Activity-Based Cost-to-Serve

Most payment fintechs track revenue per customer but lack visibility into the true cost of serving different customer segments. The full cost picture - including processing fees (often 2-4% of revenue), support overhead, infrastructure allocation, fraud losses, and operational time - typically lives across multiple systems with no unified view. Without activity-based cost tracking, companies discover too late that their fastest-growing customer segment is unprofitable after accounting for support tickets, manual interventions, and processing costs.

This solution builds a comprehensive activity-based cost model showing true cost-to-serve for each customer segment, identifies which operational activities consume the most resources, and reveals which customer types are subsidizing others.

WHAT DOES IT SOLVE?

Activity Mapping & Time Tracking

• Answers: Where is operational time actually going, and which activities consume the most resources?

• What it contains: Complete mapping of operational activities (support, onboarding, transaction processing, fraud review, account management); time allocation per activity type; resource consumption patterns; bottleneck identification

Activity Costing & Driver Analysis

• Answers:What's the cost per activity, and what are the major cost drivers?

• What it contains: Cost per time unit calculation for each resource type (support staff, operations, compliance); time required per activity measurement; activity cost calculation; cost driver analysis (what drives activity volume and duration)

Cost-to-Serve Analysis

• Answers: What's the true cost to serve & its breakdown across customers, segments & products?

• What it contains: full cost allocation to transactions & customers (processing fees, support, infrastructure, fraud, operations), CTS calculations by customer segment, product, geography, and transaction characteristics

Cost Tracking & Monitoring

• Answers: How are our costs trending over time, and where are we seeing unexpected increases or drift?

• What it contains: Cost trend analysis by activity, segment, and cost category; budget vs actual cost tracking; cost per transaction trends; anomaly detection for unusual cost spikes; variance analysis by cost driver; early warning indicators for cost escalation

CORE MODULES

Descriptive & Diagnostic

Customer Lifetime Cost Modeling

• Answers: How do costs evolve over a customer's lifetime, and what's the total cost of ownership?

• What it contains: Cost projection over customer lifetime (onboarding front-loaded, support ongoing); cohort-based cost patterns; integration with LTV analysis for true profitability; total cost of ownership by segment

Support Cost Prediction Model

• Answers: Which customer types or behaviors will generate high support costs, and how can we forecast support resource needs?

• What it contains: ML-based prediction of support costs by customer segment and behavior; early identification of high-support-cost customers; support resource demand forecasting; customer onboarding flags for likely high-touch needs; cost impact modeling of customer mix changes

Optimised Cost Reduction Initiatives

• Answers: What specific cost reduction opportunities carry the lowest risk to customer satisfaction, compliance, and process integrity?

• What it contains: Risk-scored cost reduction opportunities; customer experience impact assessment per recommendation; compliance and regulatory risk evaluation; process integrity safeguards; prioritized initiatives balancing savings with risk; quick wins vs strategic optimizations; expected cost savings with risk mitigation strategies

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 & Processing Data - All transactions with processing costs, payment methods, and customer segment attribution

• Operational Activity Logs - Support tickets, manual reviews, exception handling, onboarding tasks, and staff time allocation

• Customer & Segment Data - Customer segments, account status, product usage, and activity levels

• Cost Data - Infrastructure costs, staffing costs, vendor fees, fraud losses, and overhead allocation

Data Sets

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