KDD Workshop on Machine Learning in Finance

Call for Papers

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:

• Mining for signals in financial data

  • Vetting and sourcing data for high-stakes decision making

  • Transfer learning from 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

  • Generating synthetic data for privacy preservation, data sharing, robustness, etc

• Detecting bad actors and activity in financial data

  • 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

• Model Explainability & Governance

  • Role of explainability in several verticals, markets

  • Deployed and vetted applications with explainability

• 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

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

Overview of Industry Challenges

• 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.

Algorithmic Tutorials

• 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 latest academic research to their use-cases.

Submission Guidelines

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 and tables 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 26th June 1st, 2022 11:59 PM Pacific Time

https://easychair.org/my/conference?conf=kddmlf2022

Key Dates

• Submission Deadline: May 26, 2022 11:59 Pacific Time June 1, 2022 11:59 Pacific Time

• Author Notification: June 20, 2022 June 27, 2022

• Camera ready papers due:

• Workshop: August 15, 2022