Digital fraud is no longer an occasional event, but has become part of the daily routine of e-commerce.Nethone data shows that suspected fraud attempts remained above 400 million in January and February, indicating that fraudsters continue to target users even when the volume of returns, refunds and complaints is at its peak, making detection even more challenging.

The main focus of these actions is high-value digital commerce, such as e-commerce stores that sell high-priced products and companies in the airline ticket industry. These businesses, because they are more attractive to criminals, are forced to innovate faster than others, becoming laboratories for the latest fraud detection technologies.

What makes a transaction high risk (so-called “high-risk business”) is the association with high value operations, immediate liquidity or large volume.We are talking about:

E-commerce platforms for expensive items such as electronics and premium brand marketplaces that handle products easily resold in the informal market;

Online games and betting, which allow quick movement and multiplication of resources;

Tourism and airline tickets, with high average transaction values and immediate resale potential;

Cryptocurrencies and digital assets, which enable transactions marked by anonymity, liquidity and absence of borders;

Fintech services, where account opening and customer interactions are vulnerable to social engineering and account takeover scams.

Companies with this profile face sophisticated threats on a daily basis, which forces them to raise their security standards and continuously innovate. Those outside this group should pay close attention, because the risks faced by these businesses today tend to spread throughout the market in a short time.

The problems of traditional prevention approaches

The classic response to fraud is blocking based on registration data and transaction history.This is a static model, with clear limitations, such as excessive blocking, which increases the number of false positives and leads to the loss of legitimate customers.In addition, the traditional model does not keep up with the dynamism of attacks, and sophisticated fraudsters already know how to manipulate static data, such as document numbers, addresses and cloned cards.

In the end, blocking too much costs sales; blocking too little generates financial losses. That is why it is so important to include other elements in the equation, such as behavioral analysis. This is already a learning of high-risk sectors, which no longer limit their evaluations to what the user reports, but also analyze how he behaves online.

Some behavioral metrics that have been successfully applied include:

Speed and typing pattern;

Geolocation and discrepancies with billing address;

Use of VPNs or device emulators;

Navigation flow (time on pages, repeated attempts, click paths).

Fraudsters can obtain cadastral data, but it is much harder to consistently replicate a legitimate behavioral pattern.

Artificial intelligence on the front line

The main lesson high-value digital commerce can teach about fraud prevention is that it is never static: it is an ongoing process that requires constant updates in response to evolving criminal techniques.

Every e-commerce, even the lowest risk, should be inspired by this dynamic ecosystem and adopt a proactive stance, since reputation, cash flow and customer relationships depend on the ability to detect and block threats.

The massive use of technologies such as Artificial Intelligence (AI) enables the detection of anomalies in real time, something essential in sectors where decisions need to be made instantly.In addition, these systems have continuous learning capabilities & MODELS improve as they identify new attack vectors, providing faster and more effective responses to emerging behaviors.

AI has not yet completely replaced human analytics, but it powers anti-fraud teams by automating massive volumes of attempts, creating a combination that makes defenses much more robust.

What all industries need to understand (and fast)

Investments and security strategies of high-risk sectors should be treated as a reference for the entire market. After all, technological evolution happens on both sides & defrauders & IDF and what is being tested today in highly targeted sectors can spread to others very soon.

As the data shows, fraud is increasingly dynamic, no longer restricted to key dates in the business calendar, and it is a mistake to treat it as a “IT IT team issue”.

In practice, this means that bolstering defenses just in November, before Black Friday, is not enough. Even for moderate risk sectors, the way is to prioritize investment in behavioral technology and AI.

Those who closely follow how high-risk sectors deal with fraud are better prepared for the challenges that already knock on the door of the market as a whole 'WHEEL fraud prevention is a business strategy, not just a defense measure.

By Thiago Bertacchini, Head of Sales at Nethone

Edsel Simas, Chief Technology Officer, Setrion Software and Milldesk

The pressure for leaner margins and increasingly strict deadlines has taken the logistics sector to a tipping point. In a market where minutes of delay impact contracts and loyalty, ensuring the availability of systems and standardization of processes between operating units is no longer just a technical challenge & has become a strategic demand.

The help desk (often treated as a basic operational function 'DO within this context, has come to play a central role in value chain efficiency.When structured with technology, automation and visibility, technical support becomes a tool capable of reducing costs, avoiding operational losses and increasing end-to-end control, especially in companies with multiple locations.

Recent data help to scale the impact of unavailability on logistics results. According to Gartner estimates, one hour of downtime can cost up to US$ 42 thousand for a medium or large company. And these are not sporadic events: the same study indicates that companies face, on average, 87 hours of unplanned downtime per year the equivalent of almost four full days of stopped operation.

In the logistics industry, where the availability of warehouse management systems (WMS), transportation (TMS), mobile devices, networks and printers is directly connected to productivity, each disruption impacts deadlines, contractual penalties, routing and end customer satisfaction.

The complexity of support in decentralized environments

In distributed logistics operations, IT decentralization amplifies support challenges. Warehouses, branch offices, urban hubs and distribution centers operate with diverse structures, distinct user profiles and varying levels of technical maturity.

In many organizations, service still depends on overloaded local teams or face-to-face support coming from the matrix ''A model that generates disparities in response times, improvisations in resolution and, especially, loss of visibility for corporate managers.

According to a survey conducted in 2024 by a global ITSM consultancy, almost 46% of companies with geographically distributed operations report difficulties to maintain consistent service levels between units. And when there is no standardization, support becomes reactive, slow and prone to rework. Tickets are lost, histories are not consolidated and recurring problems are no longer identified, multiplying silent operating costs.

Centralization and visibility: what changes with a structured help desk

The adoption of an efficient and centralized help desk solution represents a game changer for logistics companies.This is a model that unifies technical support in a single platform, allowing all calls (regardless of the place of origin (follow defined flows, with standardized categorization, priority levels and agreed service deadlines.

This type of structure creates an environment in which real-time visibility is guaranteed. The IT manager can track incidents by unit, by affected system or by type of problem, identifying trends, bottlenecks and areas that require technical reinforcement or training. This continuous monitoring, associated with performance indicators such as SLAs (Service Level Agreements) and SLIs (Service Level Indicators), transforms IT into a data-based decision center, and no longer into assumptions.

By centralizing the service, the company also reduces the dependence on face-to-face support in remote locations. Incidents that previously required the displacement of technicians are now solved by remote access, with speed, standardization and lower cost. Studies indicate that remote support reduces the average resolution time by up to 30% and operational costs by about 50%, especially when associated with automated flows.

Automation and standardization: the new basis of efficiency

Automation is one of the key differentiators of a modern help desk solution. Repetitive, low-value tasks such as password resetting, system updates, or diagnosing known failures can be performed automatically, freeing up staff to handle more complex and strategic incidents.In addition, intelligent flows ensure that calls are routed directly to the right team or analyst, according to previously configured business rules.

This model eliminates the need for manual sorting and significantly reduces service time.It also avoids unnecessary escalations and contributes to improving the internal user experience, which now has a more agile, accurate and predictable support.

Another essential resource in this context is the integrated knowledge base, continuously fed by solved calls. Each incident turns into documented learning, accessible not only to the technical team, but also to users. Thus, the organization can offer self-service portals and dynamic FAQs, allowing simple problems to be solved by the employee himself, without opening a ticket. Automation combined with knowledge base intelligence reduces the volume of calls and improves the average response time, while strengthening the autonomy of operational teams.

Data-driven indicators, reports and decisions

In logistics environments, where every minute counts, operational predictability is a valuable asset.Therefore, another strategic benefit of adopting a structured help desk is the ability to generate actionable reports (with indicators segmented by branch, type of call, resolution time, reopening frequency and degree of impact.

With this data in hand, IT can more clearly assess which units require infrastructure reinforcement, which systems have the most instability and where are the recurring points of failure. This visibility not only optimizes investments, but also allows the technology area to act proactively, anticipating demands and reducing the likelihood of critical failures.

A study published in 2024 by an international service management association showed that organizations operating with well-defined and monitored SLAs were able to reduce the occurrence of critical incidents by 76%.More than that, they increased the availability of the most operation-sensitive systems, such as WMS and routing platforms, by 20%.

Financial impact and tangible return

The efficiency and control gains provided by a well-implemented help desk structure result in tangible financial impacts.In addition to the direct reduction with commutes, technical visits and rework, there is significant savings associated with decreased downtime.

To give you an idea, according to IBM data, companies that adopt automation in support can reduce average costs per incident by up to 45%, in addition to improving the resolution rate in the first contact 'DO a key indicator to contain repeat calls and preserve the productivity of local operations.

Process traceability itself also contributes to risk reduction. In regulated segments, such as the transportation of pharmaceuticals or food, maintaining a complete history and auditing support is essential to meet legal and contractual requirements. The help desk, in this context, becomes not only a service tool, but a strategic component of governance and operational compliance.

Operational efficiency in the logistics industry depends on multiple factors, but few have as direct and often overlooked an impact as technical support.In companies with scattered units, remote branches and heavy reliance on integrated systems, investing in an efficient help desk solution is not a matter of convenience: it is a strategy to protect margin, ensure quality and scale safely.

By centralizing service, automating flows, measuring performance accurately and documenting learnings, IT starts to operate with predictability and intelligence - DELIVERing real value to the operation. And in an increasingly demanding market, where error costs money and delay compromises contracts, having a strong help desk is more than important: it is a way to ensure that the business continues running, without stops, with control, visibility and confidence.

The recent history of technology is marked by the promise of disintermediation.In the beginning of the internet, there was a belief that the network would allow direct connections, in which artists would talk to their fans without labels, companies would sell to consumers without retailers, ideas would circulate without filters. It was a libertarian, almost romantic ideal of a simpler and more transparent world.For a while, this view seemed to take shape, but reality reorganized around new intermediaries, as powerful as the old ones, although disguised in the form of digital platforms.

Services such as Uber, Mercado Livre, Instagram and Amazon created closed ecosystems that facilitated interactions and transactions, but also established new layers between desire and its fulfillment.They were practical, efficient and often inevitable.The rise of software as a service (SaaS) consolidated a model in which technology presents itself as packaging, where an elegant interface that involves user intention and translates it into action, but in the process, remains a barrier.

Three out of four companies (75%) plan to prioritize SaaS application backup operations as a critical requirement by 2028, a dramatic leap from the 15% recorded in 2024, Gartner said.However fluid an interface may seem, it requires opening an application, typing, selecting, and browsing. Each microdecision represents friction, and the accumulation of these small frictions has become evident.

Currently, we live surrounded by passwords, flows and screens, in a maze of tools that should facilitate, but often complicate. With this, the perception grows that we do not seek applications themselves, but the results they deliver. And if it is possible to reach these results without going through an app, even better. Artificial intelligence is promoting this silent and integrated change, especially by popularizing natural interfaces such as voice search.

In 2025, about 20.5% of people worldwide use this form of research, a slight increase from the 20.3% recorded in the first quarter of 2024, according to Data Reportal data.In addition, the number of voice assistants in use exceeds the global population, reaching 8.4 billion devices in 2025, according to Statista. By merging intention and execution in the same act, AI eliminates the need for explicit interactions with platforms.

Online search already offers signs of this transition, in which a question is typed and the answer appears, without clicks or manual filtering. Traditional search, which required multiple steps, begins to be replaced by direct answers. This is the new disintermediation, not a visible disruption, but a gradual disappearance of tools, and this transformation shifts the role of interface technology to infrastructure.

Soon, tasks such as writing, organizing, translating or planning can be performed the moment the desire arises, without the mediation of visible applications. Technology will become as ubiquitous and silent as electricity or piped water, essential but invisible. This implies that many software and platforms, once central to the digital experience, will no longer have a noticeable form, brand or presence.

The practical consequence is that a significant part of the SaaS ecosystem can become infrastructure and no longer service to the end user. When functionality becomes internal to an automated cognitive layer, the need to access specific tools disappears. For the user, this absence will not be a loss; on the contrary, it will be perceived as a gain in fluidity. Application nostalgia will cease to exist because, in practice, they will dissolve in the flow of tasks.

The impact of this disintermediation on the market is profound. Business models based on user retention on a platform will need to reinvent themselves, because value will reside in the result, not in the way. For companies, this means competing no longer for the most attractive interface, but for the ability to integrate invisibly and efficiently into the life of the user. For consumers, the possibility of a daily life less fragmented by screens and logins, but more dependent on infrastructures controlled by few global suppliers is opened.

The great disintermediation that emerges is neither utopian nor libertarian, as dreamed in the early years of the internet. It is technical, silent and definitive. By shortening the distance between thought and action, artificial intelligence erases the center of the digital experience and relegates the interfaces to the background. In the near future, we will not notice when an application ceases to exist, we will simply move on, as if it had never been part of our daily lives. And perhaps it is exactly there that one realizes that the future has already arrived.