Datasets:

electricsheepafrica
/

africa-synth-telecom-telecom-credit-scoring-data-nigeria

customer_id stringlengths 11 11	phone_number stringlengths 14 14	operator stringclasses 4 values	assessment_date timestamp[ns]date 2025-09-30 00:00:00 2025-09-30 00:00:00	credit_score int64 300 1k	credit_rating stringclasses 4 values	tenure_months int64 1 120	avg_monthly_spend_ngn float64 500 50k	recharge_frequency_per_month int64 1 30	payment_consistency_score float64 0 1	late_payment_count int64 0 10	account_type stringclasses 2 values	loan_eligibility bool 2 classes	max_loan_amount_ngn float64 0 150k	default_risk stringclasses 3 values
CUST7884214	+2348188064475	9mobile	2025-09-30T00:00:00	766	good	47	38,033.69	19	0.61	1	prepaid	true	62,311.73	low
CUST9262918	+2347037995775	MTN	2025-09-30T00:00:00	508	fair	51	4,681.59	6	0.6	1	prepaid	false	0	low
CUST2670942	+2348177270309	9mobile	2025-09-30T00:00:00	1,000	excellent	114	37,461.29	24	0.12	2	prepaid	true	47,919.34	medium
CUST3837926	+2348059892823	Glo	2025-09-30T00:00:00	1,000	excellent	118	43,504.04	29	0.78	2	prepaid	true	104,373.86	low
CUST1683850	+2348104277310	MTN	2025-09-30T00:00:00	945	excellent	105	41,622.46	11	0.48	1	postpaid	true	41,723.86	low
CUST4299117	+2349098509080	9mobile	2025-09-30T00:00:00	765	good	69	23,632.45	1	0.6	0	postpaid	true	42,041.62	low
CUST9186097	+2348024701991	Airtel	2025-09-30T00:00:00	732	good	36	15,389.44	22	0.54	0	prepaid	true	46,119.87	medium
CUST9155225	+2349012879447	Airtel	2025-09-30T00:00:00	440	poor	32	3,240.44	11	0.5	2	prepaid	false	0	high
CUST6844919	+2348055478761	Glo	2025-09-30T00:00:00	566	fair	50	3,022.8	29	0.02	4	prepaid	false	0	high
CUST1592445	+2348175126138	9mobile	2025-09-30T00:00:00	1,000	excellent	99	27,094.05	29	0.55	1	prepaid	true	74,480.37	low
CUST4001542	+2348145751946	MTN	2025-09-30T00:00:00	373	poor	49	2,216.19	9	0.06	5	prepaid	false	0	high
CUST5644586	+2347018218245	Airtel	2025-09-30T00:00:00	1,000	excellent	95	29,890.87	25	0.9	0	prepaid	true	76,856.64	low
CUST8027577	+2349018224756	Airtel	2025-09-30T00:00:00	965	excellent	88	43,867.66	30	0.02	2	prepaid	true	56,553.66	low
CUST3811241	+2348188435039	9mobile	2025-09-30T00:00:00	545	fair	23	39,622.35	3	0.7	9	prepaid	false	0	medium
CUST3606833	+2347011717748	Airtel	2025-09-30T00:00:00	1,000	excellent	107	14,065.54	22	0.55	1	prepaid	true	20,775.8	low
CUST1834654	+2348120449947	Airtel	2025-09-30T00:00:00	593	fair	77	25,245.63	5	0.02	0	prepaid	false	0	medium
CUST2971573	+2347011709601	Airtel	2025-09-30T00:00:00	1,000	excellent	78	42,063.37	17	0.94	2	postpaid	true	112,790.87	medium
CUST2078747	+2349012056163	Airtel	2025-09-30T00:00:00	862	excellent	91	14,062.4	18	0.32	2	postpaid	true	33,524.22	medium
CUST6335343	+2349037633105	MTN	2025-09-30T00:00:00	1,000	excellent	84	36,935.11	26	0.71	2	prepaid	true	76,255.51	medium
CUST4215627	+2348146098332	MTN	2025-09-30T00:00:00	783	good	87	11,361.77	3	0.8	0	prepaid	true	25,636.19	low
CUST4321545	+2348147253723	MTN	2025-09-30T00:00:00	676	good	54	38,152.79	2	0.75	0	prepaid	true	57,613.64	low
CUST4638772	+2348167170186	MTN	2025-09-30T00:00:00	308	poor	2	5,968.51	15	0.44	4	postpaid	false	0	medium
CUST5773364	+2347067219728	MTN	2025-09-30T00:00:00	740	good	12	26,742.86	24	0.78	2	prepaid	true	39,938.76	low
CUST1334647	+2348068391251	MTN	2025-09-30T00:00:00	706	good	67	13,137.43	15	0.18	0	prepaid	true	18,212.5	low
CUST3148987	+2347088216361	Airtel	2025-09-30T00:00:00	761	good	77	19,965.93	8	0.31	1	prepaid	true	26,872.22	low
CUST5689248	+2348177515557	9mobile	2025-09-30T00:00:00	886	excellent	91	31,037.99	6	0.62	0	prepaid	true	81,176.42	low
CUST1539398	+2347069555616	MTN	2025-09-30T00:00:00	798	good	55	47,930.41	28	0.16	1	postpaid	true	81,885.32	low
CUST4438101	+2349050960283	Glo	2025-09-30T00:00:00	999	excellent	68	44,947.85	24	0.75	2	prepaid	true	108,411.26	medium
CUST1729952	+2349016347109	Airtel	2025-09-30T00:00:00	504	fair	29	9,743.35	3	0.81	7	prepaid	false	0	high
CUST6396918	+2348148670704	MTN	2025-09-30T00:00:00	631	fair	18	869.9	29	0.64	9	prepaid	false	0	medium
CUST9493877	+2347056122156	Glo	2025-09-30T00:00:00	484	poor	7	48,856.01	5	0.6	9	prepaid	false	0	high
CUST8436331	+2349014040260	Airtel	2025-09-30T00:00:00	674	good	32	22,503.92	20	0.25	2	prepaid	true	44,640.05	medium
CUST9272571	+2349058901686	Glo	2025-09-30T00:00:00	731	good	28	21,026.24	13	0.81	1	prepaid	true	29,034.12	high
CUST5359142	+2349086000328	9mobile	2025-09-30T00:00:00	722	good	44	32,133.92	2	0.82	2	prepaid	true	48,221.37	low
CUST2480711	+2348185550892	9mobile	2025-09-30T00:00:00	690	good	65	36,249.63	9	0.32	1	prepaid	true	59,907.2	low
CUST1839596	+2348106296578	MTN	2025-09-30T00:00:00	590	fair	72	35,181.67	6	0.05	9	prepaid	false	0	high
CUST3539174	+2349065432272	MTN	2025-09-30T00:00:00	518	fair	10	36,491.95	29	0.07	9	prepaid	false	0	high
CUST4478154	+2347016340435	Airtel	2025-09-30T00:00:00	891	excellent	28	38,337.01	21	0.99	2	prepaid	true	109,002.27	low
CUST9466406	+2348120381648	Airtel	2025-09-30T00:00:00	1,000	excellent	118	48,127.49	21	0.9	1	prepaid	true	122,946.11	low
CUST3950321	+2348052373046	Glo	2025-09-30T00:00:00	503	fair	39	3,518.88	1	0.97	2	prepaid	false	0	high
CUST2344652	+2348070132372	Glo	2025-09-30T00:00:00	853	excellent	92	45,901.86	21	0.08	2	prepaid	true	93,377.48	low
CUST1194359	+2348088012879	Airtel	2025-09-30T00:00:00	1,000	excellent	87	41,558.38	28	0.66	0	prepaid	true	117,452.67	low
CUST1915395	+2348146420381	MTN	2025-09-30T00:00:00	472	poor	15	45,749.79	1	0.5	4	postpaid	false	0	high
CUST7146065	+2348137260507	MTN	2025-09-30T00:00:00	836	excellent	41	15,898.43	28	0.78	2	prepaid	true	34,783.38	low
CUST5029343	+2348157182172	Glo	2025-09-30T00:00:00	931	excellent	60	21,392.01	20	0.93	1	prepaid	true	54,562.98	low
CUST4230884	+2349068496535	MTN	2025-09-30T00:00:00	987	excellent	81	37,006.2	18	0.52	0	prepaid	true	82,390.49	low
CUST9852356	+2347051041995	Glo	2025-09-30T00:00:00	955	excellent	72	12,238.48	20	0.98	2	prepaid	true	35,875.03	low
CUST4129455	+2348142305877	MTN	2025-09-30T00:00:00	720	good	78	42,810.89	5	0.17	1	prepaid	true	59,746.95	low
CUST1707478	+2348069750924	MTN	2025-09-30T00:00:00	1,000	excellent	82	48,487.78	26	0.48	1	prepaid	true	93,442.51	medium
CUST2825248	+2348133760148	MTN	2025-09-30T00:00:00	668	good	45	35,150.27	11	0.28	0	prepaid	true	70,215.52	low
CUST1093056	+2347017566788	Airtel	2025-09-30T00:00:00	1,000	excellent	99	47,154.62	16	0.78	0	postpaid	true	89,979.68	medium
CUST1350697	+2348036428232	MTN	2025-09-30T00:00:00	699	good	49	31,688.65	25	0.08	2	prepaid	true	80,530.78	low
CUST9588724	+2349013552384	Airtel	2025-09-30T00:00:00	377	poor	1	9,391.23	1	0.93	5	prepaid	false	0	high
CUST9765104	+2348069987337	MTN	2025-09-30T00:00:00	677	good	11	21,881.06	19	0.67	1	prepaid	true	27,929.88	low
CUST2406784	+2349065570588	MTN	2025-09-30T00:00:00	775	good	50	40,066.33	6	1	1	prepaid	true	52,579.33	low
CUST7173202	+2348131666502	MTN	2025-09-30T00:00:00	690	good	30	32,193.72	24	0.42	2	prepaid	true	75,116.92	high
CUST8052885	+2349070861522	Airtel	2025-09-30T00:00:00	575	fair	49	13,982.66	13	0.19	10	postpaid	false	0	high
CUST9029691	+2348022742111	Airtel	2025-09-30T00:00:00	410	poor	38	37,870.54	4	0.01	6	prepaid	false	0	medium
CUST9934635	+2348035400044	MTN	2025-09-30T00:00:00	796	good	87	11,628.47	22	0.05	2	prepaid	true	27,642.44	low
CUST5683590	+2349094409972	9mobile	2025-09-30T00:00:00	877	excellent	87	8,753.77	6	0.82	2	prepaid	true	9,223.53	high
CUST8593362	+2347014829259	Airtel	2025-09-30T00:00:00	681	good	41	33,081.38	3	0.81	1	prepaid	true	77,392.56	medium
CUST5474599	+2349013091066	Airtel	2025-09-30T00:00:00	966	excellent	94	32,209.38	11	0.67	1	prepaid	true	68,038.21	low
CUST8307085	+2349026499121	Airtel	2025-09-30T00:00:00	946	excellent	94	29,806.17	15	0.34	2	prepaid	true	45,710.51	low
CUST1163747	+2348068126368	MTN	2025-09-30T00:00:00	833	excellent	86	37,002.31	11	0.15	0	prepaid	true	64,862	medium
CUST2720853	+2348025522953	Airtel	2025-09-30T00:00:00	300	poor	2	9,621.02	3	0.27	8	prepaid	false	0	medium
CUST7600721	+2349063257545	MTN	2025-09-30T00:00:00	673	good	48	26,322.15	1	0.81	1	prepaid	true	53,630.8	low
CUST6827362	+2347068416793	MTN	2025-09-30T00:00:00	722	good	26	44,614.46	19	0.82	2	prepaid	true	87,104.44	low
CUST5162319	+2348068327720	MTN	2025-09-30T00:00:00	820	excellent	112	6,340.97	22	0.08	2	prepaid	true	9,780.85	low
CUST8207354	+2347062467841	MTN	2025-09-30T00:00:00	752	good	98	3,219.03	6	0.55	0	prepaid	true	5,552.46	low
CUST8586970	+2347013496122	Airtel	2025-09-30T00:00:00	698	good	8	30,190.97	17	0.89	1	prepaid	true	65,812.73	low
CUST6218163	+2348114423079	Glo	2025-09-30T00:00:00	1,000	excellent	109	18,253.52	30	0.2	1	prepaid	true	47,301.57	low
CUST4808450	+2348096790687	9mobile	2025-09-30T00:00:00	875	excellent	100	6,663.16	9	0.87	1	prepaid	true	18,409.53	low
CUST8491903	+2348076389699	Glo	2025-09-30T00:00:00	952	excellent	83	39,488.24	6	0.85	1	prepaid	true	75,537.17	high
CUST4621119	+2348058923956	Glo	2025-09-30T00:00:00	452	poor	10	39,370.69	25	0	5	postpaid	false	0	medium
CUST2436545	+2347083681964	Airtel	2025-09-30T00:00:00	1,000	excellent	108	31,144.86	8	0.63	1	prepaid	true	59,045.62	low
CUST4935970	+2349064456886	MTN	2025-09-30T00:00:00	854	excellent	45	10,349.96	26	0.92	0	prepaid	true	12,819.29	low
CUST7324599	+2349067339386	MTN	2025-09-30T00:00:00	343	poor	20	49,331.01	5	0.09	4	prepaid	false	0	low
CUST9335643	+2347058920567	Glo	2025-09-30T00:00:00	765	good	49	15,552.4	13	0.69	1	prepaid	true	27,960.85	medium
CUST3587333	+2348159453914	Glo	2025-09-30T00:00:00	1,000	excellent	85	42,500.21	28	0.41	1	prepaid	true	102,749.35	low
CUST8901021	+2347054585048	Glo	2025-09-30T00:00:00	842	excellent	39	22,199.49	15	0.92	2	prepaid	true	31,349.25	high
CUST3394975	+2347053159959	Glo	2025-09-30T00:00:00	890	excellent	97	14,527.92	11	0.34	0	prepaid	true	21,992.33	low
CUST5233237	+2349090623322	9mobile	2025-09-30T00:00:00	756	good	54	43,823.57	9	0.75	0	prepaid	true	86,111.7	high
CUST6733253	+2348085031340	Airtel	2025-09-30T00:00:00	940	excellent	89	45,206.77	6	0.64	2	prepaid	true	101,631.95	medium
CUST8821176	+2348119572398	Glo	2025-09-30T00:00:00	817	excellent	37	33,447.09	21	0.62	1	prepaid	true	62,121.79	medium
CUST2094719	+2347031826451	MTN	2025-09-30T00:00:00	859	excellent	115	3,898.9	9	0.5	2	prepaid	true	6,331.12	low
CUST6115794	+2347083887426	Airtel	2025-09-30T00:00:00	596	fair	15	43,527.12	21	0.22	5	prepaid	false	0	high
CUST7613949	+2349023237767	Airtel	2025-09-30T00:00:00	601	fair	71	1,432.31	17	0.37	10	postpaid	false	0	high
CUST4916792	+2348037680731	MTN	2025-09-30T00:00:00	766	good	62	2,678.96	26	0.71	2	prepaid	true	5,008.01	low
CUST8509922	+2348136907966	MTN	2025-09-30T00:00:00	578	fair	49	10,256.96	4	0.73	4	prepaid	false	0	high
CUST4220342	+2348114559985	Glo	2025-09-30T00:00:00	802	excellent	62	22,265.25	8	0.65	0	prepaid	true	44,848.41	low
CUST7826305	+2349066801269	MTN	2025-09-30T00:00:00	461	poor	28	28,682.19	9	0.1	7	prepaid	false	0	high
CUST5250467	+2348092163120	9mobile	2025-09-30T00:00:00	888	excellent	29	31,470.52	28	0.88	1	postpaid	true	36,404.45	medium
CUST6547951	+2348157679295	Glo	2025-09-30T00:00:00	719	good	97	42,614.61	4	0.05	1	prepaid	true	50,288.72	low
CUST3518060	+2348174107909	9mobile	2025-09-30T00:00:00	605	fair	53	8,867.84	2	0.6	10	prepaid	false	0	high
CUST4864264	+2347015103677	Airtel	2025-09-30T00:00:00	958	excellent	78	34,199.36	18	0.52	1	prepaid	true	47,535.48	medium
CUST2529096	+2349032514160	MTN	2025-09-30T00:00:00	933	excellent	39	21,293	30	0.96	1	prepaid	true	59,644.14	high
CUST8960913	+2349063074062	MTN	2025-09-30T00:00:00	971	excellent	99	42,856.49	25	0.16	1	prepaid	true	92,876.56	low
CUST5942969	+2348188213967	9mobile	2025-09-30T00:00:00	708	good	75	4,373.14	6	0.88	0	prepaid	true	13,111.74	medium
CUST4941115	+2347061140457	MTN	2025-09-30T00:00:00	985	excellent	115	22,528.54	13	0.14	0	prepaid	true	67,043.1	low
CUST1839020	+2348134032112	MTN	2025-09-30T00:00:00	743	good	26	43,043.63	28	0.58	1	prepaid	true	125,061.93	low

End of preview. Expand in Data Studio

Telecom Credit Scoring Data

Dataset Description

Credit worthiness assessment based on telecom usage and payment behavior

Dataset Information

Category: Financial and Fraud
Format: CSV, Parquet
Rows: 500,000
Columns: 15
Date Generated: 2025-10-05
Location: data/telecom_credit_scoring_data/

Schema

Column	Type	Sample Values
`customer_id`	String	CUST7884214
`phone_number`	String	+2348188064475
`operator`	String	9mobile
`assessment_date`	Datetime	2025-09-30 00:00:00
`credit_score`	Integer	766
`credit_rating`	String	good
`tenure_months`	Integer	47
`avg_monthly_spend_ngn`	Float	38033.69
`recharge_frequency_per_month`	Integer	19
`payment_consistency_score`	Float	0.61
`late_payment_count`	Integer	1
`account_type`	String	prepaid
`loan_eligibility`	Boolean	True
`max_loan_amount_ngn`	Float	62311.73
`default_risk`	String	low

Sample Data

customer_id   phone_number operator assessment_date  credit_score credit_rating  tenure_months  avg_monthly_spend_ngn  recharge_frequency_per_month  payment_consistency_score  late_payment_count account_type  loan_eligibility  max_loan_amount_ngn default_risk
CUST7884214 +2348188064475  9mobile      2025-09-30           766          good             47               38033.69                            19                       0.61                   1      prepaid              True             62311.73          low
CUST9262918 +2347037995775      MTN      2025-09-30           508          fair             51                4681.59                             6                       0.60                   1      prepaid             False                 0.00          low
CUST2670942 +2348177270309  9mobile      2025-09-30          1000     excellent            114               37461.29                            24                       0.12                   2      prepaid              True             47919.34       medium

Nigerian Context

This dataset incorporates authentic Nigerian telecommunications characteristics:

Geographic Coverage: Major Nigerian cities including Lagos, Abuja, Kano, Port Harcourt, Ibadan
Operators: MTN, Airtel, Glo, 9mobile with realistic market shares
Phone Numbers: Nigerian format (+234 prefixes)
Currency: Nigerian Naira (NGN)
Time Zone: West Africa Time (WAT, UTC+1)
Network Types: 2G, 3G, 4G, 5G distribution

File Formats

CSV

data/telecom_credit_scoring_data/telecom_credit_scoring_data.csv

Parquet (Recommended)

data/telecom_credit_scoring_data/telecom_credit_scoring_data.parquet

Loading the Dataset

Python (Pandas)

import pandas as pd

# Load CSV
df = pd.read_csv('data/telecom_credit_scoring_data/telecom_credit_scoring_data.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/telecom_credit_scoring_data/telecom_credit_scoring_data.parquet')

Python (PyArrow)

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/telecom_credit_scoring_data/telecom_credit_scoring_data.parquet')
df = table.to_pandas()

License

MIT License - For educational and research purposes

Citation

Nigerian Telecom Datasets - Telecom Credit Scoring Data
Generated: 2025-10-05
Category: Financial and Fraud
Rows: 500,000

Related Datasets

This dataset is part of the Nigerian Telecom Datasets collection, which includes 34 datasets covering network performance, customer behavior, financial transactions, infrastructure, geospatial data, customer experience, and emerging technologies.

Downloads last month: 33

Collection including electricsheepafrica/africa-synth-telecom-telecom-credit-scoring-data-nigeria

Amon Dîn

Collection

A collection of datasets from the Nigerian Telecommunications Sector • 34 items • Updated Oct 6, 2025 • 2