For many banks, first-party fraud has become a silent drain on profitability. On paper, it often looks like classic credit risk: an account books, goes delinquent, and ultimately charges off. But a growing share of those early charge-offs is driven by something else entirely: customers who never intended to pay you back.
That distinction matters. When first-party fraud is misclassified as credit risk, banks risk overstating credit loss, understating fraud exposure, and missing opportunities to intervene earlier.
In our recent Consumer Banker Association (CBA) partner webinar, “Fraud or Financial Distress? How to Differentiate Fraud and Credit Risk Early,” Experian shared new data and analytics to help fraud, risk and collections leaders see this problem more clearly. This post summarizes key themes from the webinar and points you to the full report and on-demand webinar for deeper insight.
Why first-party fraud is a growing issue for banks
Banks are seeing rising early losses, especially in digital channels. But those losses do not always behave like traditional credit deterioration. Several trends are contributing:
- More accounts opened and funded digitally
- Increased use of synthetic or manipulated identities
- Economic pressure on consumers and small businesses
- More sophisticated misuse of legitimate credentials
When these patterns are lumped into credit risk, banks can experience:
- Inflation of credit loss estimates and reserves
- Underinvestment in fraud controls and analytics
- Blurred visibility into what is truly driving performance
Treating first-party fraud as a distinct problem is the first step toward solving it.
First-payment default: a clearer view of intent
Traditional credit models are designed to answer, “Can this customer pay?” and “How likely are they to roll into delinquency over time?” They are not designed to answer, “Did this customer ever intend to pay?”
To help banks get closer to that question, Experian uses first-payment default (FPD) as a key indicator. At a high level, FPD focuses on accounts that become seriously delinquent early in their lifecycle and do not meaningfully recover.
The principle is straightforward:
- A legitimate borrower under stress is more likely to miss payments later, with periods of cure and relapse.
- A first-party fraudster is more likely to default quickly and never get back on track.
By focusing on FPD patterns, banks can start to separate cases that look like genuine financial distress from those that are more consistent with deceptive intent.
The full report explains how FPD is defined, how it varies by product, and how it can be used to sharpen bank fraud and credit strategies.
Beyond FPD: building a richer fraud signal
FPD alone is not enough to classify first-party fraud. In practice, leading banks are layering FPD with behavioral, application and identity indicators to build a more reliable picture.
At a conceptual level, these indicators can include:
- Early delinquency and straight-roll behavior
- Utilization and credit mix that do not align with stated profile
- Unusual income, employment, or application characteristics
- High-risk channels, devices, or locations at application
- Patterns of disputes or behaviors that suggest abuse
The power comes from how these signals interact, not from any one data point. The report and webinar walk through how these indicators can be combined into fraud analytics and how they perform across key banking products.
Why it matters across fraud, credit and collections
Getting first-party fraud right is not just about fraud loss. It impacts multiple parts of the bank.
Fraud strategy
Well-defined quantification of first-party fraud helps fraud leaders make the case for investments in identity verification, device intelligence, and other early lifecycle controls, especially in digital account opening and digital lending.
Credit risk and capital planning
When fraud and credit losses are blended, credit models and reserves can be distorted. Separating first-party fraud provides risk teams a cleaner view of true credit performance and supports better capital planning.
Collections and customer treatment
Customers in genuine financial distress need different treatment paths than those who never intended to pay. Better segmentation supports more appropriate outreach, hardship programs, and collections strategies, while reserving firmer actions for abuse.
Executive and board reporting
Leadership teams increasingly want to understand what portion of loss is being driven by fraud versus credit. Credible data improves discussions around risk appetite and return on capital.
What leading banks are doing differently
In our work with financial institutions, several common practices have emerged among banks that are getting ahead of first-party fraud:
1. Defining first-party fraud explicitly
They establish clear definitions and tracking for first-party fraud across key products instead of leaving it buried in credit loss categories.
2. Embedding FPD segmentation into analytics
They use FPD-based views in their monitoring and reporting, particularly in the first 6–12 months on book, to better understand early loss behavior.
3. Unifying fraud and credit decisioning
Rather than separate strategies that may conflict, they adopt a more unified decisioning framework that considers both fraud and credit risk when approving accounts, setting limits and managing exposure.
4. Leveraging identity and device data
They bring in noncredit data — identity risk, device intelligence, application behavior — to complement traditional credit information and strengthen models.
5. Benchmarking performance against peers
They use external benchmarks for first-party fraud loss rates and incident sizes to calibrate their risk posture and investment decisions.
The post is meant as a high-level overview. The real value for your teams will be in the detailed benchmarks, charts and examples in the full report and the discussion in the webinar.
If your teams are asking whether rising early losses are driven by fraud or financial distress, this is the moment to look deeper at first-party fraud.
Download the report: “First-party fraud: The most common culprit”
Explore detailed benchmarks for first-party fraud across banking products, see how first-payment default and other indicators are defined and applied, and review examples you can bring into your own internal discussions.
Hear Experian experts walk through real bank scenarios, FPD analytics and practical steps for integrating first-party fraud intelligence into your fraud, credit, and collections strategies.
First-party fraud is likely already embedded in your early credit losses. With the right analytics and definitions, banks can uncover the true drivers, reduce hidden fraud exposure, and better support customers facing genuine financial hardship.
