jay Heo +2Financial Decision-Making Financial Forecasting
KAIST
Interpretable Factor Decomposition for Decision Intelligence in Large-Scale Financial Markets: Evidence from China's A-Share Market
Jun 11, 2026Xiao Han, Yao Xiao, Zhen Zhang +1Quantitative Finance Interpretable ML
Goizueta Business School Emory University Atlanta, GA, USA · College of Computing Georgia Institute of Technology Atlanta, GA, USA · School of Data Science University of Pennsylvania Philadelphia, PA, USA +1
DFAH-Bench: What Agreement Leaves Unmeasured in Financial Agents
Jun 10, 2026Raffi KhatchadourianAgent Evaluation AI Agent Benchmarks
IBM Financial Services Market New York, NY, USA
Dynamic Objective Selection with Safeguards and LLM Oversight for Financial Decision-Making
Jun 2, 2026Keigo Sakurai, Takahiro Ogawa, Miki Haseyama +2Quantitative Finance Sequential Decision Making
Hokkaido University · Nomura Asset Management Co., Ltd. · Kobe University +1
Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation
Jun 1, 2026Wenbin WuLLM Auditing LLM Decision-Making
Cambridge Centre for Alternative Finance, University of Cambridge
Point-in-Time Financial RAG with Frozen LLMs and Market-Feedback Adaptive Retrieval
May 29, 2026Zijie Zhao, Roy E. WelschRetrieval-Augmented Generation Quantitative Finance
Massachusetts Institute of Technology · Cambridge, MA, USA
FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations
May 27, 2026Xuesi Hu, Peng Wang, Jinpeng Miao +7LLM Evaluation Financial Reasoning Benchmarks
School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China · School of Economics, Anhui University, Anhui, China · SKLPlanets, Macau University of Science and Technology, Macau, China +2
Mechanical Enforcement for LLM Governance:Evidence of Governance-Task Decoupling in Financial Decision Systems
May 14, 2026José Manuel de la Chica Rodríguez, Carlos Martí-GonzálezLLM Auditing LLM Safety
1Santander AI Lab, Grupo Santander
Herculean: An Agentic Benchmark for Financial Intelligence
May 14, 2026Xueqing Peng, Zhuohan Xie, Yupeng Cao +60AI Agent Benchmarks LLM Agent Evaluation
FIND: Toward Multimodal Financial Reasoning and Question Answering for Indic Languages
May 13, 2026Sarmistha Das, Vaibhav Vishal, Syed Ibrahim Ahmad +2Financial Services Financial QA
Indian Institute of Technology Patna, India · Microsoft, India

Oct 20, 2026J/K move · Enter open · S save

S $^2$ -MAS: A Society-Scale Multi-Agent Simulation Framework with 500 Million Household Persona Agents

Yang Li, Yike Wang, Di Wan, Chujun He+17

The University of Hong Kong · Faculty of Business and Economics, The University of Hong Kong · HKU Business School Shenzhen Research Institutes, The University of Hong Kong+6

Agent-Based Modeling Human Behavior Simulation Large Language Model-Based Social Simulation Financial Decision-Making

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Simulating economic responses at society scale requires agents whose decisions reflect household circumstances. We introduce S

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-MAS, a society-scale multi-agent simulation framework built on 500 million synthetic household personas grounded in real-survey data. Its Genese engine separates decisions from state updates, while reusable financial scenarios and application ledgers track consumption, cash, debt and payments. Trained with SFT + RLCD on 2.93 million examples, sharp-421m-mlx achieves 74.55% accuracy and 38.37% question-macro F1 on one-shot consumer financial-choice tasks derived from held-out survey responses. Its accuracy exceeds GLM-5.3-Flash, Jev 1.13, DeepSeek-V4.1-Flash, GPT-6-Luna and GPT-6-Astra in the common benchmark (full test for the first four; matched 500-group sample for Astra). We evaluate eight financial task families and simulate 12 million distinct household agents in paired purchase-funding conditions. Jointly raising purchase goals and approved credit limits increases consumption, with responses differing across age and income groups. Education, employment and household-size differences persist after age-income standardization and mainly reflect transitions from deferral to purchase. Asset and debt groups differ in cash drawdown, repayment and closing debt. S

^2

-MAS links heterogeneous household decisions to evolving consumption, cash and repayment paths, supporting economic experiments across household groups and population scales.