Activity-Based Costing & Profitability

Many Fintechs price products, allocate resources, and make portfolio decisions without knowing what it truly costs to serve different customers, products, and channels. Contribution margins look healthy until operational costs are fully allocated — at which point fast-growing segments reveal themselves as unprofitable, cross-subsidisation patterns become visible, and pricing decisions made on incomplete data prove difficult to unwind. Without activity-based cost allocation and fully-loaded profitability visibility, cost reduction efforts are untargeted, pricing optimisation is guesswork, and portfolio decisions are made on revenue rather than margin.

This solution builds the cost allocation framework needed to calculate true profitability across every dimension of the business — by customer segment, product, channel, and geography — and identifies where costs can be reduced without compromising customer experience or compliance integrity.

WHAT DOES IT SOLVE?

Activity Mapping & Cost Driver Analysis

Answers: Where is operational time going, what does each activity cost, and what drives activity volume and duration?
Contains: Complete mapping of operational activities across support, onboarding, transaction processing, fraud review and account management, time allocation and resource consumption per activity type, cost per time unit by resource type, activity cost calculation, cost driver analysis, bottleneck identification

Cost-to-Serve & Segment Profitability

Answers: What is the true cost to serve each customer segment, product and geography, and which are profitable after full cost allocation?
Contains: Full cost allocation to transactions and customers across processing fees, support, infrastructure, fraud and operations, cost-to-serve calculations by customer segment, product, channel and geography, contribution margin and fully-allocated profitability by dimension, cross-subsidisation identification, profitability rankings

Multi-Dimensional Profitability Matrix

Answers: How does profitability vary across customer segments, products, channels and geographies, and which combinations create or erode value?
Contains: Profitability calculations by segment, product type, acquisition channel and geography, revenue, variable costs and margin per dimension, cross-dimensional analysis, product and service P&L, channel-specific customer quality and retention, market penetration vs profitability trade-offs

Cost Tracking & Monitoring

Answers: How are costs trending, and where are unexpected increases or drift emerging
Contains: Cost trend analysis by activity, segment and cost category, budget vs actual tracking, cost per transaction trends, anomaly detection for 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

Pricing Optimisation Model

Answers: How should pricing be adjusted by segment or product to maximise profitability without losing volume?
Contains: Segment-specific price elasticity modelling, revenue and profit impact of pricing changes, optimal pricing recommendations by segment and product, competitive positioning analysis, expected impact on volume and margin

Profitability Stress Test

Answers: How resilient is profitability to market changes, and which vulnerabilities pose the greatest risk?
Contains: Scenario modelling under adverse conditions including volume drops, cost spikes and churn increases, sensitivity analysis identifying key profit drivers, stress test simulations across regulatory, competitive and economic scenarios, risk prioritisation and mitigation recommendations

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.