Benchmark Credit Risk Strategy and Portfolio Performance

The Card Credit Risk Roundtable connects senior risk executives across credit card portfolios to benchmark key risk metrics, share emerging concerns, and evaluate the portfolio-level impact of economic conditions, regulation, and product design. Members explore how peers are adjusting to shifts in payment behavior, early signs of delinquency, and evolving customer risk profiles.

As new lending products (like BNPL) blur the lines of traditional credit, and macroeconomic uncertainty pressures balances and repayment rates, credit risk leaders must make confident decisions fast. This roundtable provides the peer intelligence and data-backed insight necessary to manage risk appetite, refine forecasting models, and stay ahead of credit cycle shifts.

Membership includes: Executive Meetings that focus on credit outlook, product-specific risks, and model performance; Custom Surveys on topics like credit line management, pro-active increases, or authorization settings; and Monthly Benchmarking of leading indicators such as delinquency by payment cycle, past-due balances, and year-over-year portfolio changes.

Benchmarking data is delivered via the VIZOR platform and helps credit risk leaders visualize emerging pressure points, validate internal models, and defend decisions across credit, fraud, and financial performance stakeholders.

Who Should Join?

Chief Credit Officers, SVPs of Credit Risk, Managing Directors of Acquisitions or Portfolio Risk, and risk executives managing general-purpose card portfolios.

Why It Matters:

Credit risk isn’t static. The Card Credit Risk Roundtable keeps you aligned with how peer portfolios are performing—and evolving—so you can protect your institution while optimizing for growth.

Hot Topics:

• Portfolio Performance and Outlook: Economic outlook and credit cycle observations, including trends in terms of transactions, outstanding’s, payment rates, entry rates, and delinquencies.
• Product and Industry Trends: Looking at new product offerings from a risk lens, such as “buy now, pay later,” and security brokerage transactions on credit cards.
• AI and Machine Learning: Leveraging new tools while adhering to regulatory requirements (e.g., adverse action and model governance).