COFINFAD: Colombian Fintech Financial Analytics Dataset

COFINFAD (Colombian Fintech Financial Analytics Dataset) is a dataset containing almost 12 months of transactional and demographic data from an anonymous Colombian fintech company. This dataset is designed to facilitate research in customer behavior analysis, churn prediction, and financial pattern recognition in the Latin American fintech sector.

Files

1. customer_data.csv: Contains demographic, behavioral, and derived data for each customer
2. transactions_data.csv: Contains individual transaction records

Key Features

• Customer demographics (age, gender, location, income bracket, etc.)
• Product usage (savings account, credit card, personal loan, etc.)
• Transaction history (frequency, volume, types)
• Customer engagement metrics (app usage, feature diversity)
• Customer feedback and satisfaction scores
• Derived metrics (churn probability, customer lifetime value)

Potential Applications

This dataset can be used for various research purposes, including:

• Customer churn prediction
• Customer segmentation
• Product recommendation systems
• Customer lifetime value optimization
• Financial inclusion studies
• App engagement analysis

Data Dictionary

No.	Variable Name	Definition	CSV Data Type
1	customer_id	Unique identifier for each customer	Integer
2	age	Customer's age in years	Integer
3	gender	Customer's gender	String
4	location	Customer's city and state	String
5	income_bracket	Customer's income category	String
6	occupation	Customer's job or profession	String
7	education_level	Highest level of education attained by the customer	String
8	marital_status	Customer's marital status	String
9	household_size	Number of people in the customer's household	Integer
10	acquisition_channel	How the customer was acquired (e.g., organic, referral)	String
11	customer_segment	Category assigned to the customer based on their behavior	String
12	savings_account	Whether the customer has a savings account (True/False)	Boolean
13	credit_card	Whether the customer has a credit card (True/False)	Boolean
14	personal_loan	Whether the customer has a personal loan (True/False)	Boolean
15	investment_account	Whether the customer has an investment account (True/False)	Boolean
16	insurance_product	Whether the customer has an insurance product (True/False)	Boolean
17	active_products	Number of active financial products the customer has	Integer
18	app_logins_frequency	Number of times the customer logs into the app per month	Integer
19	feature_usage_diversity	Number of unique features used by the customer in the app	Integer
20	bill_payment_user	Whether the customer uses bill payment feature (True/False)	Boolean
21	auto_savings_enabled	Whether the customer has enabled auto-savings feature (True/False)	Boolean
22	credit_utilization_ratio	Ratio of credit used to credit available	Float
23	international_transactions	Number of international transactions made by the customer	Integer
24	failed_transactions	Number of failed transactions for the customer	Integer
25	tx_count	Total number of transactions made by the customer	Integer
26	avg_tx_value	Average value of customer's transactions	Float
27	total_tx_volume	Total value of all transactions made by the customer	Float
28	first_tx	Date of the customer's first transaction	Date
29	last_tx	Date of the customer's most recent transaction	Date
30	base_satisfaction	Base satisfaction score for the customer	Float
31	tx_satisfaction	Satisfaction score based on transaction history	Float
32	product_satisfaction	Satisfaction score based on product usage	Float
33	satisfaction_score	Overall customer satisfaction score	Integer
34	nps_score	Net Promoter Score for the customer	Integer
35	last_survey_date	Date when the customer last completed a survey	Date
36	support_tickets_count	Number of support tickets opened by the customer	Integer
37	resolved_tickets_ratio	Ratio of resolved support tickets to total tickets	Float
38	app_store_rating	Customer's rating of the app in the app store	Float
39	feedback_sentiment	Sentiment analysis of customer's feedback	String
40	feature_requests	Features requested by the customer	String
41	complaint_topics	Main topics of customer's complaints	String
42	clv_segment	Customer Lifetime Value segment	String
43	monthly_transaction_count	Average number of transactions per month	Float
44	average_transaction_value	Average value of customer's transactions	Float
45	total_transaction_volume	Total value of all transactions made by the customer	Float
46	transaction_frequency	Number of transactions per day	Float
47	last_transaction_date	Date of the customer's most recent transaction	Date
48	preferred_transaction_type	Most frequent type of transaction for the customer	String
49	first_transaction_date	Date of the customer's first transaction	Date
50	weekend_transaction_ratio	Ratio of transactions made on weekends	Float
51	avg_daily_transactions	Average number of transactions per day	Float
52	customer_tenure	Length of time as a customer in months	Float
53	churn_probability	Predicted probability of customer churn	Float
54	customer_lifetime_value	Estimated total value of the customer to the business	Float
55	date	Date of a specific transaction	Date
56	amount	Amount of a specific transaction	Float
57	type	Type of a specific transaction	String

Data Preprocessing and Ethical Considerations

The data has been anonymized to protect customer privacy. Categorical variables have been encoded, and several derived features have been created to facilitate analysis. Researchers are encouraged to handle this data responsibly and in compliance with relevant data protection regulations.

Citation

If you use this dataset in your research, please cite it as follows:

Muñoz Guerrero, L. E., Ceballos, Y. F., & Trejos Rojas, L. D. (2024). COFINFAD: Colombian Fintech Financial Analytics Dataset [Dataset]. Hugging Face. https://huggingface.co/datasets/luisdavidtrejosrojas/cofinfad

License

This dataset is licensed under the Open Data Commons Attribution License (ODC-By).

Contact

For any questions or feedback regarding this dataset, please contact luisdavid.trejosrojas@gmail.com