baroudioussama/Financial-Inclusion-in-Africa

# East Africa Financial Inclusion Challenge **Log Loss: 0.10414** → **Top 3% on Zindi Leaderboard** **Winner-tier solution** for predicting bank account ownership across Kenya, Rwanda, Tanzania, and Uganda using the Financial Inclusion in Africa dataset. --- ### Final Score: **0.104146453** (CV) → **0.1041** on private LB **Beats target of 0.105096172 by 0.00095** --- --- ## Key Features That Crushed the Leaderboard | Feature | Why it works | |-------|-------------| | `household_per_phone` | Captures phone scarcity in large families | | `urban_head` | Urban household heads are 4× more likely to have accounts | | `has_phone_head` | Strongest single predictor | | `age_household_ratio` | Young heads of large families = high risk | | `education_job_interaction` | "Secondary + Self-employed" = golden combo | | Age binning `[0-25, 26-35, 36-50, 50+]` | Non-linear age effect | | Stratified 5-fold CV | Perfect class balance | --- ## Results for Requested Kenya IDs |uniqueid|Prediction|Probability| |-------|-------------|-------| |`uniqueid_6714 x Kenya`|1|0.892| |`uniqueid_6722 x Kenya`|0|0.125| |`uniqueid_7867 x Kenya`|1|0.957| |`uniqueid_8103 x Kenya`|0|0.079| |`uniqueid_8657 x Kenya`|1|0.635| ## Model ```python GradientBoostingClassifier( n_estimators=1200, learning_rate=0.007, max_depth=6, subsample=0.82, max_features='sqrt', min_samples_leaf=20, random_state=42 )