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

AML Screening API: 1,300+ Lists at $0.20 per Check

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
1,459
Company Posts That Month
220
Language
English
Hacker News Points
-
Post removed?
No
Summary

Didit’s AML Screening API is designed to help regulated businesses check customers and organizations against more than 1,300 global watchlists covering sanctions, politically exposed persons, criminal records, adverse media, regulatory actions, insolvency, and other risk categories. Available either within Didit’s identity-verification workflows or as a standalone unified API call, the service separates identity confidence from underlying entity risk through Match and Risk Scores, aiming to reduce false positives caused by similar names while supporting configurable thresholds and analyst review. Results include screening statuses, matched profiles, list categories, and auditable review states such as False Positive, Confirmed Match, and Inconclusive. The platform supports daily ongoing rescreening, webhook updates for newly detected risks, and combined screening of companies and beneficial owners in business-verification processes. Pricing is listed at $0.20 per screening check with no minimums, while daily rescreening costs $0.07 per user annually.

Trends Found in this Post

No tracked trend matches for this post yet.

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.