Home / Companies / Didit / Blog / Post Details
Content Deep Dive

Velocity Rules & Structuring Detection: A Developer's Guide

Blog post from Didit

Aggregate trend data notice

Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.

Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.

This company's pages remain public, but its content is excluded from normalized aggregate trends. Unfiltered raw trends and advanced filtering are available to Accelerate and Lead accounts.

Post Details
Company
Date Published
Author
Didit
Word Count
1,311
Company Posts That Month
190
Language
English
Hacker News Points
-
Post removed?
No
Summary

The text discusses the implementation of velocity rules for transaction monitoring to detect financial structuring and mule activity. It highlights the importance of evaluating transactions over time rather than individually, using a system that maintains rolling windows per user to count, sum, and de-duplicate counterparties. Didit's Transaction Monitoring API provides this capability by allowing users to define a window, choose an aggregation method (count, sum, or distinct), and set a threshold to trigger alerts, all without needing a separate streaming processor. The API is priced at $0.02 per transaction, with separate AML screening costs. Velocity rules are essential for identifying patterns such as structuring, which involves splitting large sums into smaller payments to avoid detection, and mule networks, characterized by funds rapidly moving in and out from multiple sources. The text provides examples of how these rules can be applied across various industries, including fintech, crypto, lending, marketplaces, and iGaming, and explains how to integrate and tune these systems using Didit's platform.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Real-time 2 6,790 1,736 269 -9%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.