Credit Scoring


Operation keyword for Features: features
Operation keyword for Credit Scores: credit-scores

Credit Scoring is a set of customisable analytical solutions for Enterprise-level clients of Nordigen that require the most advanced capabilities. Credit Scoring set includes two solutions: Features and Credit Scores.
Credit Scoring includes access to a library of up to 1 million predictive machine learning features (modelling parameters), custom model training services and bespoke infrastructure deployments.

Request Flow

To use this product via API, see the Endpoints section "report" and go through the following steps:
  1. Upload the account information;
  2. Apply operation features or credit-scores;
  3. Get results.


Features are representations from transaction data that are used as an input for scoring models.

Response Example

Key Descriptions

<function or feature logic name>_cat_<category_id>_<months>m (e.g.median_cat_79_12m)FloatNumerical representations (features) of statistically transformed raw transaction data on the aggregated account level. Each feature is associated with specific transformations on specific categories or category groups 
<statement_id> (e.g. abcdefg12345)StringUnique identifier for each statement 
statusStringProcessing record state 
typeStringResponse type 

Credit Scores

Credit scoring means calculating the probability of a default, based on behaviours identified in transaction data.

Response Example

Key Descriptions

model-name (e.g. model_test_v12.0.model)FloatA probability that the statement is going to default 
statusStringProcessing record state 
typeStringRedundant field, it will be removed in the next iteration