a) Security and protection of citizens

The primary purpose of digital identity is protection. Users whose identities are stolen suffer dramatic consequences: loans taken out in their name, administrative disputes, damaged online reputations. Having a robust digital identity based on reliable technical and behavioural signals helps limit these risks.

b) Trust and fluidity of exchanges

For a company, accepting a new customer involves a risk. Digital identity provides the necessary elements to establish a trust score: is this a real, consistent person who has been active for a long time? This trust then facilitates exchanges, reduces friction (simplified KYC, smooth user journey) and improves the customer experience.

c) Sovereignty and independence

Today, proving one’s identity online often involves major private players (connection via Google, Apple or Facebook). However, delegating this strategic function to a few companies poses a problem of sovereignty. European states are seeking to regain control in order to avoid excessive dependence and guarantee data protection.

d) Inclusion and equal access

Digital identity must not become a factor of exclusion. People who are digitally excluded (the elderly, rural areas, vulnerable populations) must have access to simple and accessible solutions. Equity requires an inclusive design of these tools.

2. Future prospects

By 2030, digital identity could undergo three major developments:

Increased standardisation: adoption of international standards enabling seamless recognition between countries and services.

Biometric integration: enhanced association with biometric fingerprints (voice, face, fingerprint) to further secure access.

Enhanced user control: emergence of solutions where users decide which elements of their identity to share, depending on the context (e.g. proving they are of legal age without revealing their date of birth).

In a nutshell…

Digital identity is no longer a technical curiosity. It has become the beating heart of digital societies. It protects, streamlines and empowers, but also raises questions about surveillance and sovereignty.

By understanding it, decision-makers and citizens have an essential lever for navigating a world where the virtual and the real are inseparable. Ultimately, digital identity is the identity card of the digital age: intangible but decisive, invisible but unavoidable.

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1 . Defining digital identity:

Unlike civil identity, which is established and certified by the state, digital identity takes many forms. It is based on four main dimensions:

• Declarative data: surname, first name, email address, telephone number, address. This information is provided voluntarily, but can be misused/“imitated”.
• Technical fingerprints: each connected device generates a unique signature (IP address, configuration, sensors, time zones, cookies). These signals, invisible to the naked eye, become valuable clues for recognising a user.
• Behaviour: typing speed, connection times, location, frequency of service use. These elements are more difficult to falsify and constitute a behavioural signature that is almost biometric.
• Social and economic interactions: history of contact, payment and browsing data use. This data builds a coherent narrative… or, conversely, reveals inconsistencies typical of fraudulent events.

2. An identity in flux

Unlike a national identity card, which is fixed at the time of issue, digital identity is dynamic. Every connection, every payment, every interaction enriches this digital portrait. This dynamic provides robustness – it is difficult to simulate a consistent digital life over time – but also raises ethical questions:

How much data should be collected without infringing on privacy?

How can we ensure that users retain control over their digital identity?

What safeguards should be put in place to prevent widespread surveillance?

The GDPR in Europe and the concept of ‘self-sovereign identity’ attempt to provide answers. But the balance between security, fluidity and respect for individual freedoms remains fragile.

3. Why has this concept become so important?

Two major trends explain its growing importance. .

• Widespread digitalisation: smartphones have become our universal access point. From public services to healthcare, everything is now digital. Initiatives such as France Identité and the European eIDAS 2.0 regulation aim to create digital identities that are recognised at national and supranational level.
• A boom in 100% web-based crime: identity fraud is skyrocketing. The concept of ‘synthetic identity’ illustrates this trend. Fraudsters assemble pieces of real and invented data to create fake profiles capable of fooling traditional controls.

In this context, the ability to assess the credibility of a digital identity is becoming strategic for banks, insurers, retailers and also for governments.

In a nutshell…

Digital identity is constantly evolving: shaped by our usage, regulated by legislation, scrutinised for its security and commercial value. But this dynamic is not without its challenges. In the second part, we will address the multiple issues it raises – security, trust, sovereignty, inclusion – and the prospects that could redefine our relationship with identity by 2030.

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Triangular fraud is a complex and ingenious method of fraud that combines elements of real and synthetic identities to create a network of fraudulent transactions. This type of fraud relies on the interaction between three parties: the fraudster, the legitimate seller and the unwitting consumer, in order to divert resources discreetly and effectively.

How triangular fraud works:

The triangular fraud process can generally be broken down into four steps:

1. Creation of multiple identities: fraudsters begin by creating synthetic identities by combining real and fictitious information from real customer information received during purchases on their website. This allows them to generate credible buyer profiles that can interact with sellers without arousing suspicion.
2. Ordering products: using these identities, fraudsters place orders with legitimate sellers. Payment is often made with stolen or misused credit cards.
3. Reshipping products: the purchased products are shipped to intermediate addresses or directly to the ‘real customer’ depending on the method used. At this stage, fraudsters may also sell the stolen products to real buyers via online platforms at a reduced price.
4. Cash-out: Fraudsters cash out payments from genuine buyers, while the original seller remains unpaid or faces a chargeback.

Why is triangular fraud effective?

Triangular fraud is particularly effective because of its networked approach, which allows fraudsters to separate the elements of the transaction. The initial seller believes they are interacting with a legitimate buyer, while the final buyer thinks they are getting a product at a bargain price. This separation makes detection difficult, as individual transactions may appear legitimate because the information used is real, long-standing and sometimes even shows healthy activity. Traditional security rules are unable to detect these weak signals of fraud.

The MERLIN network

At Oneytrust, we are constantly detecting new fraudulent schemes. One of the most telling recent cases is that of a network we have named ‘Merlin’ because it used products from this brand to carry out its attacks. Detected in June 2024, this network perfectly illustrates the complexity and evolution of today’s threats.

It all started with an alert about unusual purchases: a sharp increase in orders for Merlin educational games, worth less than £100, from a partner specialising in childcare products. This sudden spike immediately caught our attention.

Our experts quickly spotted similarities between the orders, suggesting the existence of an organised network. However, certain elements were puzzling: the digital identities appeared reliable, and some profiles even belonged to real customers – but with a different email address. This was a clear sign of identity theft, which is rare for such small amounts.

To remove any doubt, we contacted the customers concerned. All confirmed their identity… but denied having made these purchases. The fraud was now certain. A thorough discussion with one of them revealed the key: he had indeed purchased the product, but on an online marketplace, not from our partner. The evidence provided enabled us to identify the fraudulent shop and understand the modus operandi: a triangular fraud.

Once the pattern had been established, our analysts listed the common signals associated with suspicious orders and created specific security rules. Thanks to these targeted actions, reinforced by direct checks with customers, we were able to block transactions linked to this network. The result: in less than 12 hours, the ‘Merlin’ network was neutralised.

This case shows how essential the responsiveness and expertise of our teams are in stopping new fraud networks as soon as they emerge. And the story of ‘Merlin’ is only just beginning… we will tell you more very soon.

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1) Why AI has become essential in the fight against fraud

The boom in language models and content generation tools has lowered the barriers to fraud: flawless phishing emails, carefully crafted fake profiles, synthetic identities that are more difficult to detect, industrialisation of fraud scenarios, reusable attack scripts. Static controls are no longer sufficient. We need systems that are capable of learning, detecting weak signals, and continuously evolving. AI is not a gadget: it is essential for detecting anomalies, linking scattered events, and responding in real time without hindering legitimate processes.

2) Oneytrust’s AI toolkit

Over the years, Oneytrust has built a range of scores to analyse digital events, identify fraud patterns and prioritise actions. Our scores aggregate more than 200 signals and are based on a shared database covering more than 15 million consumers, authorised by the CNIL (French Data Protection Authority) in 2013 — well before the GDPR.
Beyond fraud at a given moment, we observe velocity: how a user, payment method, device (phone, PC, etc.) or email address behaves over time. This intelligent memory makes it possible to streamline the journey of good customers (controlled reuse of acquired trust) and tighten the noose on risks (accumulation of clues, inconsistencies, anomalies). Our rule engines remain adaptive: we add, adjust and remove rules as trends evolve, to keep pace with changing attacks without compromising the customer experience.

3) Humans + AI: augmented expertise, not automated

AI identifies, humans understand. Our investigators and fraud experts play a particularly crucial role in challenging alerts, contextualising cases, and revealing emerging patterns that models have not yet learned (low volumes, ambiguous signals, attacker innovations). This feedback loop feeds the models, improves the rules, and ensures an explainable decision. In particularly sensitive situations, human arbitration protects the customer relationship, avoids false positives, and maintains trust.

4) A strategy to acculturate our employees to Generative AI

As soon as ChatGPT was released in 2022, we quickly decided to train our teams in the use of generative AI to increase speed, operational efficiency and quality on non-sensitive tasks: writing, summarising, analysis assistance, preparing deliverables, etc. As part of the BPCE Group, we have access to the secure MAIA portal, which allows our employees to access reference models (e.g. GPT-4o, Mistral, Gemini) in a safe and ethical environment. In our training courses and with the help of our Generative AI Ambassadors, we emphasise the importance of maintaining a critical perspective on the results generated by AI (systematic verification, non-disclosure of sensitive information, traceability of uses): the aim is to accelerate useful production, not to automate indiscriminately.

5) Governance & compliance: already prepared for the AI Act!

Because many of our customers are regulated (banks, fintechs, e-merchants), we have long since implemented the safeguards expected by sector regulators: model documentation, decision logging and auditability, data quality, continuous monitoring, and human supervision. The AI Act, which has just come into force, reinforces these requirements: we anticipated this framework and are aligning our work with the BPCE Group’s compliance approach. In concrete terms, this means: system mapping, model risk management, periodic controls, proportionate explainability and team acculturation. Our ambition is to meet deadlines without slowing down useful innovation.

In conclusion, let us consider that the fight against fraud is a movement, not something static. AI enables earlier detection, better explanation and faster action — provided it is governed, complemented by humans and integrated without disrupting the user experience. At Oneytrust, it is this winning trio — high-performance models, committed experts and solid compliance — that transforms a shifting threat into a sustainable competitive advantage.

Would you like to learn more about the expertise of our models, which combine more than 200 types of data and velocities, and benefit from Oneytrust’s Data Consortium with more than 15 million digital identities to secure your customer journeys without losing conversions? Contact us.

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