CFP: AIFT@ ACM SAC 2027, Gwangju, South Korea

[Evan Zheng]

AI for Intelligent Financial Technologies (AIFT)

April 5-9, 2027, a track at ACM SAC 2027, Gwangju, South Korea

https://academicworkshops.github.io/AIFT/

Important Dates

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• • Paper Submission Deadline: October 2, 2026 (EST)
  • Notification of Paper Acceptance/Rejection: November 13, 2026
  • Camera-ready Copies of Accepted Papers Due: November 28, 2026
  • Author Registration Due: December 5, 2026

Introduction

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Financial technologies (FinTech) are undergoing rapid transformation driven by advances in artificial intelligence, machine learning, large language models, multi-agent systems, and data-driven decision intelligence. AI is increasingly embedded into banking, insurance, investment management, digital payments, regulatory compliance, fraud detection, financial customer services, and financial risk management. Recent developments in generative AI and agentic systems further expand the capabilities of intelligent financial services while introducing new challenges related to trustworthiness, explainability, robustness, fairness, privacy, and governance.

The goal of this track on AI for Intelligent Financial Technologies (AIFT) is to provide an interdisciplinary forum for researchers and practitioners from academia, industry, and government to present advances in AI-enabled financial technologies and intelligent financial services. The track emphasizes intelligent, trustworthy, and human-centered AI solutions for financial technologies and services, including financial analytics, decision support, compliance, fraud detection, customer intelligence, and AI-enabled financial systems.

Call For Papers

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The primary objective of this track is to facilitate the integration of AI within the area of financial technologies and services. Broadly speaking, we welcome submissions from both academia and industry to discuss their latest progress or findings in related areas.

Topics of Interest in AIFT include but are not limited to:

• Data Mining and Machine Learning Tasks (within FinTech Applications)
  • Classification, Regressions
  • Time-Series Predictions
  • Clustering
  • Association Rule Mining
  • Outlier Detection
  • Financial Optimization
  • Feature Engineering

• Generative AI, Large Language Models, and Agentic Systems for Finance
  • Generative AI and Large Language Models for Finance
  • Financial Foundation Models
  • Agentic AI and AI Agents for Financial Services
  • Retrieval-Augmented Generation (RAG) for Financial Applications
  • Synthetic Financial Data Generation
  • Multimodal Financial Intelligence
  • Financial Large Language Models (FinLLM / FinNLP)
  • Conversational Financial Systems / ChatBots for Finance

• Responsible and Trustworthy Financial AI
  • Explainability and Interpretability in Financial AI
  • Robustness and Reliability of Financial AI Systems
  • Fairness in Financial Decision Making
  • Privacy-Preserving AI for Finance
  • AI Governance, Regulation, and Compliance Analytics

• FinTech Tasks and Applications
  • Business or Financial Analysis
  • Financial Portfolio Optimization
  • Risk Management and Predictions
  • Financial News or Reports
  • Sustainability/ESG in Financial Investments
  • Scalability and Efficiency in Financial Services
  • Multilingual Challenges in Financial Services
  • Multi-Modal Financial Knowledge Discovery
  • Financial Time-Series Forecasting
  • Financial Fraud Detections
  • Customer Churn Predictions and Customer Analytics
  • Financial Information Retrieval and Recommender Systems
  • Intelligent Banking and Digital Payment Systems
  • Insurtech
  • Robo-Advisors

Submission Instructions

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Regarding the template, blind policy, page limit and submission systems, please refer to the ACM SAC 2027 website for instructions. The accepted papers will be officially published in ACM SAC proceedings.