double difference

DataFunSummit

Jan 28, 2024 · Artificial Intelligence

Causal Inference and Bias Correction Methods in Ant Financial Risk Control

This article presents how Ant Group applies causal inference techniques—including confounding bias analysis, double‑difference methods, DiDTree, and shrinkage‑based causal trees—to correct biases in risk‑control scenarios, detailing the theoretical background, algorithmic designs, experimental validation, and practical deployment.

ant financialbias correctioncausal inference

0 likes · 21 min read

Causal Inference and Bias Correction Methods in Ant Financial Risk Control

DataFunSummit

Sep 3, 2023 · Artificial Intelligence

Estimating Clustered Data Causal Effects with DiConfounder: A Double‑Difference Framework

This article presents a comprehensive approach to estimating causal effects on clustered data using a double‑difference method, introduces the DiConfounder algorithm built on Rubin Causal Model extensions, details data characteristics, model assumptions, six‑step pipeline, and reports competitive results on the ACIC2022 challenge.

DiConfoundercausal inferenceclustered data

0 likes · 13 min read

Estimating Clustered Data Causal Effects with DiConfounder: A Double‑Difference Framework