Payment Method Portfolio Optimization

Most payment fintechs offer 8-12 payment methods but lack visibility into which ones drive valuable volume versus which consume integration and maintenance costs while sitting idle. Payment methods have dramatically different economics - Amex interchange runs 2x higher than Visa/Mastercard, digital wallets have different cost structures than cards, and each method requires ongoing PCI compliance, testing, and integration maintenance. Many discover that 3-4 maintained methods generate under 1% of volume.

This solution analyzes complete payment method performance - volume, costs, fraud rates, customer quality - and provides a portfolio rationalization strategy showing what to scale, maintain, or deprecate.

WHAT DOES IT SOLVE?

Payment Method Performance Analysis

• Answers: Which payment methods drive our business, how do preferences vary by market, and which are underperforming?

• What it contains: Volume and revenue by payment method and geography, processing cost comparison, authorization success rates, adoption trends over time, market-specific payment preferences and patterns

Method-Specific Customer Analysis

• Answers: Do certain payment methods attract better or worse customers, and how should this inform prioritization?

• What it contains: Customer quality metrics by payment method (LTV, retention, repeat purchase rates), segment preferences for different methods, cohort performance analysis

Cost-Benefit Analysis by Method

• Answers: What's the true total cost of ownership for each payment method, and what's the ROI?

• What it contains: Complete cost breakdown (processing fees, integration costs, maintenance, fraud losses, compliance overhead), revenue contribution analysis, ROI calculations per method

Fraud & Chargeback Analysis

• Answers: Which payment methods carry higher fraud or chargeback risk, and what's the true cost?

• What it contains: Fraud rates and patterns by payment method, chargeback frequency and costs, risk-adjusted profitability, authentication success rates by method

CORE MODULES

Descriptive & Diagnostic

Portfolio Optimization Recommendations

• Answers: Which methods should we drop, maintain, or invest in, and what's the expected impact?

• What it contains: Specific recommendations to rationalize portfolio, expected cost savings from dropping low-value methods, customer impact assessment, implementation priorities and timeline

Emerging Payment Method Assessment

• Answers: Should we add new payment methods (BNPL, A2A, crypto, wallets), and what's the business case?

• What it contains: Analysis of emerging payment method opportunities, market sizing and adoption projections, integration ROI modeling, competitive positioning analysis

ADVANCED MODULES

Predictive & Prescriptive

DELIVERABLES

Built in PowerBI, Tableau, or Looker & adhering to client's brand book

Dedicated tab per analysis plus executive summary overview

AI-generated insights and recommended actions per analysis

SQL queries built in client's database system with controlled access

Python scripts for statistical and ML models (if applicable)

Added to client's GitHub repository, or delivered as standalone package

Technical Guide: Data sources, logic, formulas & maintenance procedures

Analysis Handbook: Metric definitions, interpretation, use cases & action framework

Dashboard

Code Base

Documentation

Knowledge Transfer

Live & Recorded walkthrough of dashboard functionality and insights

Q&A session covering methodology, use cases, and recommendations

30-day post-delivery support for questions and adjustments

MAIN REQUIREMENTS

• Transaction and operational data must be accessible in a relational database

• BI Platform Subscription with data base gateway for dashboard automation.

• Relevant APIs & ETL workflows should be functional and consistent.

Data Infrastructure*

• Transaction & Payment Method Data with payment method type, success/failure status, processing costs, and timestamps

• Payment Method Configuration - Active methods, integration details, fees by method, and maintenance costs

• Customer & Account Data - Customer segments, location, transaction history, and payment method preferences by customer

• Fraud & Risk Data - Fraud flags, chargeback records, and risk scores by payment method and transaction

Data Sets

*Data infrastructure set up is out of scope. It can be provided as a separate engagement.