Fraud Protection Process

Fraud and payment risks are becoming more sophisticated across the eMobility industry. This page explains how Last Mile Solutions monitors its platform, identifies abnormal patterns and protects both partners and end users.

It outlines the key concepts behind fraud detection, the responsibilities shared between LMS and its partners, and the typical scenarios in which fraudulent activity can arise.
The goal is to give partners a clear understanding of why certain checks exist, how risks are evaluated, and what information helps prevent misuse before it escalates.

Our fraud process is designed to be both structured and adaptable, enabling us to respond effectively to evolving fraud patterns, new technologies, and changes within the charging ecosystem. It provides a clear framework for consistent decision-making, while retaining the flexibility needed to assess cases on their individual merits. The process applies to all assets, accounts, and partners connected to the LMS ecosystem.

At its core, our approach is based on the MDMAR process, a structured methodology that guides how potential risks are identified, assessed, and addressed across the platform. This framework helps ensure transparency, proportionality, and timely action, while supporting collaboration with our partners throughout each stage of a case. The purpose of the MDMAR methodology is to ensure consistent, structured, and risk-proportionate handling across all cases.

The MDMAR process consists of the following main steps:

Effective fraud handling relies on collaboration between LMS and its partners. When a case concerns your customer or network, we depend on your verification to ensure that findings are interpreted correctly and resolved efficiently. You as a partner are expected to validate the situation with the end user, review relevant account or app activity, and share any information that may clarify the case.

Some aspects of charging behavior cannot be confirmed through platform data alone and therefore require partner input. These include:

• Verifying the identity and legitimacy of the end user
• Confirming whether the customer has (or should have) physical access to the charge card
• Validating customer explanations regarding their usage or activity
• Assessing any on-site or situational factors that LMS cannot observe remotely
• Managing or authorising assets within the partner’s own infrastructure, including external MSP assets

These responsibilities ensure that customer-level insights are accurately combined with LMS’s monitoring and analysis. This joint approach enables consistent and fair case handling without exposing detection methods or revealing how risks are identified.

These responsibilities exist because LMS does not have visibility into customer identity, card possession, or on-site behavior, which are essential to determining whether activity is legitimate.

Partner responsibilities apply to both fraud cases and payment defaults.

Partner involvement during active cases is explained in more detail on the Fraud Case Handling Guidelines page.

We ask you to avoid reactivating affected assets without contacting fraudprotection@lastmilesolutions.com through the relevant ticket, as doing so may influence the outcome and transfer transfer financial exposure to your organisation. Clear coordination helps ensure that risks are properly managed on both sides.

At LMS, risk assessment is not just a checklist—it’s a data-driven, multi-layered process designed to combine automation with human expertise. Our approach ensures that every case is evaluated intelligently and fairly.

• Integrated Monitoring and Data Analysis: Our monitoring tools and dashboards continuously analyze transaction flows to detect anomalies such as revenue spikes or simultaneous sessions. These insights are complemented by comprehensive data sources, including detailed CRM records, transactional history, platform-wide datasets for macro-level trend analysis, and advanced detection tools.
• Four-Eyes Principle: Every critical decision is reviewed internally by at least two experts. This guarantees fairness, accountability, and consistency in handling cases.
• Human Oversight Beyond Automation: While automation accelerates detection, we never rely on algorithms alone. Experienced fraud specialists validate findings, interpret patterns, and apply judgment where needed.

This structured yet adaptive approach ensures transparency, proportionality, and timely action—while maintaining trust and integrity across the LMS partner network.

The corresponding suspicion levels and required actions per level can be found on the Fraud Case Handling Guidelines page.

Fraud can manifest in different ways across the charging ecosystem. While every case is evaluated individually, certain patterns occur frequently and serve as key indicators during our monitoring and investigation process. Below is an overview of the most common fraud types observed on the LMS platform, intended to help partners better recognize and understand potential risks.

• Card Misuse or Clone Activity: Sessions initiated with a copied or spoofed charge card, often resulting in simultaneous or geographically impossible transactions.
• Lost or Shared Cards Used Improperly: A legitimate customer loses a card or shares it with another person, leading to unexpected usage outside normal charging behavior.
• False or Stolen Identity Information: Customer accounts created with incorrect, stolen or fabricated personal or banking details during onboarding.
• Account Multiplication (Multiple Accounts by Same User): A single user repeatedly creates new accounts after previous ones have unpaid invoices or are blocked for suspicious activity.
• Deliberate Non-Payment or Avoidance Behavior: Patterns indicating intentional avoidance of payment, such as repeated failed invoices while continuing high-volume charging.
• App or Portal Misuse: Attempts to initiate sessions through app-based access without possessing the physical card, or manipulation of customer credentials.
• Roaming Abuse: Fraudulent usage coming from external cards (non-LMS MSPs) via roaming connections on LMS CPO networks.

This list is not exhaustive, but provides partners with a clear understanding of the most common and relevant fraud patterns we monitor.

Payment Defaults: How They Relate to Fraud Cases

In addition to handling fraud, LMS also monitors and manages payment defaults. Although these two topics are related, they represent different types of risk and therefore follow different processes. Understanding this distinction helps partners respond appropriately and recognise when a situation may shift from one category to the other.

A payment default is triggered when an account has one or more outstanding invoices that have not been settled in time. This can occur even when a customer is already known within the LMS ecosystem, for example through another partner relationship. When such a case is identified, LMS informs you as a partner so timely follow-up with the end user can take place. This early signal allows partners to verify the customer, follow up on payment, or apply temporary restrictions before the situation escalates.

A payment default does not always imply fraudulent intent. Often, the cause lies in administrative issues, failed payments, or customer disputes. However, if a payment default remains unresolved, it may evolve into a risk scenario that resembles fraudulent behavior. Likewise, a case initially investigated as potential fraud may later be reclassified as a payment default when the root cause turns out to be non-payment rather than misuse.

For this reason, payment defaults and fraud follow separate but aligned processes. Cases can migrate between the two pathways depending on new information or partner feedback. This ensures consistent handling, clear ownership, and proportional follow-up, while maintaining a fair distinction between non-payment and confirmed fraudulent activity.

The difference between Payment Default and Fraud

Cases involving payment defaults follow the same case workflow as level 4 cases showed on the the Fraud Case Handling Guidelines page.

Our fraud and risk investigations may also involve external charge cards. These are cards that are not issued by LMS or its direct partners, but that are used via roaming arrangements on CPOs connected to the LMS platform.

In such cases, LMS may detect irregular usage patterns at network level. While LMS does not take ownership of these cards or the underlying customer relationship, we may still initiate a case to inform the relevant partner of the observed activity. This enables partners to validate the legitimacy of the usage within their own processes and to take appropriate action where necessary.

These cases are shared as part of our platform-wide monitoring approach and are intended to support partners in maintaining a secure and reliable charging ecosystem.

More information on case notifications, reminders, and closure logic is available on the Fraud Case Handling Guidelines page.

LMS aims to maintain clear, consistent, and timely communication throughout the lifecycle of every case. Partners are informed when a case is opened, updated when its status changes, and notified once a conclusion has been reached. This ensures visibility into how potential risks are identified, assessed, and resolved on the platform.

If new information becomes available or if a partner believes that additional context should be considered, a case can be discussed further or reopened upon request. Our support team remains available to clarify case details, explain decisions taken, or provide guidance on the overall fraud and risk management process.

This transparent approach is designed to support effective collaboration and informed decision-making across the LMS partner network.

Our fraud monitoring relies on data from multiple sources, including partners, roaming hubs and charging devices. While we perform extensive validation and cross-checking, not all data is always complete, perfectly synchronized or available in real time. Delayed updates, inconsistent location details or technical issues at charge points can influence how an activity initially appears.

For this reason, every alert is reviewed in context. Some irregularities turn out to have a legitimate explanation after partner verification, while others may stem from data inconsistencies rather than true misuse. For example, a charging session may not close correctly on the CPO side, causing the session to appear active while the user has already started a new session elsewhere. Situations like these can resemble suspicious activity, even though they are not fraudulent.

These limitations make your validation essential. LMS cannot see on-site behavior or customer interactions, and certain conclusions cannot be drawn from platform data alone. Our monitoring tools detect known patterns and anomalies, but they do not capture every scenario automatically.

More information on case notifications, reminders, and closure logic is available on the Fraud Case Handling Guidelines page.

Timely collaboration and information exchange help ensure that findings are interpreted correctly and that cases are resolved efficiently, fairly and with the appropriate level of action. At LMS, we are committed to maintaining a secure, transparent and reliable charging ecosystem, and this relies on the combined effort of both our platform monitoring and the partner’s direct interaction with end users.

While our tools are designed to identify irregular behavior as early as possible, certain conclusions can only be drawn through partner verification. Your insights help confirm legitimacy, clarify context and prevent unnecessary escalation. By working together, we ensure fair handling of incidents, protection of legitimate users and minimal operational or financial risk for all parties involved.

If you encounter activity that appears unusual or cannot be immediately explained, you can always contact fraudprotection@lastmilesolutions.com. Early notification allows us to assess the situation together and helps prevent issues from escalating. Even if the activity turns out to be legitimate, we prefer to be informed early rather than too late.

Together we maintain a safer and more trusted EV charging environment.