Acquiring Party Prediction Platform for Merchant Churn

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Solution Overview

Problem

Acquiring banks face difficulty in predicting when a merchant is likely to stop using their services for payment transactions due to fluctuations in transaction volumes and shares, making it challenging to anticipate and respond to potential losses.

Innovation Solution

An acquiring party prediction platform that analyzes transaction data using modeling parameters, such as autoregressive integrated moving average (ARIMA) models, to generate predictions on transaction volumes and share trends, enabling automated alerts for acquiring banks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If acquiring banks monitor transaction data to predict merchant churn, then predictive accuracy improves, but system complexity increases

Engineering Contradiction:

Improvepredictive accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the prediction problem into multiple components: transaction volume prediction, share of total volume prediction, and churn probability prediction. Each component is modeled separately using appropriate methods (ARIMA for volume, ratio calculations for share, logistic regression for churn), which simplifies the overall system while maintaining high predictive accuracy through specialized models for each aspect.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces intermediate calculations and thresholds as mediators between raw transaction data and final churn predictions. Intermediate metrics include normalized volume ratios, share changes, and threshold comparisons that bridge the gap between complex transaction patterns and actionable churn predictions, making the system more interpretable and manageable.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If acquiring banks use multiple acquiring banks to process transactions, then competition and fee negotiation improve, but difficulty in predicting merchant churn increases

Engineering Contradiction:

Improvecompetition capabilityVSAvoidchurn prediction difficulty

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system dynamically adapts to changing transaction patterns by continuously monitoring volume and share metrics across multiple acquiring banks. The prediction model adjusts to new data patterns over time, capturing dynamic shifts in merchant behavior and acquiring bank performance, which enables accurate churn predictions even in volatile multi-bank environments.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback loops that continuously compare predicted churn probabilities with actual merchant behavior. This feedback enables the model to refine its predictions by learning from actual churn events and non-churn outcomes, improving accuracy in predicting which acquiring banks will be dropped by merchants in the multi-bank scenario.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS9558490B2Systems and methods for predicting a merchant's change of acquirer

Publication Date: 2017.01.31 MASTERCARD INT INC

AI summary

According to some embodiments, an acquiring party prediction platform may receive transaction information about a plurality of transactions associated with a merchant, and different transactions may be associated with different acquiring parties. The transaction information may be analyzed to generate a prediction that a particular acquiring party may be associated with a transaction volume below a threshold volume in the future. An indication associated with the prediction may then be transmitted.