Credit score proxy
Groups individuals into 12 ranks across 5 tiers (Best, Above average, Average, Below average, Poor); each tier spans 2-3 ranks. Rank 1 (~760 credit score) is best, rank 12 (~590) is lowest. Lower rank = higher score.
Coverage
For how many people does Faraday have a value for this attribute? Depending on the type of attribute, Faraday could know a value for people at the individual level, or infer it based on values it knows for each person's address. Finally, in some cases, we can estimate a value for a person based on what we know about other people in their area.
Time series
Faraday collects observations for this attribute over time. This chart shows how many observations we collected at different times.
Data distribution
Technical details
These technical details describe how Faraday represents this attribute internally.
| Property | Value | API value |
|---|---|---|
| API name | credit_ | |
| Category | Financial | fig/financial |
| Unit | Not applicable | null |
| Type | Integer | long |
| Statistical type | Ordinal | ordinal |
| Allowed values | Not applicable | null |
| Deprecation | Not deprecated | false |
| Derivations | Modeled | ["modeled"] |
| Directionality | Lower rank values indicate a higher modeled credit score and greater marketing profitability; rank 1 is best, rank 12 is poor. | |
Interpretation table
For enumerable attributes, a mapping from values to their interpretations. The key type matches the attribute's data type, and the value is always a string interpretation.
| Value | Interpretation |
|---|---|
1 | Best - ~760 credit score |
2 | Best - ~740 credit score |
3 | Above average - ~725 credit score |
4 | Above average - ~710 credit score |
5 | Average - ~690 credit score |
6 | Average - ~675 credit score |
7 | Below average - ~660 credit score |
8 | Below average - ~650 credit score |
9 | Below average - ~640 credit score |
10 | Poor - ~625 credit score |
Contribution
1 authority contributed since Jul 2023.
| Data observation date | Data ingestion date | Count | ID |
|---|---|---|---|
| 2026-05-01 | 2026-09-10 | 266,506,942 | c5492806-a892-460e-aba1-ee78ffb29c5b |
| 2026-03-01 | 2026-07-01 | 264,096,977 | 1181277b-b751-4a59-aae1-101fa3f55375 |
| 2026-02-01 | 2026-07-02 | 264,777,400 | af53c569-4fe2-4282-975b-4cbf5f85692d |
| 2025-12-01 | 2026-08-11 | 268,508,091 | 84d6a1c5-d142-4a4d-9cb3-902de4c82c30 |
| 2025-11-01 | 2026-08-11 | 268,299,874 | a071c538-cbbf-4faf-8993-53a6d2810951 |
| 2025-10-01 | 2026-02-05 | 267,680,760 | ace9a9e6-ba69-4a69-8301-0dec523b924a |
| 2025-07-01 | 2026-01-28 | 262,889,193 | a51ec85a-c11f-4b07-8ee5-35a8120f8bd2 |
| 2025-04-01 | 2026-02-06 | 262,668,284 | cb1857b9-bd1d-44c1-8093-9ac634bbf433 |
| 2025-03-01 | 2026-01-18 | 261,432,302 | 87669a43-8737-4a8b-a226-17a05b5bf229 |
| 2024-11-01 | 2026-01-28 | 246,860,464 | 7c0b300e-8a87-44f8-aeb7-8b90596fc1ac |
| 2024-06-01 | 2026-02-05 | 248,015,318 | 8fc3fa4d-9436-4d62-a1c6-2093c8a6ce31 |
| 2024-03-01 | 2025-10-11 | 248,916,514 | 5b84b6ac-adf8-4775-ba5c-853340ed9338 |
| 2023-07-01 | 2026-02-05 | 246,101,092 | 49e62ee3-2dbf-46a1-8c14-608702fb14cb |
Popularity
How much Faraday's models lean on this attribute.
| Industry | Popularity rank | Average share of weight |
|---|---|---|
| All industries | 39 of 500 | 0.3% |
| Ecommerce | 19 of 331 | 0.9% |
| Home services | 23 of 387 | 0.4% |
| Real estate | 184 of 291 | 0.2% |
| Marketing | 341 of 500 | 0.1% |
| Solar | 191 of 203 | 0.1% |