Credit Strategy Reporting – Account Management

Introduction

This is the first in a series of articles examining consumer credit risk strategy reporting, a role that is often overlooked or under-resourced.

Having the best credit risk and operations tools, software and processing capabilities is largely meaningless if you do not have robust and comprehensive reporting in place to track and monitor all aspects of the credit life cycle.

This series will start with examining account management reporting, specifically account management of revolving products. Revolving credit has a broader range of reporting requirements than instalment credit, due to the nature of it being an ongoing credit advance tool. As such, there are a broader range of metrics and reports that should be implemented for successful revolving credit account management.

In the world of revolving credit, what you do not measure, you cannot manage. Whether you are overseeing credit card portfolios, lines of credit, or other revolving products, having the right reporting framework isn’t just good practice, it is essential for maintaining profitability, managing risk, and ensuring regulatory compliance.

Let’s explore the key reports and metrics that should be on every credit manager’s dashboard, and how these metrics interact to tell the complete story of your portfolio’s performance.

Note that this article does not focus on collections, which will be covered in the next article in this series.

Core Account Behaviour Metrics

Utilisation Rates: The Pulse of Your Portfolio

Utilisation is perhaps the most fundamental metric in revolving credit management. It is simply the percentage of available credit that customers are actually using. At the account level, utilisation is calculated as the current balance divided by the credit limit, multiplied by 100 to give a percentage.

While individual account utilisation helps identify accounts approaching their limits, you will also want to track segment utilisation to understand how different customer groups use their available credit. Your portfolio-wide utilisation gives you a sense of your overall exposure relative to total approved credit.

High utilisation signals potential risk, while very low utilisation might indicate disengaged customers who aren’t generating sufficient interest revenue. The sweet spot is customers who maintain moderate, consistent usage which generates interest income without raising red flags for overextension.

Purchase Volume and Transaction Activity

While utilisation shows the static picture, transaction activity reveals the dynamic usage patterns of your customers. The average transaction size tells you whether customers make many small purchases or a few large ones. Transaction frequency reveals how often your customers are engaging with their accounts. If you track merchant categories, you will gain valuable insights into where customers are spending.

These activity patterns help identify your most valuable customers, those who regularly use their accounts without necessarily carrying high balances. They’re also invaluable for designing targeted marketing campaigns and identifying shifts in spending behaviour that might warrant product adjustments.

Payment Behaviour

Payment patterns offer crucial insights into customer financial health and engagement. The payment-to-balance ratio shows what percentage of outstanding balance the average customer pays each month. The minimum payment rate reveals how many customers only pay the minimum due. Payment timing and payment method distribution provide additional layers of understanding about customer behaviour.

Customers who consistently make only minimum payments are your primary interest revenue generators but may also represent higher long-term risk profiles. Those who pay in full each month (often called ‘transactors’) generate less interest income but more interchange revenue and typically present lower credit risk.

Performance Metrics

Revenue Analysis

Understanding where your revenue comes from helps optimise product structures and pricing. Interest yield (interest income as a percentage of average balances) forms the foundation of revolving credit profitability.

Other revenues that are received include fee income from annual fees, late fees, and cash advance fees. Credit card portfolios also benefit from interchange revenue collected from merchants.

The interaction between these revenue streams reveals fascinating patterns. Accounts with a high utilisation generate more interest income but might incur higher credit losses.

Accounts with frequent transactions and full monthly payments generate more interchange fees but less interest.

The most profitable accounts often strike a balance between these behaviours, which you can track through metrics such as revenue per account and risk-adjusted return.

Balance Trends

Tracking how balances evolve over time provides insight into both portfolio growth and potential risks. The average balance per active account serves as a baseline, while the balance growth rate shows momentum.

Understanding balance distribution across different ranges and seasonal patterns throughout the year adds context to these numbers.

Rising balances can indicate portfolio growth (positive) or increasing consumer financial stress (potentially negative). The context matters, which is why you should track these metrics alongside economic indicators and credit quality measures to get the full picture.

Risk Management Metrics

Credit Quality Indicators

While collections metrics are outside the scope of this article, early warning signs of credit deterioration are crucial to monitor. Vintage analysis lets you compare performance of accounts by origination period, revealing trends in underwriting quality.

Credit score migration tracks shifts in customer creditworthiness over time, while utilisation spikes can signal financial distress.

Cash advance usage often correlates with higher-risk behaviour, as customers typically turn to cash advances when facing liquidity challenges. Unusual patterns in authorised user additions might indicate potential abuse or synthetic identity fraud attempts.

Credit quality rarely deteriorates overnight (unless it is fraud related). These early indicators help identify concerning trends before they manifest as delinquencies, allowing for pre-emptive credit line management or customer outreach to mitigate potential issues.

Profitability and Loss Forecasting

Sophisticated revolving credit management requires forward-looking metrics that help you anticipate future performance. Vintage forecasting models project outcomes based on historical segment data, while expected loss rates calculated from current risk indicators help you prepare for future write-offs.

Risk-adjusted return on capital (RAROC) evaluates true profitability by accounting for both current income and potential future losses.

Stress test results show how your portfolio metrics might shift under adverse economic conditions, helping you prepare contingency plans.

These predictive metrics help to balance growth objectives with risk management, ensuring that today’s account acquisition and line increase decisions don’t become tomorrow’s loss problems.

Customer Experience and Engagement Metrics

Digital Engagement

Modern revolving credit risk management increasingly depends on digital channel engagement. The percentage of customers actively using your mobile platform, adopting digital statements, and handling service interactions through self-service channels all impact your operational efficiency and customer satisfaction.

Feature utilisation patterns reveal which digital tools resonate with your customers, from spending alerts to credit score access. Customers who engage digitally typically have lower servicing costs, higher satisfaction, and stronger product loyalty.

These customers are also more responsive to digital marketing offers and balance transfer promotions, making them valuable from multiple perspectives.

Customer Satisfaction and Retention

The ultimate measure of product success is customer satisfaction and longevity. The Net Promoter Score (NPS) indicates whether your customers would recommend your product. Retention rates and voluntary closure statistics reveal long-term satisfaction.

Average customer tenure – how long accounts typically remain active – directly impacts lifetime value calculations.

These satisfaction metrics correlate strongly with long-term profitability. The acquisition cost for revolving credit products is typically high, making retention critical for a good return on investment.

Understanding why customers stay, or why they leave, informs product development and service improvement initiatives.

Putting It All Together: Integrated Reporting

The true power of these metrics emerges when they are analysed in relation to each other. Segment performance analysis breaks down key metrics by customer groups, such as credit tier, utilisation behaviour, product type, or acquisition channel. This multidimensional view helps identify your most valuable customer profiles and optimise acquisition strategies accordingly.

Looking beyond point-in-time metrics through trend analysis reveals seasonal patterns in utilisation and payment behaviour. Trend analysis also identifies the correlation between economic indicators and portfolio performance, and early warning signs of potential shifts in customer behaviour or credit quality.

For senior management, consolidated executive dashboards highlight key performance indicators against targets, year-over-year and quarter-over-quarter trends, risk indicators requiring attention, and growth and profitability metrics that drive strategic decisions.

Conclusion: From Reporting to Action

The most sophisticated reporting framework is only valuable if it drives action. Your revolving credit account management reports should be designed to trigger specific responses when metrics move outside acceptable ranges.

For example, utilisation in certain segments could prompt targeted line increase reviews. Shifts in payment behaviour might inform pricing or minimum payment policy adjustments to maintain portfolio health.

In today’s competitive environment, the revolving credit providers who thrive are those who master not just the collection of data, but its transformation into actionable insights that drive portfolio performance.

By focusing on the metrics outlined above and understanding their complex interactions, you will be well-positioned to optimise your revolving credit operations for both growth and stability.

About the Author

Jarrod McElhinney is the Chief Experience Officer at ADEPT Decisions and has been with ADEPT Decisions since 2017, playing a key role in designing and managing the platform, and ensuring that all subscribers realise direct business benefits from our solutions.

About ADEPT Decisions

We disrupt the status quo in the lending industry by providing clients with customer decisioning, credit risk consulting and training, predictive modelling and advanced analytics to level the playing field, promote financial inclusion and support a new generation of financial products.