Pipeline Overview

Evidence is transformed at application grain and evaluated as a simulation-only credit-risk diagnostic.

1

Credit-scoring dataset

Application-grain source evidence

Source tables

11

Prepared rows

1,000

Candidate features

126

2

Feature engineering & selection

10 final model inputs from governed candidates

Candidate features

126

Final model inputs

10

The persisted diagnostic model retains 10 raw features, the smallest set within one standard error of the lowest nested-CV MAE. Missing source values remain unavailable, receive fold-local imputation, and retain a missingness indicator.

Final model featureBusiness meaningData sourcePermutation importance
max_dpd_12mGoverned engineered feature; description pending registry entry.credit_facility47.3642
requested_loan_to_revenue_ratioRequested credit relative to annual business revenue.loan_application + financial_statement34.9561
requested_loan_to_operating_cashflow_ratioGoverned engineered feature; description pending registry entry.derived application-grain feature2.0743
debt_service_coverage_ratioGoverned engineered feature; description pending registry entry.derived application-grain feature1.2558
installment_to_operating_cashflow_ratioGoverned engineered feature; description pending registry entry.derived application-grain feature0.9325
installment_to_bank_inflow_ratioGoverned engineered feature; description pending registry entry.credit_facility + bank_statement_month_sum0.9063
positive_cashflow_month_ratio_6mGoverned engineered feature; description pending registry entry.derived application-grain feature0.3774
negative_cashflow_month_count_6mGoverned engineered feature; description pending registry entry.derived application-grain feature0.3755
debit_credit_ratio_6mGoverned engineered feature; description pending registry entry.derived application-grain feature0.3443
worst_collectability_12mGoverned engineered feature; description pending registry entry.credit_facility0.2841
3

Comparable candidate branches

Group-safe regression evaluation with fold-local selection

all numeric pca 95

All governed numeric features compressed to 95% training-fold explained variance.

MAE

57.036

RMSE

71.672

0.716

one se 10 plus residual pca 95

One-SE minimal raw features plus PCA of the non-overlapping numeric residual block at 95% training-fold variance.

MAE

43.364

RMSE

55.854

0.828

one se minimal 10 raw

Smallest 10-feature raw set within one standard error of the best nested-CV MAE.

MAE

43.420

RMSE

57.195

0.819

top 20 permutation raw

Top 20 fold-local permutation-ranked raw features.

MAE

42.672

RMSE

55.759

0.828

top 30 permutation raw

Top 30 fold-local permutation-ranked raw features.

MAE

42.579

RMSE

55.664

0.829

top 45 permutation raw

Top 45 fold-local permutation-ranked raw features.

MAE

42.298

RMSE

54.613

0.835

top 65 permutation raw

Top 65 fold-local permutation-ranked raw features.

MAE

42.666

RMSE

55.274

0.831

4

Optional financial-statement resilience

A missing statement is evidence status, not an error or zero value

observed as recorded

MAE 37.82 · RMSE 51.68 · R² 0.853

financial statement unavailable

MAE 73.97 · RMSE 92.62 · R² 0.528

A score remains eligible with bank statements, bookkeeping, invoices, or a financial statement.

5

Model evaluation

Current persisted diagnostic credit-score model

catboost · 10 raw features

Validation MAE 42.83 · Test MAE 41.04 · Test R² 0.831

Synthetic FICO-style scores and internal SLIK-aligned tiers are diagnostic only.