Overview
Minerva has created a proprietary customer risk rating (CRR) engine which takes a multifactor approach to scoring client risk. This includes hard binary criteria such as the presence of an individual or entity on a global terror, sanctions, or criminal watchlists, as well as inferred criteria such as criminal status or political exposure from unstructured notes and listed occupations. The entire profile is considered when assigning a CRR score to it, and includes all fields from social media, global news, watchlists, registries, independent journalism, open-source web pages, legal databases, and business registries. The score is normalized out of 100, with default risk classification breakpoints at 33 and 66 (where the next category score is greater than or equal to that of the previous breakpoint).CRR Criteria Categories
The CRR criteria are separated into 3 categories:- Dynamic: Criteria which apply to the unique characteristics of the profile being analyzed and are subject to change between profiles.
- Organizational: Criteria which are static between profile searches but differ between the institutions performing the search. The out-of-box solution is set with the defaults listed in Appendix S2 and can be configured at request.
- Contributed: Criteria which the end user can modulate based on their unique knowledge, the knowledge of their institutions, or their unique understanding of the profile being analyzed.
- Dynamic criteria have the highest degrees of freedom due to the range of possible profiles that may present themselves to the algorithm.
- Contributed criteria vary based on the interpretation of the end user and their unique knowledge of the profile, which may or may not be applicable in every search case.
- Organizational criteria have the lowest degrees of freedom, and typically only vary among the institutions of the customer base and are unlikely to change through time unless the business practices of the end user’s organization dramatically change.
Risk Categories and Weightings
Dynamic Factors
| Code | Criteria | Formula | Score |
|---|---|---|---|
| 1 | Sanctions list match | Soft name match | 100* |
| 2 | Sanctioned geography (FATF blacklisted) | Geography match | 100* |
| 3 | Politically-exposed persons (PEP) list match | Soft name match | 100* |
| 4 | PEP status inferred from profile | Contextual inference | 25 |
| 5 | High-risk business inferred from profile | Contextual inference | 25 |
| 6 | High-risk (FATF greylisted) geography | Geography match | 15 |
| 7 | Offshore assets discovered | Soft name match | 10 |
| 8 | Adverse media discovered (N number of URLs) | max(1, 0.02N) | 0–50 |
| 9 | Public exposure index (N number of URLs) | max(1, 0.1N) | 0–10 |
| 16 | Criminal status inferred from profile | Contextual inference | 25 |
| 17 | Criminal list match | Soft name match | 100* |
| 19 | Involvement in high-risk legal cases | Soft name match | 25 |
Organizational Factors
| Code | Criteria | Formula | Score |
|---|---|---|---|
| 10 | Organization supports remote transactions | Configurable | 5 |
| 11 | Organization processes transactions through third parties | Configurable | 5 |
| 12 | Emphasis on fast and/or anonymous transfers | Configurable | 5 |
| 13 | Organization facilitates cross-border transactions | Configurable | 5 |
Contributed Factors
| Code | Criteria | Formula | Score |
|---|---|---|---|
| 14 | Previous SAR/STR filed | User-contributed | 10 |
| 15 | Known cash/crypto intensive business (CIB) | User-contributed | 5 |
| 18 | User Override (Low/Medium/High)** | User-contributed | 0/50/100* |
- Categories that override the total score to equal 100 (High).
** The User Override function will allow the user to override the Minerva score to either Low, Medium, or High. The user must enter a rationale for the override for audit purposes, and in alignment with the organization’s risk assessment policy.