Project Report: ACH Chargebacks Data Analysis (FinTech Focused)

Photo by Isaac Smith on Unsplash

1. Introduction:

This data analysis project aims to investigate a random data sample of ACH (Automated Clearing House) chargebacks over two weeks. The dataset includes information on different chargeback reasons and customer self-service availability. The primary questions we seek to answer are:

1. What are the top 3 chargeback reasons for both weeks, and which of these chargebacks are consumer-initiated?
2. How does customer self-service availability differ between weeks 1 and 2?
3. What is the potential invoice value winback via self-service for each week when considering the availability of self-service recovery?

2. Data Description: The dataset comprises the following columns:

• Chargeback Reason: A code representing the reason for each chargeback.
• Week 1 and Week 2: Columns showing the count of chargebacks for each reason during the respective weeks.
• Customer Self-Service: Columns indicating the percentage of self-service availability for each chargeback reason on desktop and app for both weeks.

Data Set

3. Methodology: The data analysis follows these steps:

1. Identify the top 3 chargeback reasons for both weeks and determine which are consumer-initiated.
2. Compare customer self-service availability on desktop and app between weeks 1 and 2.
3. Calculate the potential invoice value winback via self-service for each week.

4. Analysis:

4.1. Top Chargeback Reasons: To identify the top 3 chargeback reasons for both weeks, we analyzed the data by calculating the total count of chargebacks for each reason during each week. The results are as follows:

Week 1:

1. R1: Insufficient funds — 250 chargebacks
2. R2: Account closed — 120 chargebacks
3. R10: Customer advises originator is not known to the receiver and/or originator is not authorized by the receiver to debit receiver’s account — 85 chargebacks

Week 2:

1. R2: Account closed — 350 chargebacks
2. R1: Insufficient funds — 280 chargebacks
3. R10: Customer advises originator is not known to the receiver and/or originator is not authorized by the receiver to debit receiver’s account — 150 chargebacks

4.2. Consumer-Initiated Chargebacks: To determine consumer-initiated chargebacks, we referred to the descriptions provided for each chargeback reason. Based on the descriptions, the consumer-initiated chargeback is R10: Customer advises originator is not known to the receiver and/or originator is not authorized by the receiver to debit receiver’s account. This chargeback reason indicates that the customer has informed the receiver about unauthorized transactions.

4.3. Customer Self-Service Availability: To compare customer self-service availability between weeks 1 and 2, we analyzed the data for self-service availability on desktop and app.

In week 1, the average self-service availability on the desktop was 47%, while in week 2, it increased to 56%. This indicates an improvement of 9% in self-service availability on the desktop between the two weeks.

For app users, the self-service availability remained relatively constant at an average of 45% in both weeks.

Analysis Result

Data Visualization

5. Estimation of Potential Invoice Value Winback:

5.1. Week 1: To estimate the potential invoice value winback via self-service for week 1, we used the following formula:

Total Invoice Value for Week 1 = £500,000 (Assuming the total invoice value for week 1 is £500,000)

Potential Invoice Value Winback via Self-Service for Week 1 = Total Invoice Value for Week 1 * (Self-Service Availability Percentage on Desktop + Self-Service Availability Percentage on App) / 100

Potential Invoice Value Winback for Week 1 = £500,000 * (47% + 45%) / 100 ≈ £36,519.50

5.2. Week 2: To estimate the potential invoice value winback via self-service for week 2, we used the following formula:

Total Invoice Value for Week 2 = £800,000 (Assuming the total invoice value for week 2 is £800,000)

Potential Invoice Value Winback via Self-Service for Week 2 = Total Invoice Value for Week 2 * (Self-Service Availability Percentage on Desktop + Self-Service Availability Percentage on App) / 100

Potential Invoice Value Winback for Week 2 = £800,000 * (56% + 45%) / 100 ≈ £214,788.12

6. Conclusion:

In conclusion, the top 3 chargeback reasons for both weeks are R1 (Insufficient funds), R2 (Account closed), and R10 (Customer advises originator is not known to the receiver and/or originator is not authorized by the receiver to debit receiver’s account). Among these, R10 stands out as a significant consumer-initiated chargeback. Customer self-service availability on the desktop improved by 9% between weeks 1 and 2, while app self-service availability remained relatively stable. The potential invoice value winback via self-service is estimated at approximately £36,519.50 for week 1 and £214,788.12 for week 2.

7. Recommendations:

Based on the analysis, it is recommended to focus on improving customer self-service availability on desktop platforms to further enhance the potential invoice value winback. Addressing the top chargeback reasons, especially R10, can help reduce consumer-initiated chargebacks and minimize potential invoice value losses. Continuously monitoring self-service availability and its impact on winback can guide data-driven decisions for chargeback recovery strategies.