The rise of first-party fraud: the hidden threat costing Canadian financial institutions millions

Traditional fraud controls are primarily designed to detect unauthorized actors, stolen credentials and suspicious third-party activity. They are less effective in the context of first-party fraud, when authenticated customers or applicants use valid credentials to misrepresent identity, income, affordability or intent.

Intent is the key distinction. Not every adverse outcome, costly customer behavior or misuse of a product feature is first-party fraud. A missed payment, dispute, profile change or exception request may be legitimate in one context and concerning in another. The test is whether measurable signals, viewed in context, and across all lifecycle stages, suggest deliberate misrepresentation, misuse, exploitation or rule avoidance.

Intent can be a subtle distinction to make when each customer behavior is viewed in isolation. This is why first-party fraud requires monitoring across the customer lifecycle stages, effective governance, signals identification and connection, careful outcome tagging, and coordinated responses across functions and business units. [RJ1.1]

 

A growing challenge 

First-party fraud is on the rise in Canada as well. Equifax Canada reported a 31 per cent year-over-year increase in first-party fraud between Q4 2024 and Q4 2025, with the sharpest pressure in credit cards, banking and younger consumer segments.¹ 

To place this in the broader fraud context, the Canadian Anti-Fraud Centre records C$643 million in reported fraud losses – across various fraud types – in 2024. However, government statements indicate that these reported fraud numbers may capture only 5 to 10 per cent of total fraud losses.² 

Under-reporting is particularly problematic in the case of first-party fraud. Although it represents a significant subset of total fraud losses, first-party fraud is often incorrectly recorded as credit losses, charge-offs, dispute write-offs, collections activity, goodwill credits or operating costs. 

Capco's working estimate of first-party fraud across Canadian financial institutions points to a broader economic exposure of approximately C$2.5 billion, broken out across deliberate credit misuse, dispute abuse, account misuse and associated operational costs.³

 

Understanding the problem

First-party fraud is difficult to quantify because it often looks like something else when it is first discovered. Some behaviors are clearly fraudulent from the outset such as intentional misrepresentation on an application, deliberate false disputes or carefully planned ‘bust-out’  – where the fraudster cultivates trust with institutions and then commits multiple abuses, often by maxing out credit lines.

Many others sit in the grey area between deliberate misuse, genuine error, legitimate product use and financial hardship. Here, the customer’s true intent is rarely visible from a single event. The picture only becomes clearer when behaviors are viewed alongside timing, frequency, customer history and product usage – in conjunction with supporting evidence.

Looking at first-party fraud events in terms of personas helps explain why a single type of control is often insufficient: 

• A bust-out strategist plans misuse early, builds exposure quickly, cashes out and defaults. 
• An identity fraudster may use synthetic, manipulated or inconsistent identity and affordability information. 
• A ‘friendly fraud’ opportunist may use disputes, refunds or claims as a low-risk tool. 
• A policy exploiter tests fee reversals, overdraft rules, goodwill credits or exceptions while staying below hard thresholds. 
• A stressed rationalizer may start as a legitimate customer under financial pressure, and then slide into deliberate non-repayment or deception.

Each of these behaviors may require different monitoring and responses. The stressed rationalizer may need well-governed support in accordance with bank hardship policies, before restrictions are imposed. The bust-out strategist requires ‘velocity monitoring’ to track unusually rapid changes in behavior, alongside intent scoring and cross-product exposure controls. 

The ‘friendly fraud’ opportunist, on the other hand, is likely to require dispute scoring, repeat-dispute flags and reviews of the evidence over the longer term. Finally, the policy exploiter requires exception monitoring, enterprise thresholds and consistent treatment rules.

 

The data and visibility hurdle 

The challenge for the industry is to identify and correctly categorize first-party fraud – and its subtypes – by understanding behaviors that reveal intent, deception, repeated exploitation or deliberate misuse. 

We mentioned above that first-party fraud exposure and losses are frequently underreported because they are erroneously absorbed into credit losses, charge-offs, dispute write-offs, collections activity, goodwill credits, remediation or operational expense.

If the data is not labelled accurately, institutions cannot identify and measure the risk, monitor individuals in the right way, and impose the most applicable controls. The fundamental problem is that many institutions are still organized around products and functions, with each team only seeing part of the customer story. Fraud, credit, operations, disputes and collections may each be doing their job well. However, without an accountable first-party fraud owner, with a complete end-to-end customer view to connect the signals across the journey, the enterprise can miss the broader patterns required to make correct decisions.

 

Understanding the shift

It follows that, as first-party fraud becomes more prominent, institutions need to look beyond individual products to build a clearer view of customer behavior over time. 

Product-level controls still matter, but the risk rarely stays within one product, one team or one point in the journey. An application detail, a device change, a payment pattern, a servicing request, a dispute, or a collections outcome may each seem reasonable on its own, but taken together, tell a different story.

To ensure  signals create cumulative insight, they must be consistently defined, routed to the right owners and systems, tagged with outcomes when these are known, and fed back into models, rules, controls and treatment standards. 

At Capco, we understand that the shift is not only technological. Most institutions already hold much of the data they need, spread across platforms, workflows, case tools and reports. A stronger model does not necessarily require a monolithic system. 

Instead, it requires a common customer-risk intelligence layer that connects data, uses consistent signal definitions and creates feedback loops so that teams can interpret behavior consistently and act at the right point in the customer lifecycle. 

 

What good looks like

In our work with financial institutions, we often observe strong controls within individual teams covering each stage of a customer lifecycle, but weaker cross-lifecycle coordination. 

Institutions need a more connected operating model across onboarding, servicing, transactions, disputes and collections – and this should be supported by a named accountable owner empowered to set strategy, appetite, decision rights and reporting. 

The goal should be to impose communication and coordination mechanisms across lifecycle stages and teams such as fraud, credit, KYC, AML, data and technology. Without the clear ownership role in place, teams are likely to continue meeting local, siloed metrics while the enterprise fails to build the single view of the customer necessary to manage first-party fraud.

A stronger first-party fraud model is less about adding controls, but more about connecting the decisions across the customer lifecycle. It helps the institution identify intent earlier, respond consistently and learn from outcomes, while keeping clear boundaries between confirmed first-party fraud, related customer product misuse, genuine hardship, legitimate product use and third-party risks.

Operating Model Family	What good looks like
Direction & scope	Leading institutions define first-party fraud as a distinct risk, with clear objectives, risk appetite, ownership and treatment principles. These include an explicit view of how to balance loss prevention against the customer experience: genuine customers avoid unnecessary friction while higher-risk behaviors receive the right level of challenge, review, restriction or support.
Data & decisioning	Mature organizations connect customer, account and behavioral signals over time. This moves them beyond point-in-time detection and builds a clearer view of emerging customer misuse and intent-based risk. The purpose is not to treat every signal as fraud, but to create enough context to distinguish intent, vulnerability, error, legitimate product use and third-party risk.
Controls, customer lifecycle & technology	Effective models apply controls across the customer lifecycle, from onboarding through to servicing, transactions, disputes and collections. The focus is on making the right intervention at the right point, supported by clear evidence standards, workflows and monitoring routines.
Governance & learn-back	Strong governance sets out clear ownership of first-party fraud with decision rights and escalation routes. Downstream outcomes from disputes, collections, investigations and quality reviews are then fed back into upstream policies, rules, controls, models and treatment standards as behaviors and typologies evolve.

Next steps: how institutions can respond

We recommend that Canadian financial institutions, fintechs and credit unions treat first-party fraud as a strategic operating-model priority, not another control challenge. 

The starting point is a maturity baseline assessment that allows institutions to understand, at the minimum, whether they can effectively distinguish deliberately deceitful customer behavior from legitimate activity. The assessment should test whether signals are reaching the right decision points and whether downstream lessons feed back into earlier controls. 

The findings from the assessment can then be translated into focused workstreams that act to reduce first-party fraud losses, improve customer treatment and strengthen governance. 

 

How Capco can help

Capco can help institutions assess their current-state maturity, identify the signals and customer lifecycle gaps that matter most, and translate those findings into a practical roadmap. Capco can also support the realization of the roadmap by helping institutions move from assessment and design into delivery and sustainable adoption.

 

References 
¹ https://www.equifax.ca/about-equifax/newsroom/-/intlpress/first-party-fraud-rises-amidst-economic-pressures 
² https://www.canada.ca/en/department-finance/news/2025/10/combatting-financial-fraud-protecting-canadians-against-scams-and-abuse.html 
³ Capco working estimate, based on directional exposure modelling across deliberate credit misuse, dispute abuse, account misuse and associated operational cost. This estimates broader first-party fraud economic exposure, including losses often coded as credit, dispute, charge-off or operating cost, and thus should not be directly compared with CAFC reported victim-loss figures.