Product-Level Profitability Analysis

Overview

Decomposes banking product profitability to the unit economics level using funds transfer pricing (FTP), activity-based costing (ABC), credit cost allocation, and risk-adjusted return metrics. Enables management to identify value-creating vs. value-destroying products, optimize the product mix, calibrate pricing, and allocate capital efficiently across business lines.

When to Use

Evaluating the economic contribution of individual banking products
Performing product rationalization or product line simplification reviews
Calibrating product pricing against FTP-adjusted breakeven
Supporting ALCO capital allocation decisions across business lines
Analyzing cross-subsidy dynamics between products and customer segments
Benchmarking product economics against peers or market rates

Required Inputs

| Input | Description | Format | |-------|-------------|--------| | Product balances | Average balances by product line (assets and liabilities) | Balance data | | Customer rates | Interest rates charged/paid by product | Rate schedule | | FTP rates | Transfer pricing rates by product tenor/repricing profile | FTP schedule | | Fee income | Non-interest income attributable to each product | Revenue data | | Direct costs | Direct operating costs by product (origination, servicing, collections) | Cost data | | Indirect costs | Allocated overhead (technology, compliance, management) | Allocation methodology | | Credit costs | Expected loss and provision expense by product portfolio | Credit data | | Capital allocation | RWA and economic capital by product | Capital data | | Volume data | Account counts, transaction volumes, utilization rates | Activity data |

Methodology

Step 1 — Calculate FTP-Adjusted Net Interest Margin by Product

For each product, compute the FTP spread:

Asset products (loans, investments): FTP Spread = Customer Rate − FTP Rate

The FTP rate represents the internal cost of funding the asset at its maturity/repricing profile
Positive FTP spread = product contributes positively to NII after funding cost

Liability products (deposits): FTP Spread = FTP Rate − Customer Rate

The FTP rate represents the internal value of the funding provided to treasury
Positive FTP spread = product provides funding at a cost below its internal value

FTP-adjusted NII per product: NII_product = FTP Spread × Average Balance

Decompose FTP into components:

Base rate (risk-free benchmark at the product's repricing tenor)
Liquidity premium (compensation for LCR/NSFR impact of the product)
Credit spread (for asset products, the funding spread above risk-free)
Option cost (for products with embedded options: prepayment, early withdrawal)

Step 2 — Allocate Non-Interest Income

Assign fee and non-interest income directly to products where possible:

Direct fees: Origination fees, annual fees, transaction fees, late fees, interchange
Indirect fees: Wealth management referral fees, cross-sell revenue attributable to the relationship
Ancillary income: Insurance premiums, brokerage commissions linked to the product relationship

Apply the revenue attribution principle: Revenue is attributed to the product that generates the customer interaction, not the product where it is booked. Cross-sell revenue should be shared using a defined attribution model.

Step 3 — Allocate Operating Costs Using Activity-Based Costing

Apply ABC methodology to allocate costs accurately:

Direct costs (fully traceable):

Origination/underwriting costs per unit originated
Servicing costs per account per month
Collections costs per delinquent account
Technology costs directly attributable (product-specific platforms)

Indirect costs (allocated):

Branch network costs: Allocate based on transaction volumes or customer visits by product
Technology infrastructure: Allocate based on system usage, data storage, or processing volumes
Compliance and regulatory: Allocate based on regulatory intensity (AML monitoring costs higher for transaction accounts)
Management and overhead: Allocate using a cost driver hierarchy (headcount, revenue, or balance-based)

Cost allocation hierarchy:

Direct assignment (preferred — highest accuracy)
Activity-based allocation (where direct assignment not possible)
Balance-based or revenue-based allocation (last resort — lowest accuracy)

Clearly identify the allocation methodology tier used for each cost category.

Step 4 — Compute Credit Costs and Expected Losses

Allocate credit-related costs to asset products:

Expected credit loss (ECL): PD × LGD × EAD for the product portfolio, reflecting through-the-cycle loss expectations
Provision expense: Actual provision charges recorded in the period (may differ from ECL due to IFRS 9 staging, macro scenario weights)
Net charge-offs: Actual losses realized, net of recoveries
ECL cost rate: ECL / Average Balance (expressed in bps annually)

For liability products, credit cost is zero but allocate fraud loss costs where applicable.

Step 5 — Calculate Risk-Adjusted Returns

Compute risk-adjusted profitability metrics for each product:

Product Economic Profit (EP): EP = FTP-Adjusted NII + Fee Income − Operating Costs − Credit Costs − Capital Charge

Where Capital Charge = Allocated RWA × Target CET1 Ratio × Cost of Equity

Key return metrics:

RAROC: EP / Economic Capital — risk-adjusted return on capital
RoRWA: Net Income (after all costs) / RWA — return on regulatory capital
EP per account: EP / Number of accounts — unit economics measure
EP per dollar of balance: EP / Average Balance — balance sheet efficiency
Cost-to-income ratio: Operating Costs / (NII + Fees) — operational efficiency

Hurdle rate test:

Products with RAROC above the cost of equity are value-creating
Products with RAROC below the cost of equity destroy shareholder value
Products with negative EP should be examined for cross-subsidy justification or rationalization

Step 6 — Analyze Cross-Subsidy Dynamics

Identify and quantify cross-subsidy flows between products:

Map which products subsidize others (e.g., low-rate checking accounts funded by high-spread lending)
Assess whether cross-subsidies are intentional (strategic bundling) or accidental (mispricing)
Evaluate the customer relationship economics: Does a loss-making product anchor a profitable relationship?
Compute the relationship-level EP: Sum of all product EPs for multi-product customers

Cross-subsidy matrix: | Product | Standalone EP | Relationship Contribution | Net Position | |---------|---------------|---------------------------|-------------| | Checking | Negative | High anchoring value | Subsidized | | Mortgage | Low positive | Drives checking + wealth | Contributor | | Wealth | High positive | Primary profit driver | Subsidizer |

Step 7 — Generate Optimization Recommendations

Based on the analysis, recommend specific actions:

Pricing optimization:

Products priced below FTP-adjusted breakeven: Identify repricing opportunity
Products with RAROC significantly above hurdle: Assess competitive positioning and market share growth opportunity
Fee income opportunities: Identify below-market fee schedules

Product rationalization:

Products with negative EP, no cross-subsidy justification, and declining volumes: Candidates for discontinuation
Products with low EP but high strategic value (customer acquisition, retention): Re-evaluate pricing and cost structure

Capital reallocation:

Redirect capital from low-RAROC products to high-RAROC products
Quantify the incremental EP from reallocation (RAROC differential × capital shifted)

Cost reduction:

Products with cost-to-income ratios significantly above peers: Target for operational efficiency improvement
Migration from high-cost channels (branch) to low-cost channels (digital)

Output Specification

# Product Profitability Analysis — [Period]

## Product Economics Summary
| Product | Avg Bal ($M) | FTP Spread (bps) | Fee ($M) | OpEx ($M) | Credit ($M) | EP ($M) | RAROC | RoRWA |
|---------|-------------|------------------|----------|-----------|-------------|---------|-------|-------|

## Product Ranking by RAROC
| Rank | Product | RAROC | Hurdle Rate | Value Creation | Recommendation |
|------|---------|-------|-------------|----------------|----------------|

## FTP Decomposition
| Product | Customer Rate | FTP Rate | Base | Liquidity | Credit | Option | FTP Spread |
|---------|--------------|----------|------|-----------|--------|--------|-----------|

## Cost Allocation Summary
| Product | Direct Cost | Allocated Cost | Total Cost | Cost/Account | Cost-to-Income |
|---------|------------|----------------|-----------|-------------|---------------|

## Cross-Subsidy Analysis
| Subsidizing Product | Subsidized Product | Subsidy Amount ($M) | Justification |
|--------------------|-------------------|--------------------|----|

## Optimization Recommendations
| # | Action | Product | EP Impact ($M) | Implementation | Priority |
|---|--------|---------|----------------|----------------|----------|

Analysis Framework

Apply the Product Value Chain framework:

Originate: What does it cost to acquire the customer and originate the product?
Fund: What is the internal cost (FTP) of funding the asset or value of the deposit?
Service: What is the ongoing cost to maintain and service the product?
Risk: What credit, market, or operational losses does the product generate?
Capitalize: What regulatory and economic capital does the product consume?
Return: What is the net economic value after accounting for all five prior stages?

Products that fail to generate positive economic value at Stage 6, after accounting for relationship-level cross-subsidies, are candidates for repricing, restructuring, or rationalization.

Examples

Example — Product RAROC Analysis: "Commercial real estate lending generates the highest RAROC at 18.2%, driven by a 285bps FTP spread and strong fee income from origination and unused commitment fees. However, it consumes 34% of total allocated capital at an RWA density of 92%. Residential mortgages, by contrast, earn a RAROC of only 8.4% — below the 12% hurdle rate — reflecting compressed FTP spreads of 95bps and elevated servicing costs of $145/loan/year. The mortgage product destroys $12M of shareholder value annually but anchors $3.2B of core deposit relationships with combined positive EP."

Example — Cross-Subsidy Insight: "The free checking account product generates negative EP of -$28M annually (operating cost of $164/account exceeds the FTP value of $112/account). However, 72% of checking customers hold at least one additional product with the bank. Relationship-level analysis shows that multi-product households anchored by checking generate average EP of $340/household, making the cross-subsidy economically rational. Recommendation: Maintain the product but migrate servicing to digital channels to reduce cost-to-serve by $35/account."

Guidelines

Always use FTP-adjusted margins, never gross interest margins, for product economics
Apply ABC costing where possible; clearly flag balance-based allocations as lower accuracy
Include the capital charge in all EP calculations — products consuming capital must earn above the cost of equity
Assess cross-subsidies at the relationship level before recommending product rationalization
Express RAROC, RoRWA, and EP in consistent units for cross-product comparability
Benchmark product economics against peers and best-in-class to identify improvement potential
Update product profitability analysis at least quarterly to capture rate and volume changes

Validation Checklist

[ ] FTP rates correctly matched to each product's repricing/maturity profile
[ ] FTP spreads decomposed into base, liquidity, credit, and option components
[ ] Fee income attributed to originating product with cross-sell allocation documented
[ ] Operating costs allocated using ABC hierarchy with methodology tier identified
[ ] Credit costs reflect through-the-cycle expected losses, not single-period provisions
[ ] Capital charge computed using allocated RWA × target CET1 × cost of equity
[ ] RAROC compared to cost-of-equity hurdle rate for value creation assessment
[ ] Cross-subsidy analysis performed at relationship level before rationalization recommendations
[ ] Optimization recommendations quantified with EP impact
[ ] Peer benchmarking applied to cost ratios and return metrics