Co-located with SIGMOD/PODS 2026

FinDS: Workshop on Data Management for the Modern Financial Systems

This workshop provides a dedicated venue for research that addresses the holistic challenge of building end-to-end financial data systems, where security, privacy, realtime performance, and data quality are deeply co-designed system properties.

May 31, 2026 • Bengaluru, India
Sheraton Grand Bengaluru Whitefield • Room : Petunia

Topics of Interest

Topics of interest include but are not limited to the following...

Analytics For Financial Data

  • • Financial knowledge modeling: Modeling the evolving financial data to trace money laundering, model systemic risk, and perform causal analysis.
  • • (Near) Real-time Fraud Detection: Problems such as real-time subgraph matching in high-velocity streams. Eg:- capturing sophisticated fraud-rings.
  • • Graph-RAG: Addressing the core data management challenges of moving beyond simple vector retrieval to enable multi-hop logical reasoning over financial knowledge graphs.

Storage and Processing

  • • Foundational Storage: Efficient storage while ensuring durability, security & encryption, fast access, and the use of distributed file systems, cloud-based data lakes, and scalable database architectures.
  • • Optimized Processing: Parallel processing, In-memory computation, optimized query engines to handle workloads and keep latency in check. Real-time Anomaly detection for streaming data.

Agent-based Economic Systems

  • • Agentic AI Infrastructure: Scalable Management systems for millions of autonomous payment agents.
  • • Algorithmic Governance: Designing data-centric systems for creating the "black box recorder" for financial AI, essential for dispute resolution, regulatory audits etc.
  • • Dynamic Knowledge Graphs: Representing agent capabilities and beliefs in real-time, enable complex (near) real-time queries over evolving financial systems.

High-Performance Infrastructure

  • • Hardware Co-design: The co-design of data systems with FPGAs, Trusted Execution Environments (TEEs), and modern hardware to accelerate cryptographic workloads, privacy-preserving computations, and graph-based fraud detection etc.
  • • Faster stream-processing: System architectures designed for complex feature engineering and model inference on massive transaction streams under extreme latency constraints.
  • • Native Support: Architectures supporting real-time, multi-hop graph traversal and complex analytics within high-throughput transactional workloads.

Trustworthy and Privacy-preserving AI

  • • Privacy-Preserving ML: Support for training and deploying models on sensitive financial data, including techniques such as federated learning and efficient analytics over encrypted data.
  • • Data Management for Federated Learning (FL): Infrastructure to manage the entire FL lifecycle, addressing challenges such as secure and efficient data partitioning, ensuring statistical consistency, and optimizing communication costs across different legal and geographical jurisdictions.

Tentative Program Schedule

Sunday, May 31, 2026 • Bengaluru, India

Morning Session I
09:00 AM
Welcome Address
09:10 AM
Short Bayesian Calibration of the Heston Model Across Physical and Risk-Neutral Measures
Ahmik Virani, Arkaprava Majumdar, Aaditya Bhashyam, P. K. Srijith
09:25 AM
Short Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models
Aditya Tanna, Mitul Solanki, Mohamed Bouadi, Nassim Bouarour, Pratinav Seth, Vinay kumar Sankarapu
09:40 AM
Invited Talk I From Static to Strategic: Rethinking Testing and Benchmarking in Data Systems
Prof. Anupam Sanghi IIT Hyderabad
10:20 AM – 11:00 AM — Coffee Break
Morning Session II
11:10 AM
Short AIFDR: The AI Flight Data Recorder — A Contract for Non-Blocking, Verifiable Algorithmic Governance
Shreshta Shyamsundar, Anmol Jain
11:30 AM
Short Fed-SAuNF: Structure-Augmented Federated Graph Learning for Privacy-Sensitive Graphs
Saurav Sudevan, Harsh Pal, Deepanshu, Adarsh Patankar, Deepak Yadav
11:50 AM
Invited Talk II Compliant Data Processing Across Discovery, Sharing, and Querying
Prof. Kaustubh Beedkar IIT Delhi
12:30 PM – 01:30 PM — Lunch Break
Afternoon Session I
01:30 PM
Invited Talk III AI in Data Lakes
Prof. Rihan Hai TU Delft
02:10 PM
Long The Tin Inversion: When Feature Importance Depends on Forecast Horizon in Time Series Forecasting
Muktinath Vishwakarma, Manish Kurhekar
02:30 PM
Short FinOps over Heterogeneous Systems: Enabling Agentic Workflows via GraphQL
Ngoc Phuoc An Vo, Manish Kesarwani, Ruchi Mahindru, Chandrasekhar Narayanaswami
02:45 PM
Short AI Vaccination for Financial Fraud: Bio-Inspired Self-Healing Defense for Payment Networks
Sanket Krishna Pande
03:00 PM – 03:30 PM — Afternoon Break
Afternoon Session II
03:30 PM
Invited Talk IV Agentic AI in practice : Building & Deploying responsible end-end Agentic AI systems for Finance & Accounting Processes
Dr. Niyati Chhaya Co-Founder, Hyperbots
04:10 PM
Long Zero-Copy Semantic Contagion: In-Memory Streaming Architecture for Attention Graphs
Kabir Murjani
04:45 PM
Closing Remarks

Invited Talks

Kaustubh Beedkar

Kaustubh Beedkar

Assistant Professor, IIT-Delhi

Niyati

Niyati Chhaya

Co-Founder Hyperbots

Rihan

Rihan Hai

Assistant Professor, TU Delft

Prof. Anupam Sanghi, Assistant Professor, IIT Hyderabad

Anupam Sanghi

Assistant Professor, IIT Hyderabad

Call for Papers

Submission Tracks

  • Full Research Papers (8 pages): For Mature, well developed, and rigorously evaluated research
  • Short/Vision Papers (4 pages): For early-stage results, novel system designs, or bold, provocative ideas.

Submission Format

  • Template: Kindly adhere to the submission template guidlines found here.
    You can find the accepted Overleaf format here.
  • Author names: You can use the following LaTeX command to compile your paper without author names:
    \documentclass[sigconf, anonymous, review]{acmart}
  • Submissions that do not follow these requirements will be desk-rejected.

Evaluation & Presentation


  • Evaluation: Reviewing will be double-anonymous, for which the submissions must be anonymized by following the same anonymity requirements as for regular track papers at the SIGMOD/PODS 2026 conference.

  • To provide maximum visibility and foster deep discussions, every accepted paper (both full and short) will receive presentation opportunities: An oral presentation slot within a technical session. A spot in a dedicated interactive poster session facilitating direct engagement and in-depth conversations between authors and attendees.
  • Accepted papers will be non-archival and posted on the workshop website.
Submit via OpenReview

Important Dates

MAR 24, 2026 (AoE)
Paper Submission
APR 20, 2026 (AoE)
Author Notification
MAY 08, 2026
Camera Ready
MAY 31, 2026
Workshop

Workshop Organizers

organizer

Nitendra Rajput

Senior Vice President, Mastercard AI Garage

organizer

Dr. Ankur Arora

Vice President, Mastercard AI Garage

organizer

Prof. Srikanta Bedathur

Professor, IIT-Delhi

organizer

Prof. Sayan Ranu

Nick McKeown Chair Professor, IIT-Delhi

organizer

Dr. Aakarsh Malhotra

Director Data Science, Mastercard AI Garage

organizer

Dr. Sahil Manchanda

Manager Data Science, Mastercard AI Garage

organizer

Raghavendra P

Web-chair & Data Scientist II, Mastercard AI Garage

Program Committee

Mridula Verma
Institute for Development and Research in Banking Technology
Victor Lee
TigerGraph
Shikha Singh
Mastercard India Pvt Ltd
Sourav Dutta
Huawei Research Center
Hiroaki Shiokawa
University of Tsukuba
Vinayak Gupta
Lawrence Livermore National Laboratory
Amitabha Bagchi
Indian Institute of Technology Delhi
Sourav Medya
University of Illinois at Chicago
Pratinav Seth
Lexsi.ai
Kaustubh Beedkar
Indian Institute of Technology Delhi