Nigerian Banking
Collection
20 Nigerian banking datasets for ML research, fraud detection, and financial analytics.
•
20 items
•
Updated
•
1
Datasets:
record_id
stringlengths 14
14
| customer_id
stringlengths 12
12
| report_date
timestamp[ns]date 2023-12-02 00:00:00
2024-11-30 00:00:00
| credit_score
int64 300
850
| total_debt_ngn
float64 367
50M
| active_accounts
int64 0
14
| delinquent_accounts
int64 0
8
| payment_history_months
int64 6
119
| credit_utilization
float64 0
0.96
| high_risk
bool 2
classes |
|---|---|---|---|---|---|---|---|---|---|
CBR-0001543953
|
CUS-95543715
| 2024-09-28T00:00:00
| 592
| 292,523.753467
| 1
| 0
| 91
| 0.471054
| false
|
CBR-0000293166
|
CUS-71670513
| 2024-09-29T00:00:00
| 551
| 602,670.82242
| 4
| 0
| 46
| 0.178354
| false
|
CBR-0001355954
|
CUS-40872535
| 2023-12-05T00:00:00
| 694
| 1,303,946.008736
| 2
| 0
| 61
| 0.268925
| true
|
CBR-0001407017
|
CUS-67813998
| 2024-04-16T00:00:00
| 746
| 154,232.604995
| 2
| 2
| 14
| 0.169534
| false
|
CBR-0000944098
|
CUS-65710941
| 2024-04-04T00:00:00
| 746
| 369,264.432047
| 5
| 0
| 18
| 0.501417
| true
|
CBR-0000490010
|
CUS-35648438
| 2024-03-29T00:00:00
| 590
| 360,738.477418
| 3
| 0
| 12
| 0.373705
| false
|
CBR-0000332513
|
CUS-79606324
| 2024-09-16T00:00:00
| 699
| 430,823.435248
| 1
| 0
| 103
| 0.113895
| false
|
CBR-0001008405
|
CUS-58382489
| 2024-10-08T00:00:00
| 714
| 268,950.812758
| 1
| 0
| 22
| 0.252972
| false
|
CBR-0001611905
|
CUS-42464670
| 2024-10-02T00:00:00
| 696
| 474,166.831267
| 5
| 1
| 107
| 0.563795
| false
|
CBR-0001608594
|
CUS-71194111
| 2024-05-08T00:00:00
| 526
| 1,271,761.235065
| 3
| 0
| 118
| 0.763703
| false
|
CBR-0001504754
|
CUS-33715684
| 2024-04-02T00:00:00
| 773
| 118,198.820537
| 2
| 0
| 29
| 0.468672
| false
|
CBR-0001011064
|
CUS-25211410
| 2024-01-04T00:00:00
| 534
| 334,234.495682
| 5
| 1
| 11
| 0.024442
| false
|
CBR-0000956038
|
CUS-15874696
| 2024-08-09T00:00:00
| 613
| 275,350.444958
| 5
| 0
| 44
| 0.650557
| false
|
CBR-0000928084
|
CUS-79755317
| 2024-07-22T00:00:00
| 661
| 344,631.784724
| 2
| 2
| 116
| 0.194234
| false
|
CBR-0000979816
|
CUS-25335002
| 2024-07-28T00:00:00
| 784
| 154,256.245277
| 5
| 1
| 100
| 0.159151
| false
|
CBR-0000087068
|
CUS-17669672
| 2024-08-24T00:00:00
| 647
| 1,271,059.752542
| 6
| 0
| 51
| 0.458556
| false
|
CBR-0001572850
|
CUS-90846082
| 2023-12-10T00:00:00
| 632
| 2,392,647.037739
| 4
| 1
| 30
| 0.476032
| false
|
CBR-0000232133
|
CUS-95810923
| 2024-03-27T00:00:00
| 598
| 307,480.740726
| 2
| 0
| 63
| 0.183533
| false
|
CBR-0000558283
|
CUS-40148198
| 2024-07-15T00:00:00
| 474
| 197,147.362115
| 1
| 1
| 20
| 0.16907
| false
|
CBR-0001062180
|
CUS-10410395
| 2024-11-21T00:00:00
| 662
| 431,587.405795
| 3
| 0
| 92
| 0.068819
| false
|
CBR-0000694924
|
CUS-26491474
| 2024-09-06T00:00:00
| 582
| 338,997.956009
| 5
| 2
| 119
| 0.39473
| true
|
CBR-0000470141
|
CUS-33291081
| 2024-06-21T00:00:00
| 618
| 714,548.674593
| 1
| 0
| 49
| 0.422054
| false
|
CBR-0000950667
|
CUS-28787801
| 2024-07-11T00:00:00
| 593
| 1,312,944.145323
| 4
| 2
| 61
| 0.418797
| false
|
CBR-0001629205
|
CUS-99733564
| 2024-07-20T00:00:00
| 620
| 275,645.387154
| 1
| 0
| 65
| 0.47429
| false
|
CBR-0001060798
|
CUS-98008097
| 2024-05-01T00:00:00
| 692
| 1,590,830.362014
| 5
| 1
| 93
| 0.542343
| false
|
CBR-0001603983
|
CUS-34664497
| 2024-08-10T00:00:00
| 711
| 29,008.760661
| 5
| 0
| 58
| 0.155299
| false
|
CBR-0000525970
|
CUS-74818373
| 2024-03-19T00:00:00
| 574
| 650,705.757151
| 5
| 0
| 10
| 0.465782
| true
|
CBR-0000420549
|
CUS-30562960
| 2024-09-04T00:00:00
| 580
| 176,283.051899
| 1
| 0
| 44
| 0.273995
| false
|
CBR-0001353343
|
CUS-96477120
| 2024-09-01T00:00:00
| 734
| 877,048.771841
| 3
| 0
| 78
| 0.421122
| false
|
CBR-0000865022
|
CUS-95358914
| 2024-04-02T00:00:00
| 613
| 1,214,960.051113
| 4
| 1
| 9
| 0.179467
| false
|
CBR-0000018838
|
CUS-57114946
| 2024-01-06T00:00:00
| 441
| 305,815.405767
| 3
| 0
| 82
| 0.448062
| false
|
CBR-0000612126
|
CUS-45577586
| 2024-05-20T00:00:00
| 565
| 2,296,178.681362
| 3
| 0
| 17
| 0.535022
| false
|
CBR-0001503102
|
CUS-51396281
| 2024-05-18T00:00:00
| 620
| 6,548.625129
| 1
| 0
| 6
| 0.320563
| false
|
CBR-0001084929
|
CUS-74880029
| 2024-05-27T00:00:00
| 589
| 625,763.481834
| 3
| 1
| 32
| 0.445906
| true
|
CBR-0000282770
|
CUS-90638225
| 2024-08-31T00:00:00
| 594
| 693,473.72137
| 3
| 0
| 19
| 0.282469
| false
|
CBR-0000748952
|
CUS-11789433
| 2024-04-24T00:00:00
| 568
| 449,703.664045
| 5
| 1
| 59
| 0.231489
| false
|
CBR-0000511174
|
CUS-63441919
| 2024-07-23T00:00:00
| 614
| 846,443.759979
| 3
| 0
| 85
| 0.386074
| false
|
CBR-0000519556
|
CUS-41217997
| 2024-05-10T00:00:00
| 479
| 1,372,751.535471
| 6
| 1
| 110
| 0.188889
| false
|
CBR-0000111675
|
CUS-12608392
| 2024-01-22T00:00:00
| 664
| 1,365,400.983354
| 1
| 1
| 70
| 0.198374
| true
|
CBR-0000341241
|
CUS-11058965
| 2024-05-16T00:00:00
| 513
| 19,211.693298
| 3
| 0
| 47
| 0.364712
| true
|
CBR-0000228860
|
CUS-75893925
| 2024-07-31T00:00:00
| 698
| 1,792,128.239118
| 2
| 0
| 92
| 0.352892
| false
|
CBR-0001987233
|
CUS-62532559
| 2024-09-27T00:00:00
| 607
| 260,433.439452
| 5
| 0
| 48
| 0.23899
| false
|
CBR-0001316514
|
CUS-42962908
| 2024-04-19T00:00:00
| 551
| 199,800.141165
| 7
| 1
| 55
| 0.058984
| false
|
CBR-0000821373
|
CUS-29916256
| 2024-06-29T00:00:00
| 658
| 3,588,886.877068
| 3
| 0
| 116
| 0.206859
| false
|
CBR-0000208036
|
CUS-74334758
| 2024-03-08T00:00:00
| 580
| 3,499,140.998892
| 3
| 2
| 81
| 0.175481
| false
|
CBR-0001411060
|
CUS-55628162
| 2024-09-04T00:00:00
| 646
| 171,169.7699
| 4
| 0
| 59
| 0.177308
| true
|
CBR-0001766743
|
CUS-11992739
| 2024-04-15T00:00:00
| 615
| 476,095.732805
| 3
| 0
| 54
| 0.217495
| false
|
CBR-0001419742
|
CUS-89194325
| 2024-06-30T00:00:00
| 577
| 520,645.632353
| 3
| 0
| 77
| 0.303988
| false
|
CBR-0001423861
|
CUS-65864204
| 2024-11-30T00:00:00
| 367
| 412,640.374381
| 2
| 0
| 84
| 0.049682
| false
|
CBR-0000834427
|
CUS-10163504
| 2024-07-16T00:00:00
| 623
| 135,437.339657
| 3
| 0
| 75
| 0.079112
| false
|
CBR-0000375646
|
CUS-99339833
| 2024-03-18T00:00:00
| 752
| 613,834.24971
| 3
| 0
| 78
| 0.352828
| false
|
CBR-0000700396
|
CUS-50946776
| 2024-02-12T00:00:00
| 743
| 122,906.162846
| 4
| 1
| 21
| 0.132763
| false
|
CBR-0000409325
|
CUS-14378298
| 2024-02-28T00:00:00
| 670
| 311,742.077029
| 5
| 1
| 97
| 0.386621
| false
|
CBR-0001170021
|
CUS-91111225
| 2024-05-25T00:00:00
| 655
| 249,149.805417
| 1
| 0
| 55
| 0.161579
| false
|
CBR-0000329948
|
CUS-56968730
| 2024-08-31T00:00:00
| 783
| 2,847,011.900538
| 4
| 0
| 72
| 0.223049
| false
|
CBR-0000554774
|
CUS-49324302
| 2024-11-30T00:00:00
| 691
| 95,682.933243
| 3
| 0
| 89
| 0.567289
| false
|
CBR-0000115543
|
CUS-51730774
| 2024-02-10T00:00:00
| 717
| 3,368,247.387197
| 7
| 1
| 88
| 0.236688
| true
|
CBR-0001681225
|
CUS-16951031
| 2024-05-15T00:00:00
| 537
| 92,339.154409
| 6
| 1
| 54
| 0.126931
| true
|
CBR-0001652476
|
CUS-65563213
| 2024-03-10T00:00:00
| 703
| 175,683.781278
| 2
| 1
| 37
| 0.129859
| true
|
CBR-0001599654
|
CUS-21610542
| 2024-08-27T00:00:00
| 754
| 1,353,606.007952
| 5
| 0
| 39
| 0.368087
| false
|
CBR-0000300463
|
CUS-30767457
| 2024-01-01T00:00:00
| 656
| 159,026.85841
| 2
| 1
| 92
| 0.511242
| false
|
CBR-0001860823
|
CUS-11123444
| 2023-12-14T00:00:00
| 521
| 1,307,032.942859
| 2
| 1
| 93
| 0.386085
| true
|
CBR-0000495942
|
CUS-57390073
| 2024-07-28T00:00:00
| 555
| 10,079,961.288876
| 4
| 2
| 82
| 0.4424
| false
|
CBR-0001172623
|
CUS-56586096
| 2024-02-18T00:00:00
| 524
| 1,154,263.169788
| 7
| 0
| 33
| 0.359518
| true
|
CBR-0000413466
|
CUS-48834393
| 2024-09-14T00:00:00
| 730
| 1,534,546.920806
| 2
| 1
| 16
| 0.210514
| false
|
CBR-0001695595
|
CUS-60250481
| 2024-09-03T00:00:00
| 591
| 418,524.475262
| 4
| 1
| 71
| 0.407171
| false
|
CBR-0000861489
|
CUS-33421476
| 2024-08-20T00:00:00
| 586
| 3,969,684.133042
| 4
| 0
| 92
| 0.725825
| false
|
CBR-0001491791
|
CUS-90181434
| 2024-11-12T00:00:00
| 651
| 186,217.722748
| 3
| 0
| 37
| 0.42924
| false
|
CBR-0000596902
|
CUS-45064977
| 2024-06-21T00:00:00
| 667
| 5,040,157.256328
| 4
| 0
| 72
| 0.057104
| false
|
CBR-0001504714
|
CUS-56219237
| 2024-02-08T00:00:00
| 584
| 15,895,263.895571
| 3
| 0
| 44
| 0.186844
| false
|
CBR-0001521012
|
CUS-59987552
| 2024-05-22T00:00:00
| 492
| 118,652.174304
| 3
| 1
| 22
| 0.167946
| true
|
CBR-0000391798
|
CUS-81140038
| 2024-08-06T00:00:00
| 642
| 1,028,896.548759
| 4
| 1
| 97
| 0.135625
| false
|
CBR-0000129707
|
CUS-54338870
| 2024-03-19T00:00:00
| 593
| 3,088,582.861042
| 5
| 0
| 20
| 0.170648
| false
|
CBR-0001287570
|
CUS-52444067
| 2024-07-06T00:00:00
| 670
| 410,557.10559
| 3
| 0
| 62
| 0.02733
| false
|
CBR-0001447813
|
CUS-34979679
| 2024-02-16T00:00:00
| 601
| 133,986.435913
| 3
| 0
| 37
| 0.312651
| false
|
CBR-0000467836
|
CUS-10978256
| 2024-07-18T00:00:00
| 545
| 83,404.005124
| 2
| 0
| 69
| 0.286206
| false
|
CBR-0001762379
|
CUS-31333206
| 2024-08-02T00:00:00
| 633
| 2,693,723.739719
| 8
| 1
| 95
| 0.233767
| false
|
CBR-0001334635
|
CUS-50430371
| 2024-10-22T00:00:00
| 451
| 51,700.716442
| 3
| 2
| 92
| 0.146882
| false
|
CBR-0000108622
|
CUS-64391883
| 2024-01-29T00:00:00
| 717
| 2,484,851.504264
| 2
| 1
| 78
| 0.0916
| false
|
CBR-0000533949
|
CUS-42117222
| 2024-08-03T00:00:00
| 557
| 4,006,613.817657
| 1
| 1
| 67
| 0.623405
| true
|
CBR-0000521521
|
CUS-49952347
| 2024-02-17T00:00:00
| 644
| 93,663.289759
| 2
| 0
| 74
| 0.231444
| true
|
CBR-0000161960
|
CUS-35785213
| 2024-07-27T00:00:00
| 669
| 657,274.078675
| 2
| 1
| 56
| 0.168302
| false
|
CBR-0001850312
|
CUS-91573703
| 2024-05-05T00:00:00
| 732
| 69,804.526937
| 4
| 0
| 63
| 0.071131
| true
|
CBR-0001100412
|
CUS-95990976
| 2024-06-13T00:00:00
| 598
| 73,446.971186
| 2
| 0
| 32
| 0.174323
| false
|
CBR-0001121210
|
CUS-13372049
| 2024-07-09T00:00:00
| 696
| 793,259.009334
| 5
| 1
| 89
| 0.269387
| false
|
CBR-0000772495
|
CUS-45903927
| 2024-02-28T00:00:00
| 677
| 425,214.220164
| 3
| 1
| 24
| 0.081291
| false
|
CBR-0000064744
|
CUS-27837046
| 2024-07-10T00:00:00
| 492
| 173,198.822328
| 6
| 0
| 58
| 0.150279
| false
|
CBR-0001800528
|
CUS-81623194
| 2024-10-04T00:00:00
| 481
| 338,392.727637
| 3
| 1
| 70
| 0.379914
| false
|
CBR-0001008402
|
CUS-34514579
| 2024-05-04T00:00:00
| 652
| 1,753,240.820902
| 1
| 0
| 115
| 0.261951
| false
|
CBR-0001822173
|
CUS-82544255
| 2023-12-07T00:00:00
| 590
| 106,236.006736
| 4
| 1
| 119
| 0.045691
| false
|
CBR-0000261173
|
CUS-35599017
| 2024-02-19T00:00:00
| 732
| 2,544,988.845637
| 1
| 0
| 107
| 0.316982
| false
|
CBR-0001870332
|
CUS-37144255
| 2023-12-31T00:00:00
| 573
| 320,788.385525
| 2
| 0
| 39
| 0.138424
| false
|
CBR-0001282167
|
CUS-99506512
| 2024-11-06T00:00:00
| 759
| 731,271.357931
| 3
| 1
| 50
| 0.056471
| false
|
CBR-0000573694
|
CUS-32562411
| 2024-03-17T00:00:00
| 688
| 104,615.035409
| 3
| 0
| 96
| 0.166904
| true
|
CBR-0000515735
|
CUS-24172679
| 2024-01-30T00:00:00
| 556
| 1,537,795.83374
| 4
| 0
| 96
| 0.481885
| false
|
CBR-0000579596
|
CUS-54100673
| 2024-04-28T00:00:00
| 606
| 37,380.118774
| 1
| 0
| 73
| 0.33962
| false
|
CBR-0000002822
|
CUS-12843236
| 2024-08-05T00:00:00
| 607
| 61,372.08491
| 3
| 0
| 12
| 0.406617
| false
|
CBR-0000018481
|
CUS-11767588
| 2023-12-19T00:00:00
| 569
| 4,069,551.6514
| 1
| 1
| 100
| 0.74299
| true
|
CBR-0001264692
|
CUS-45226928
| 2024-05-15T00:00:00
| 832
| 13,290.835667
| 2
| 1
| 106
| 0.39147
| false
|
CBR-0000523782
|
CUS-17444987
| 2024-03-21T00:00:00
| 575
| 455,980.549324
| 3
| 0
| 19
| 0.180546
| false
|
End of preview. Expand
in Data Studio
Credit Bureau Records
Dataset Description
Nigerian credit bureau data with credit risk labels
This is a production-grade synthetic dataset with authentic Nigerian banking context, designed for credit risk modeling, creditworthiness assessment, and lending optimization.
Key Features
- 🇳🇬 Nigerian Context: Real bank names, states, demographics
- 📊 ML-Ready Labels: High risk flag (20% prevalence)
- ⚡ Large Scale: 2,000,000 rows
- 🎯 Realistic Distributions: Normal credit scores, lognormal debt amounts, account distributions
- 📅 Temporal Coverage: 2023-01-01 to 2024-12-31
Dataset Structure
Splits
- Train: 1,400,000 rows (70%)
- Validation: 300,000 rows (15%)
- Test: 300,000 rows (15%)
Schema
Key columns: record_id, customer_id, report_date, credit_score, total_debt_ngn, active_accounts, delinquent_accounts, payment_history_months, credit_utilization, high_risk
Usage
from datasets import load_dataset
# Load full dataset
dataset = load_dataset("electricsheepafrica/nigerian_credit_bureau")
# Load specific split
train_data = load_dataset("electricsheepafrica/nigerian_credit_bureau", split="train")
Labels
- Type: High risk flag (20% prevalence)
- Use Case: credit risk modeling, creditworthiness assessment, and lending optimization
Nigerian Context
Nigerian credit bureau reporting, typical credit score ranges, debt levels, payment history patterns, delinquency rates, and credit utilization behaviors reflecting the Nigerian lending landscape.
Citation
@dataset{nigerian_banking_credit_bureau,
title = {Nigerian Credit Bureau Records},
author = {Electric Sheep Africa},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/nigerian_credit_bureau}}
}
License
Apache 2.0 - Free for commercial and research use.
Contact
- Organization: Electric Sheep Africa
- Collection: Nigeria Banking & Finance Datasets
- Downloads last month
- 29
Size of downloaded dataset files:
73.3 MB
Size of the auto-converted Parquet files:
73.3 MB
Number of rows:
2,000,000