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MKTplace-data type: Fraud

BritCard: Identity, Inclusion, and the Fine Line Between Safety and Surveillance 

BritCard: Identity, Inclusion, and the Fine Line Between Safety and Surveillance

Let’s be honest. The first reaction to a new government-backed identity card like the proposed BritCard isn’t excitement — it’s suspicion.

Headlines and social media posts paint a picture of a tracking tool:

  • A way to log when you go abroad.
  • A database that can follow your every move.
  • Even fears that the government could dip directly into your bank account.

These stories get attention because they play to something real — our collective anxiety about privacy and control in the digital age.

The plan is to anchor BritCard within the existing Gov.UK One Login/Wallet infrastructure, enabling landlords, employers, banks, and public services to verify entitlements — such as right-to-work and right-to-rent — through a single secure verifier app.

This blog explores both sides of the BritCard conversation: the tangible benefits a universal digital ID could deliver and the concerns that need addressing if it’s to earn public trust. Whether you see it as a step toward inclusion or a step too far, the debate matters — because the way we design identity systems shapes how millions of people access services, prove who they are, and protect what’s theirs.

The Potential Benefits

  • Free ID for Everyone

    Passports and driving licences cost money — often over £80 — and not everyone can afford them. That’s why, even today, estimates suggest between 2 and 3.5 million adults in the UK do not have any form of recognised photo ID. For those people, everyday tasks like proving their identity for a job, rental, or bank account become unnecessarily difficult.

    A free, universal ID could change that by giving everyone the same basic proof of identity, regardless of income or background. Everyone should have the right to a free, recognised form of identification. For some, the BritCard could be their very first form of official ID — a tool that unlocks access, not just for the few, but for everyone.

  • “I Don’t Have My Document With Me — But I Have My Phone”

    We’ve all had that frustrating moment: halfway through an application, asked for a passport or licence that’s sitting in a drawer at home. With a reusable digital ID, that roadblock disappears. You carry it with you, ready to use in seconds, whether you’re applying for a loan, signing a tenancy, or verifying your age.
  • Fighting Deepfakes, Fake IDs, and Synthetic Identities

    Fraudsters thrive on weak ID checks. They exploit gaps by creating fake identities, using stolen details, or even building synthetic identities that blend real and fake information to appear legitimate. In 2024, UK victims reported over 100,000 cases of identity fraud, with losses running into the hundreds of millions.

    Criminals are already a step ahead. They’re using deepfake technology to generate highly convincing images and videos of passports, driving licences, and even live “selfie” checks. These fakes are often detected — but when they slip through the net, the results can be very costly for businesses in terms of direct losses, compliance fines, and reputational damage.

    Would the BritCard be a perfect, spoof-proof solution? Probably not. No system is. But by anchoring identity to a single, secure, government-issued credential, rather than fragmented checks across dozens of providers, it could raise the barrier significantly.

  • Inclusion for the “Thin File”

    Not everyone has a long credit history. Young people, newcomers to the UK, and international students often struggle to prove not that they exist, but where they live.

    Take Anna, a 19-year-old student from Spain arriving for university. She doesn’t have a UK credit record, isn’t on the electoral roll, and her rental agreement isn’t always accepted by banks. Today, opening a bank account might take weeks of back-and-forth. With a BritCard linked to her university enrolment and HMRC registration, her address could be confirmed instantly — letting her start life in the UK without delay.

    This kind of real-time verification would mean:

    • Faster access for genuine newcomers and young people.
    • Less frustration in everyday applications.
    • Stronger protection against fake documents, since address data would come only from verified sources.
  • One Solution Across Industries

    Today, every organisation has its own way of verifying identity. Banks, lenders, telcos, landlords, and employers all use different systems, which means customers face repeated checks, duplicated requests, and sometimes inconsistent outcomes.

    A universal digital ID like the BritCard could streamline this. Instead of juggling multiple verification systems, businesses could plug into a single, trusted credential.

  • Banks & lenders:
    Since the Immigration Act requires them to verify that customers have the right to live and work in the UK, a universal digital ID could make compliance far easier — reducing manual processes and ensuring consistency.
  • Telcos & utilities:
    Easier verification for new contracts, protecting against account fraud and “bust-out” scams.
  • Landlords & letting agents:
    Reliable right-to-rent checks without chasing paper documents.
  • Employers:
    Quicker right-to-work verification, reducing the cost and risk of manual checks.
  • E-commerce & digital services:
    Stronger age and identity checks at checkout, with less friction for genuine buyers.
  • Healthcare and public services:
    Faster onboarding with safeguards for sensitive data.
In short, the BritCard could become a common trust layer across industries, making life easier for genuine customers and raising the bar for criminals trying to exploit inconsistent processes.

What We Can Learn from Other Countries

The UK wouldn’t be the first to try a universal digital identity. Other countries have already rolled out similar schemes, with valuable lessons:
estonia flagEstonia has built one of the most advanced digital societies in the world on the back of its national ID. Citizens use it for healthcare, tax, banking, and even voting. A cryptographic flaw in 2017 forced an emergency response — a reminder that even strong systems must plan for cyber risks.
denmark flagDenmark’s MitID is used by almost all adults, proving that widespread adoption is possible. It has improved trust and convenience, though scams and social engineering remain ongoing challenges.
singapore flagSingapore’s Singpass shows how integration across public and private services can reduce friction for citizens, but also how critical it is to provide strong customer support against fraud attempts.
india flagIndia’s Aadhaar demonstrates scale and inclusion, giving hundreds of millions of people their first form of ID. But it has also highlighted the importance of legal guardrails and clear limits on how data can be used.
When designed well, digital ID systems can unlock access, improve security, and fight fraud. But every example also shows that inclusion, privacy, and resilience must be built in from day one.

The Concerns and Risks of BritCard

For the BritCard to work, public trust will be just as important as the technology itself. While the benefits are clear, there are also challenges that need to be addressed.
  • Inclusion and the Right to ID
    Every adult should have the right to a recognised identity. For some, the BritCard could be their very first form of official ID. But to live up to that promise, it must be accessible to everyone — not just those with smartphones, stable internet, or digital confidence. Without inclusive design and offline options, the very people who stand to benefit most could still be left out.
  • Privacy and Data Use
    People want to know how their data will be stored, who can access it, and for what purpose. Without clear guardrails, concerns about “too much information in one place” could undermine trust.
  • Cyber security
    Any centralised identity system will be a target for hackers. Even the most secure designs need robust contingency plans, rapid patching, and transparent communication in the event of an incident.
  • Consistency of Experience

    If the BritCard is adopted unevenly, with some industries using it fully and others sticking to older processes, users may end up facing the same frustrations as today. A smooth, consistent experience will be critical to delivering real value.

Walking the Fine Line

To some, BritCard feels like a step closer to monitoring; to others, it promises inclusion, protection, and simplicity. The truth is that it could be both — or neither — depending on how it is designed and delivered.

If the system is built with cyber security at its core, with ease of use for every citizen, and with a focus on adding real value for both consumers and businesses, then the BritCard could solve many of the frustrations we face today with passports, licences, and paper-based processes.

Get it wrong, and it risks being seen as another layer of control. Get it right, and it could be one of the most empowering tools of the digital age — tackling fraud, opening access, and proving that identity can be both secure and inclusive.

This isn’t about politics — it’s about tackling fraud, improving inclusion, and building a digital ID system that puts privacy and cyber security first.

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First-Party Fraud: The Hidden Cost

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First-Party Fraud:
The Hidden Cost of “Good” Customers

Unmasking Risk with a Unified Approach

  • jason abbott headshot

    Jason Abbott 

In the relentless battle against fraud, our industry has traditionally focused heavily on third-party attacks – the obvious criminals attempting to steal identities or hijack accounts. While crucial, this focus can obscure a far more insidious and often underestimated threat: first-party fraud (FPF).

First-party fraud occurs when a seemingly legitimate customer manipulates products or services for financial gain. Unlike external fraudsters, these individuals often use their own genuine identity, making them incredibly difficult to detect with traditional fraud detection methods. The insidious nature of FPF means it frequently slips through the cracks, masquerading as legitimate credit risk or bad debt, and quietly eroding profitability across a number of businesses globally.

The Nuances of First-Party: Beyond Just Bad Debt

FPF manifests in various forms:
  • No Intent to Repay: This is perhaps the most damaging type. Here, the applicant takes out a loan, opens a credit line, or acquires a device with a deliberate intention not to repay from the outset. They may appear creditworthy on paper, but their true aim is to default.
  • Fabricated Income/Employment: Inflating income, creating fake employment, or misrepresenting financial obligations to secure better terms or larger credit limits.
  • Bust-Out Schemes: Initially establishing a good payment history, then maxing out credit lines with no intention of repayment, often followed by disappearing or declaring bankruptcy.
  • Friendly Fraud/Chargeback Abuse: Disputing legitimate charges or feigning non-receipt of goods/services to avoid payment.
  • Early Account Closure/Churn: Using an account for a specific benefit (e.g., promotional offer, cashback) and then closing it immediately, leaving the provider out of pocket.

The core challenge with FPF, particularly “no intent to repay,” is that it blurs the lines between credit risk and outright fraud. A customer might appear to simply be a “bad credit risk” when, in fact, they are a fraudster. Traditional fraud prevention systems, often siloed from credit risk assessments, are not designed to detect this deliberate deception.

Why FPF Goes Undetected: The Blurry Line of Intent

The struggle to detect FPF stems from several factors:

  • Authentic Identity: The applicant uses their real name, address, and genuine identity documents. This makes it difficult for standard ID&V checks to flag them as fraudulent.
  • Intent is Hard to Prove: Proving intent to defraud is complex. Unlike stolen identities, where the illicit nature is clear, FPF relies on understanding behavioral anomalies and subtle red flags that indicate malicious pre-meditation.
  • Siloed Operations: Credit risk, fraud, and collections teams often operate independently, using separate data sets and disparate systems. This prevents a holistic view of the customer journey and makes it challenging to connect early application behaviors with later default patterns.
  • Data Gaps: Traditional credit models primarily focus on past payment behavior. They often lack the dynamic, real-time insights into application inconsistencies, behavioral biometrics, or device intelligence that could expose FPF.

Unifying Risk to Unmask First-Party Fraud Through Behavioral Intelligence

Effectively combating first-party fraud – especially the “no intent to repay” variant – requires a unified, data-driven approach that breaks down the traditional silos between fraud, credit risk, and even collections. This necessitates adding a crucial layer of behavioral intelligence to risk assessments.

  • Orchestrating a 360-Degree View of the Applicant: The key to unmasking intent lies in connecting seemingly disparate data points. This involves integrating vast and diverse data sources – not just credit bureau data, but alternative data, device intelligence, telecom data, and internal application history. By orchestrating this rich tapestry of information, a comprehensive profile can be built that reveals subtle inconsistencies and red flags indicative of FPF.
  • Early Detection of Fraudulent Intent through Behavioral Signals: This goes beyond traditional checks. Actively capturing and analyzing behavioral signals during the application process and beyond can provide critical insights. These include:

    • Application Behavior: How an applicant interacts with the application form (e.g., speed of completion, excessive copy/pasting, rapid changes to information, unusual navigation patterns).
    • Device Fingerprinting: Identifying suspicious device usage patterns (e.g., multiple applications from the same device but different identities, use of emulators or VPNs).
    • User Interface Anomalies: Detecting unusual interactions that deviate from typical, legitimate user behavior. These early behavioral indicators, often invisible to conventional systems, provide invaluable insights into a potential “no intent to repay” scenario, allowing for intervention before a loss occurs.
  • Advanced Machine Learning Models for Deeper Intent Detection: Leveraging this enriched dataset, including behavioral signals, powerful machine learning models can be employed. These models should be continuously learning and adapting to:

    • Identify Anomalies in Application Data: Pinpointing unusual patterns that might bypass basic checks.
    • Correlate Behavioral Flags with Risk: Understanding how specific behavioral patterns, when combined with other data, indicate a higher propensity for FPF.
    • Predict “No Intent to Repay”: By analyzing a combination of application data, behavioral signals, past repayment behaviors (across an ecosystem of lenders, if applicable), and external fraud indicators, models can generate a predictive score for intent-based fraud. This allows for proactive intervention at the application stage.

  • Real-Time, Adaptive Decisioning: FPF requires rapid response. Real-time decision engines allow organizations to instantly assess the nuanced risk of each applicant. This means legitimate customers experience seamless onboarding, while suspicious applications are flagged for further review or denied, preventing losses before they occur. The flexibility of such systems enables rapid adaptation of strategies as new FPF patterns emerge.

Connecting the Dots Across the Customer Lifecycle: A core strength lies in unifying platforms for credit risk, fraud prevention, and collections. This holistic view is paramount for FPF:

  • Integrated Data for Credit Risk: Data insights gathered during fraud detection, including behavioral signals, can directly feed into and enhance credit risk models, providing a more accurate assessment of true repayment likelihood.
  • Early Warning for Collections: By identifying FPF at the application stage or early in the account lifecycle, businesses can proactively adjust collections strategies, prioritize accounts, or even prevent the onboarding of high-risk individuals from the outset.
  • Feedback Loops for Continuous Improvement: Performance data from credit risk and collections efforts can be fed back into the fraud models, creating a powerful feedback loop that continuously refines detection capabilities.

Beyond the Bad Debt Write-Off: Preventing Fraud at the Source

First-party fraud is not simply bad debt; it’s a deliberate act of deception that demands a dedicated, intelligent solution. By moving beyond siloed operations and embracing a unified risk approach that intelligently combines traditional and behavioral data, leverages advanced machine learning, and enables real-time decisioning, businesses can effectively unmask “no intent to repay” schemes and other forms of FPF. This not only mitigates significant financial losses but also ensures that resources are focused on truly legitimate customers, fostering a more secure and profitable ecosystem for all.


Jason Abbott is a highly experienced fraud prevention leader with 18 years of expertise, currently serving as the Director of Fraud Solutions at Provenir. He specializes in application fraud, identity, and authentication, with a strong background in product management and go-to-market strategies for fraud software. Having held significant roles at major UK banks like JPMorgan Chase & Co., Barclays, and HSBC, Jason has a proven ability to deliver results across retail, corporate, and wealth sectors, actively contributing to the industry by sharing insights on evolving fraud threats. Get in touch on LinkedIn.

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  • AI-Driven Expertise and Certification. Leveraging advanced AI and machine learning, Meelo excels in fraud detection and prevention, backed by certifications and proven expertise

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Unparalleled Fraud Prevention and Risk Management with Meelo

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AdviceRobo mission is to responsibly promote financial inclusion for the next generation, globally. Younger generations possess unique attributes such as digital fluency, strong entrepreneurial spirit, and a commitment to sustainability, often overlooked by traditional financial methods. To bridge this gap, we’ve crafted an advanced data collection tool tailored for next-gen traits and behaviors.

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