ComplyCube provides the ability to customise check thresholds and settings. This allows you to automate your checks in accordance with your risk-based approach, as recommended by your Money Laundering Reporting Officer (MLRO).
You can amend these automation rules through the Web Portal (Automation).
ComplyCube's AML Screening matching engine is purpose-built to find and match comparable identity data from any language or script. It incorporates sophisticated fuzzy matching algorithms, heuristics, variants, and phonetic analysis to find matches without producing costly and time-wasting lists of false positives.
To simplify usage, ComplyCube represents the outcome of the analysis in the form of a match score. A match score can range from 0 - 100, with 100 being the best match.
By default, an AML Screening Check will only return matches with a match score over 85 and automatically reject matches with a score ranging between 85 and 90. Ultimately, only matches with a score higher than 90 will require manual checks.
These automation thresholds can be adjusted in line with your risk-based framework and internal process.
By default, ComplyCube will exclude any matches that are deceased or deemed inactive (e.g. ex-PEPs). It will also return all matches, even if they do not have DOB, gender, nationality, or incorporation country details. Furthermore, matches against low-quality aliases will also be returned.
Depending on your risk tolerance and preference, you can select from two distinct name matching techniques:
Fuzzy (default): applies various linguistic, phonetic, and near-match techniques on names to find matches.
Precise: only matches names that are exact
ComplyCube's Document Check uses OCR technology and advanced analytics to authenticate and extract data from your clients' ID documents.
This setting empowers age verification compliance by allowing you to set a minimum acceptable age before your client ID is flagged.
By default, a Document Check will flag anyone who is younger than 18 years of age.
ComplyCube extends further optional checks, including:
Client data validation: this check compares the client record data (e.g. first and last names) with data extracted from an ID document.
By default, ComplyCube will not perform any additional checks.
ComplyCube's Identity Check utilises computer vision, spoof-detection technologies, and facial comparison algorithms to determine whether two faces belong to the same client.
ComplyCube represents the outcome of a facial analysis in the form of a facial similarity score. A facial similarity score can range from 0 - 100, with 100 being an exact match.
By default, an Identity check will deem two faces a match when the facial similarity score is over 80.