Datasets:
country string | year int64 | urban_rural string | gender string | age int64 | age_group string | income_quintile string | education string | employment_status string | monthly_income_usd float64 | income_stability int64 | credit_history string | has_bank_account int64 | credit_score int64 | credit_need int64 | preferred_credit_source string | loan_amount_requested_usd float64 | collateral_available string | loan_purpose string | approved int64 | loan_disbursed_usd float64 | interest_rate float64 | loan_term_months int64 | monthly_payment_usd float64 | repayment_status string | rejection_reason string | scenario string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Uganda | 2,020 | rural | female | 65 | 55+ | middle | none | self_employed | 143.25 | 6 | none | 0 | 0 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,024 | urban | female | 44 | 35-44 | fourth | secondary | employed_informal | 129.63 | 8 | good | 0 | 260 | 1 | informal_lender | 9,743.53 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_collateral | low_burden |
Rwanda | 2,018 | rural | male | 49 | 45-54 | fourth | tertiary | employed_informal | 166.68 | 6 | good | 0 | 561 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,021 | urban | male | 36 | 35-44 | lowest | primary | employed_formal | 87.63 | 10 | none | 1 | 130 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,024 | rural | female | 64 | 55+ | lowest | tertiary | farmer | 64.67 | 1 | none | 1 | 268 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
DRC | 2,025 | urban | female | 21 | 18-24 | fourth | secondary | self_employed | 825.77 | 4 | limited | 0 | 241 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Uganda | 2,020 | rural | female | 32 | 25-34 | highest | tertiary | farmer | 1,169.03 | 7 | limited | 1 | 525 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,023 | urban | female | 69 | 55+ | highest | primary | unemployed | 335.5 | 1 | none | 1 | 120 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ghana | 2,019 | urban | female | 43 | 35-44 | highest | none | self_employed | 1,290.22 | 6 | excellent | 1 | 382 | 1 | commercial_bank | 5,307.51 | savings | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Uganda | 2,018 | rural | female | 27 | 25-34 | middle | none | unemployed | 333.05 | 1 | good | 1 | 850 | 1 | microfinance | 4,925.17 | guarantor | agriculture | 1 | 4,350.51 | 0.361 | 24 | 246.79 | late_60_days | not_applicable | low_burden |
Zambia | 2,020 | urban | female | 39 | 35-44 | highest | secondary | self_employed | 1,154.66 | 5 | excellent | 0 | 532 | 1 | informal_lender | 28,604.99 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_collateral | low_burden |
South Africa | 2,025 | urban | female | 31 | 25-34 | second | tertiary | self_employed | 257.24 | 7 | none | 0 | 489 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,023 | rural | female | 45 | 35-44 | fourth | primary | self_employed | 85.25 | 10 | none | 1 | 0 | 1 | informal_lender | 1,542.95 | vehicle | education | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Mali | 2,021 | urban | male | 30 | 25-34 | highest | none | employed_informal | 495.3 | 1 | none | 1 | 94 | 1 | commercial_bank | 8,899.72 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Niger | 2,020 | rural | male | 38 | 35-44 | fourth | none | employed_informal | 857.95 | 6 | none | 1 | 570 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,019 | rural | male | 65 | 55+ | second | secondary | self_employed | 99.74 | 6 | none | 0 | 203 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Zambia | 2,020 | urban | female | 22 | 18-24 | second | tertiary | employed_formal | 857.9 | 4 | none | 0 | 155 | 1 | family_friends | 4,867.25 | guarantor | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Uganda | 2,019 | rural | female | 57 | 55+ | second | primary | employed_informal | 49.57 | 7 | limited | 0 | 146 | 1 | family_friends | 3,056.36 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | employment_status | low_burden |
DRC | 2,019 | urban | male | 22 | 18-24 | second | secondary | farmer | 540.75 | 1 | none | 0 | 126 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,023 | rural | female | 41 | 35-44 | fourth | secondary | self_employed | 215.04 | 7 | none | 1 | 99 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Zambia | 2,019 | urban | male | 52 | 45-54 | fourth | tertiary | employed_formal | 899.67 | 6 | limited | 1 | 678 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ethiopia | 2,018 | urban | male | 67 | 55+ | lowest | secondary | employed_formal | 73.08 | 5 | limited | 0 | 799 | 1 | informal_lender | 11,355.41 | equipment | housing | 1 | 9,681.79 | 0.78 | 36 | 478.81 | current | not_applicable | low_burden |
Nigeria | 2,022 | urban | female | 31 | 25-34 | fourth | primary | unemployed | 533.41 | 1 | good | 1 | 109 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mozambique | 2,020 | rural | male | 20 | 18-24 | second | secondary | unemployed | 184.05 | 1 | limited | 1 | 116 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,021 | rural | male | 57 | 55+ | middle | secondary | self_employed | 130.19 | 3 | none | 1 | 433 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Rwanda | 2,019 | rural | female | 64 | 55+ | second | tertiary | employed_informal | 212.53 | 5 | limited | 0 | 748 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,019 | rural | male | 47 | 45-54 | middle | secondary | self_employed | 166.04 | 9 | limited | 0 | 269 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
DRC | 2,021 | rural | female | 21 | 18-24 | fourth | none | employed_informal | 373.51 | 9 | none | 0 | 616 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Senegal | 2,023 | rural | female | 44 | 35-44 | fourth | secondary | farmer | 51.76 | 8 | none | 1 | 0 | 1 | sacco | 3,927.94 | property | agriculture | 1 | 3,734.89 | 0.309 | 6 | 815.08 | late_30_days | not_applicable | low_burden |
Malawi | 2,021 | rural | female | 38 | 35-44 | fourth | secondary | self_employed | 260.39 | 5 | good | 0 | 712 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,022 | rural | female | 41 | 35-44 | second | primary | farmer | 293.77 | 2 | none | 0 | 702 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ghana | 2,022 | urban | male | 20 | 18-24 | fourth | tertiary | self_employed | 799.98 | 5 | none | 0 | 322 | 1 | commercial_bank | 7,943.11 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Uganda | 2,020 | rural | female | 34 | 25-34 | lowest | primary | farmer | 112.04 | 1 | none | 0 | 397 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Senegal | 2,020 | rural | male | 69 | 55+ | middle | tertiary | self_employed | 207.61 | 2 | good | 0 | 299 | 1 | family_friends | 2,392.54 | guarantor | emergency | 1 | 2,086.47 | 0.087 | 12 | 189.08 | paid_off | not_applicable | low_burden |
Mozambique | 2,021 | urban | male | 20 | 18-24 | middle | primary | self_employed | 964.6 | 4 | limited | 0 | 668 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Kenya | 2,018 | urban | female | 65 | 55+ | fourth | none | self_employed | 601.98 | 7 | excellent | 1 | 850 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
DRC | 2,023 | urban | male | 44 | 35-44 | highest | secondary | self_employed | 624.06 | 8 | good | 1 | 850 | 1 | informal_lender | 5,910.55 | none | housing | 1 | 5,264.67 | 0.777 | 24 | 389.72 | current | not_applicable | low_burden |
DRC | 2,022 | rural | female | 48 | 45-54 | second | secondary | unemployed | 220.72 | 3 | good | 0 | 789 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Tanzania | 2,020 | urban | male | 66 | 55+ | fourth | tertiary | self_employed | 938.36 | 3 | none | 0 | 0 | 1 | commercial_bank | 5,505.34 | none | housing | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Rwanda | 2,020 | rural | female | 29 | 25-34 | second | secondary | unemployed | 188.49 | 4 | none | 0 | 347 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Nigeria | 2,020 | rural | male | 69 | 55+ | middle | none | self_employed | 150.85 | 10 | good | 0 | 513 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,023 | rural | male | 32 | 25-34 | fourth | tertiary | employed_informal | 401.56 | 7 | excellent | 1 | 190 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,024 | urban | female | 36 | 35-44 | fourth | secondary | employed_informal | 1,304.59 | 8 | good | 0 | 761 | 1 | family_friends | 3,692.43 | guarantor | business | 1 | 3,589.61 | 0.093 | 18 | 217.89 | late_30_days | not_applicable | low_burden |
Ethiopia | 2,018 | rural | male | 41 | 35-44 | highest | primary | employed_formal | 927.6 | 10 | excellent | 1 | 414 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Uganda | 2,021 | rural | female | 49 | 45-54 | fourth | tertiary | farmer | 117.2 | 8 | limited | 1 | 361 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
South Africa | 2,018 | urban | male | 34 | 25-34 | second | none | employed_formal | 116.53 | 10 | limited | 0 | 47 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,021 | urban | female | 59 | 55+ | highest | none | employed_informal | 617.47 | 3 | limited | 0 | 771 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mozambique | 2,019 | urban | female | 19 | 18-24 | highest | secondary | employed_informal | 584.23 | 4 | limited | 0 | 253 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,020 | urban | female | 52 | 45-54 | second | secondary | farmer | 41.28 | 2 | none | 1 | 339 | 1 | commercial_bank | 623.28 | none | consumption | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Mali | 2,021 | rural | female | 52 | 45-54 | lowest | secondary | unemployed | 226.27 | 1 | none | 0 | 332 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mali | 2,020 | rural | male | 45 | 35-44 | second | tertiary | farmer | 65.69 | 6 | none | 0 | 0 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Nigeria | 2,021 | rural | female | 49 | 45-54 | fourth | primary | employed_informal | 187.83 | 10 | none | 0 | 626 | 1 | family_friends | 2,471.73 | savings | business | 1 | 2,051.38 | 0.014 | 12 | 173.36 | paid_off | not_applicable | low_burden |
Ethiopia | 2,024 | rural | female | 56 | 55+ | highest | tertiary | self_employed | 170.57 | 3 | none | 1 | 5 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Zambia | 2,024 | rural | female | 65 | 55+ | fourth | none | employed_informal | 604.75 | 8 | limited | 1 | 555 | 1 | sacco | 6,363.08 | savings | business | 1 | 5,810.33 | 0.295 | 12 | 627.13 | late_30_days | not_applicable | low_burden |
Zambia | 2,018 | rural | female | 29 | 25-34 | second | none | unemployed | 113.83 | 1 | limited | 0 | 146 | 1 | digital_lender | 6,526.22 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | existing_debt | low_burden |
Kenya | 2,021 | rural | female | 42 | 35-44 | lowest | primary | employed_formal | 47.12 | 10 | limited | 1 | 511 | 1 | family_friends | 1,511.97 | savings | emergency | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Senegal | 2,024 | urban | female | 47 | 45-54 | middle | none | unemployed | 242.19 | 2 | limited | 0 | 192 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Nigeria | 2,022 | rural | male | 35 | 25-34 | second | primary | farmer | 183.05 | 5 | none | 1 | 536 | 1 | sacco | 4,517.29 | guarantor | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_collateral | low_burden |
Mali | 2,019 | urban | female | 68 | 55+ | lowest | tertiary | farmer | 64.22 | 4 | none | 0 | 379 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,022 | rural | female | 44 | 35-44 | lowest | secondary | farmer | 14.97 | 10 | limited | 0 | 544 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Mozambique | 2,019 | rural | female | 48 | 45-54 | lowest | secondary | employed_informal | 24.39 | 5 | none | 0 | 740 | 1 | commercial_bank | 656.98 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Mali | 2,018 | rural | male | 28 | 25-34 | lowest | none | employed_informal | 23.52 | 2 | limited | 0 | 377 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ethiopia | 2,023 | urban | female | 39 | 35-44 | fourth | tertiary | self_employed | 596.48 | 6 | good | 1 | 725 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
South Africa | 2,022 | rural | female | 50 | 45-54 | second | primary | employed_informal | 232.6 | 6 | none | 1 | 593 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,024 | urban | female | 40 | 35-44 | second | secondary | farmer | 504.91 | 8 | good | 0 | 356 | 1 | family_friends | 3,732.79 | savings | business | 0 | 0 | 0 | 0 | 0 | not_applicable | employment_status | low_burden |
Tanzania | 2,020 | rural | male | 58 | 55+ | middle | secondary | self_employed | 63.68 | 5 | none | 0 | 163 | 1 | microfinance | 610.33 | savings | business | 1 | 500.95 | 0.274 | 12 | 53.17 | paid_off | not_applicable | low_burden |
Mozambique | 2,024 | urban | male | 25 | 18-24 | highest | none | unemployed | 1,529.21 | 1 | limited | 0 | 700 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ethiopia | 2,021 | rural | male | 25 | 18-24 | fourth | secondary | unemployed | 214.38 | 1 | good | 1 | 850 | 1 | family_friends | 16,383.85 | property | agriculture | 1 | 16,311.29 | 0.009 | 18 | 914.66 | current | not_applicable | low_burden |
Uganda | 2,023 | rural | male | 35 | 25-34 | middle | tertiary | employed_informal | 1,548.03 | 10 | limited | 1 | 12 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Zambia | 2,018 | urban | female | 34 | 25-34 | fourth | primary | employed_informal | 1,295.7 | 2 | limited | 0 | 98 | 1 | microfinance | 9,901.43 | savings | business | 1 | 8,538.7 | 0.296 | 12 | 921.83 | current | not_applicable | low_burden |
Mali | 2,018 | urban | male | 60 | 55+ | fourth | secondary | self_employed | 1,619.13 | 4 | limited | 0 | 143 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Nigeria | 2,024 | rural | female | 63 | 55+ | fourth | tertiary | employed_formal | 578.26 | 5 | none | 1 | 442 | 1 | microfinance | 7,038.54 | savings | emergency | 1 | 6,912.17 | 0.336 | 12 | 769.28 | late_60_days | not_applicable | low_burden |
Malawi | 2,024 | urban | male | 42 | 35-44 | middle | primary | farmer | 389.8 | 3 | limited | 0 | 357 | 1 | informal_lender | 7,502.72 | property | business | 1 | 6,552.89 | 0.77 | 12 | 966.6 | current | not_applicable | low_burden |
Uganda | 2,025 | urban | male | 44 | 35-44 | middle | primary | farmer | 225.09 | 1 | limited | 1 | 425 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,020 | urban | female | 33 | 25-34 | second | primary | farmer | 118.96 | 4 | none | 1 | 169 | 1 | sacco | 15,504.54 | none | education | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Zambia | 2,018 | urban | female | 45 | 35-44 | second | secondary | self_employed | 103.36 | 10 | none | 0 | 262 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Tanzania | 2,025 | rural | male | 54 | 45-54 | second | primary | farmer | 186.91 | 3 | excellent | 0 | 809 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ghana | 2,022 | rural | male | 55 | 45-54 | second | primary | self_employed | 361.62 | 10 | none | 1 | 265 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Senegal | 2,019 | urban | female | 68 | 55+ | second | primary | unemployed | 140.97 | 3 | good | 0 | 414 | 1 | informal_lender | 2,795.29 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Niger | 2,024 | rural | female | 48 | 45-54 | middle | tertiary | farmer | 120.62 | 9 | none | 0 | 0 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
South Africa | 2,025 | urban | male | 35 | 25-34 | middle | tertiary | farmer | 105.62 | 7 | none | 0 | 221 | 1 | informal_lender | 1,796.97 | equipment | business | 1 | 1,741.69 | 0.844 | 12 | 267.63 | current | not_applicable | low_burden |
Malawi | 2,020 | urban | female | 21 | 18-24 | lowest | secondary | employed_informal | 106.66 | 10 | limited | 0 | 639 | 1 | family_friends | 10,789.09 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Nigeria | 2,024 | rural | male | 53 | 45-54 | second | tertiary | farmer | 286.81 | 6 | limited | 0 | 116 | 1 | microfinance | 2,300.75 | guarantor | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | no_collateral | low_burden |
DRC | 2,024 | urban | female | 59 | 55+ | second | secondary | employed_informal | 443.12 | 9 | limited | 1 | 299 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Rwanda | 2,022 | rural | male | 46 | 45-54 | fourth | tertiary | self_employed | 865.43 | 1 | none | 0 | 142 | 1 | family_friends | 16,305.15 | vehicle | business | 1 | 15,537.52 | 0.035 | 12 | 1,339.94 | current | not_applicable | low_burden |
Niger | 2,023 | rural | female | 65 | 55+ | second | none | self_employed | 162.24 | 10 | limited | 1 | 405 | 1 | commercial_bank | 3,671.72 | property | business | 1 | 3,108.15 | 0.182 | 12 | 306.12 | late_60_days | not_applicable | low_burden |
Uganda | 2,020 | rural | female | 34 | 25-34 | lowest | primary | employed_informal | 64.16 | 1 | limited | 1 | 698 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Tanzania | 2,025 | rural | male | 20 | 18-24 | lowest | tertiary | employed_formal | 147.81 | 5 | none | 1 | 621 | 1 | informal_lender | 4,796.64 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_credit_history | low_burden |
Mali | 2,025 | urban | male | 50 | 45-54 | middle | primary | employed_informal | 137.18 | 8 | limited | 1 | 326 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
DRC | 2,025 | urban | male | 24 | 18-24 | lowest | primary | farmer | 66 | 3 | none | 0 | 391 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Malawi | 2,023 | urban | male | 22 | 18-24 | middle | secondary | farmer | 988.23 | 1 | none | 0 | 595 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
DRC | 2,018 | rural | male | 54 | 45-54 | middle | secondary | unemployed | 94.26 | 5 | none | 1 | 624 | 1 | digital_lender | 1,306.67 | property | consumption | 1 | 1,214.4 | 0.466 | 18 | 98.94 | defaulted | not_applicable | low_burden |
DRC | 2,020 | rural | male | 40 | 35-44 | highest | primary | farmer | 648.2 | 6 | none | 0 | 512 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Ethiopia | 2,021 | urban | female | 49 | 45-54 | middle | primary | self_employed | 464.17 | 5 | good | 0 | 196 | 1 | family_friends | 27,659.22 | none | emergency | 1 | 23,418.19 | 0.014 | 48 | 494.53 | late_30_days | not_applicable | low_burden |
Mozambique | 2,025 | urban | male | 56 | 55+ | lowest | primary | farmer | 95.22 | 4 | excellent | 1 | 470 | 1 | commercial_bank | 2,469.9 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | insufficient_income | low_burden |
Tanzania | 2,022 | urban | female | 37 | 35-44 | second | none | self_employed | 404.6 | 8 | none | 0 | 139 | 1 | family_friends | 3,626.23 | none | business | 0 | 0 | 0 | 0 | 0 | not_applicable | no_collateral | low_burden |
Ghana | 2,022 | rural | male | 49 | 45-54 | fourth | primary | employed_informal | 959.38 | 4 | none | 1 | 478 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Niger | 2,019 | rural | female | 46 | 45-54 | second | secondary | unemployed | 169.71 | 2 | excellent | 1 | 343 | 0 | none | 0 | none | none | 0 | 0 | 0 | 0 | 0 | not_applicable | null | low_burden |
Rwanda | 2,024 | rural | male | 48 | 45-54 | highest | secondary | unemployed | 1,757 | 1 | none | 0 | 29 | 1 | family_friends | 13,799.71 | none | agriculture | 0 | 0 | 0 | 0 | 0 | not_applicable | documentation_issues | low_burden |
Nigeria | 2,020 | rural | female | 54 | 45-54 | middle | primary | employed_formal | 104.4 | 7 | none | 0 | 654 | 1 | employer | 2,187.99 | vehicle | housing | 1 | 1,758.7 | 0.069 | 12 | 156.64 | paid_off | not_applicable | low_burden |
Africa Synth Financial Inclusion Credit Access Patterns Africa All | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: economics_finance - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
Dataset context from the existing Hugging Face card: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Credit Access Patterns in Africa Synthetic dataset modeling credit access, approval, and repayment patterns across 15 Sub-Saharan African countries from 2018-2025. Dataset Description This dataset simulates individual-level credit seeking behavior, application outcomes, and repayment patterns. It captures the spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all |
| Sector | economics_finance |
| Topic tags | financial-inclusion, fintech, synthetic-data, sub-saharan-africa, credit-access, synthetic |
| Modalities | tabular, text |
| Formats | csv |
| Size category | 10K<n<100K |
| Countries | Africa-wide or source-defined African coverage |
| ISO3 coverage | not declared |
| Last modified on HF | 2026-04-14 22:53:30+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: country, upstream_publisher.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: Electric Sheep Africa metadata inventory
- Publisher/source attribution: Public dataset metadata
- License: CC BY 4.0
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_synth_financial_inclusion_credit_access_patterns_africa_all_2026,
title = {Africa Synth Financial Inclusion Credit Access Patterns Africa All | Africa (Electric Sheep Africa metadata inventory)},
author = {Public dataset metadata},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-financial-inclusion-credit-access-patterns-africa-all}}
}
License
Released under CC BY 4.0.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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