The financial sector is a complex ecosystem where data flows in myriad forms, from structured tabular datasets to intricate time series and dynamic click streams. These diverse data formats capture everything from customer transactions and behaviors to market trends and risk factors. With the advent of multimodal machine learning techniques, the fusion of signals from conventional tabular datasets, time series, free-text articles, earnings reports, images, and networks, has de-siloed decision-making to an unprecedented degree. This deluge of actionable information combined with easily available high-performance commodity computing resources has significantly lowered the landscape in the industry.

This workshop aims to explore the intersection of Generative AI with the rich tapestry of financial data types, seeking to uncover new methodologies and techniques to enhance predictive analytics, fraud detection, and customer insights across the sector. We aim to bridge the gap between the dominance of traditional models for tabular data analysis and the emerging potential of Generative AI to revolutionize the treatment of time series, click streams, and other unstructured data forms. The workshop will continue to serve as a platform for discussing how AI can be leveraged to provide comprehensive insights into customer behavior, market dynamics, and risk assessment, transcending the limitations of current models.

The purpose of this workshop is to bring together researchers and practitioners to discuss both the problems faced by the financial industry and potential solutions. We invite regular papers, positional papers, and extended abstracts of work in progress. We also encourage short papers from financial industry practitioners that introduce domain-specific problems and challenges to academic researchers. This event will be the eighth in a sequence of finance-related workshops we have organized at KDD. The first workshop was held at KDD 2017, the second workshop at KDD 2019, the third workshop at KDD 2020, the fourth workshop at KDD 2021, the fifth workshop at KDD 2022, the sixth at KDD 2023, and the seventh at KDD 2024.

We invite papers on machine learning and AI with applications to the financial industry. Topics of interest include, but are not limited to, the following:

* Understanding and predicting customer behavior
- Recommendations
- Detecting anomalies at large in unsupervised/semi-supervised settings
- Active learning strategies in noisy and uncertain environments.
- Reinforcement learning strategies and their applications to gather ground truth
- Model calibration, stability, and adaptiveness trade-offs
- Insider trading
- Fraud and abuse
- Cyber threats
- Money Laundering
- Compliance violations
- Agentic AI for Personalized Experiences and Intelligent Decision-Making
- Mining for signals in financial data
- Vetting and sourcing data for high-stakes decision-making
- Tabular transformer techniques
- Transfer learning, Time Series, Recommendation Systems, Reinforcement Learning, Network Science, Image Processing etc
- Patterns and anti-patterns in early-detection
- Multi-modal machine learning in practice
- Sensor fusion approaches in the use of alternative data
- Use cases like marketing, anomaly detection, churn prevention, etc.

* Model Safety, Explainability & Governance
- Defense against GenAI attacks and abuse
- Role of explainability in several verticals, markets
- Deployed and vetted applications with explainability and reasoning
- Guard-rails for GenAI

* Fairness
- Fairness in the context of finance - lending and beyond!
- Privacy preservation
- Reassessing credit in the conventional sense
- Role of DeFi in fairness

* Market Manipulation
- Analysis of limit order book feeds
- Fake news and other noisy social signal ingestion challenges
- Robustness to adversarial actors

* Crypto and DeFi
- Specific challenges and analysis of high-risk domains
- Best practices to thwart bad actors and stay compliant with an in-flux regulatory landscape

* Synthetic Data
- Evaluation
- Privacy protection

We also invite tutorials and introductory papers to bridge the gap between academia and the financial industry:

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Overview of Industry Challenges
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● Short papers from financial industry practitioners that introduce domain specific problems and challenges to academic researchers. These papers should describe problems that can inspire new research directions in academia, and should serve to bridge the information gap between academia and the financial industry.

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Algorithmic Tutorials
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● Short tutorials from academic researchers that explain current solutions to challenges related to the technical areas mentioned above, not necessarily limited to the financial domain. These tutorials will serve as an introduction and enable financial industry practitioners to employ/adapt the latest academic research to their use cases.

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Submission Guidelines
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All submissions must be PDFs formatted in the Standard ACM Conference Proceedings Template. Submissions are limited to 8 content pages or less, including all figures, tables, and appendices but excluding references. All accepted papers will be presented as posters and some would be selected for oral presentations, depending on schedule constraints. Accepted papers will be posted on the workshop website.

Following the KDD conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed.

Papers should be submitted on the submission portal by May 8, 2025, 11:59 PM Pacific Time.

Paper Submission at https://cmt3.research.microsoft.com/KDDMLF2025