Credit card applicant likelihood using protected data
Ranks an individual's likelihood of applying for a credit card in the next 12 months; modeling incorporates protected-class attributes such as age and gender.
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 | Rank | rank |
| Type | Integer | long |
| Statistical type | Ordinal | ordinal |
| Allowed values | Not applicable | null |
| Deprecation | Not deprecated | false |
| Derivations | Not applicable | null |
| Directionality | Higher number means a greater ranked likelihood. | |
Popularity
How much Faraday's models lean on this attribute.
| Industry | Popularity rank | Average share of weight |
|---|---|---|
| Solar | 72 of 194 | 0.4% |
| Home services | 128 of 243 | 0.2% |
| Real estate | 262 of 441 | 0.1% |