An online business receives a new account registration from an unfamiliar internet connection. A few minutes later, the same connection attempts several transactions, or a group of accounts begins showing similar activity. Before approving the requests or blocking the visitor, the business needs more information about the network behind them. This is where IP fraud intelligence can help.

Scamalytics is an IP fraud intelligence and fraud-detection provider that helps businesses assess the potential risk associated with internet connections. Its tools include an IP lookup service, a fraud-risk API, bulk IP checking, and an on-premises database option. Depending on the product and subscription, its results can include a numerical risk score, a risk classification, network information, proxy indicators, and geolocation data.

The central distinction is that an IP fraud score is a risk signal, not proof that a person has committed fraud. An IP address identifies a network connection or endpoint, not necessarily the individual using it. Multiple people may share an address, and legitimate users may connect through VPNs, mobile networks, corporate gateways, or cloud infrastructure.

Understanding Scamalytics therefore requires looking beyond the number displayed in a report. Businesses need to know what the score represents, how additional network information can be interpreted, which integration options are available, and why risk-based decisions should consider the wider context.

Scamalytics: Quick Information Table

Fact	Details
Platform Name	Scamalytics
Official Website	https://www.scamalytics.com/
Platform Type	IP fraud intelligence and fraud-detection tools
Primary Purpose	Help businesses assess potentially risky internet connections and support online fraud prevention
Main Service	IP address fraud checking
Risk Assessment	A numerical score from 0 to 100, accompanied by a risk classification
Supporting Intelligence	Depending on the product and plan, information about proxies, anonymisation, network operators, geolocation, and external risk indicators
API Availability	IP Fraud Risk API for integrating IP checks into applications and business workflows
Bulk Lookup	A browser-based tool for checking lists of IP addresses and downloading enriched results
On-Premises Option	MMDB database files for performing lookups within an organisation’s own infrastructure
Potential Business Users	Online platforms, payment businesses, marketplaces, review services, dating platforms, and other organisations managing online risk
Typical Use Cases	Account screening, suspicious connection assessment, fraud investigations, and IP risk enrichment
Pricing Model	A published API and bulk-lookup plan includes a free allowance of 5,000 monthly lookups; paid tiers and optional data add-ons are available
Individual User Consideration	A score assesses potential connection-related risk and does not establish a person’s identity or guilt
Overall Purpose	Supply IP-related risk intelligence to support more informed fraud-prevention decisions

What Is Scamalytics and What Does It Actually Do?

Scamalytics focuses on identifying patterns associated with potentially fraudulent internet traffic. Its products allow users and businesses to examine IP addresses and receive information that can support decisions about whether a connection warrants further attention.

An IP address is a numerical identifier associated with an internet connection. When someone visits a website, the website’s infrastructure can generally observe the public IP address from which the request arrives. That address may provide clues about the network operator, approximate location, connection type, and whether the connection appears to use certain anonymisation services.

These details can be useful when a business needs to evaluate a registration, login, payment attempt, or other online interaction. For example, a website receiving repeated account registrations from network infrastructure associated with previously reported suspicious activity may want to examine those registrations more closely.

Scamalytics adds a fraud-risk assessment to this process. Its published description explains that its proprietary scoring draws on fraud feedback from a network of operators that report activity they consider fraudulent. That information is applied to surrounding IP infrastructure, including related subnetworks, autonomous system numbers, and hosting blocks.

This approach means an address may receive an elevated score even when that exact address has not been individually reported. Its surrounding network may provide relevant risk signals.

However, a network-level association is not the same as evidence about a particular individual. A legitimate customer can use infrastructure that has also been used by abusive accounts. Scamalytics should therefore be understood as a source of risk intelligence, not as a service that independently proves criminal conduct.

Why businesses check IP addresses

Businesses face different types of online abuse depending on their services. An online marketplace may encounter fake accounts, a payment platform may need to assess suspicious transaction attempts, and a review website may want to investigate coordinated activity.

IP information can contribute to these investigations by highlighting network patterns that might otherwise be overlooked.

A business could use this information to decide whether a transaction should proceed normally, whether additional verification is appropriate, or whether a case deserves manual review. The correct response depends on the business, the potential harm, the strength of the available signals, and the consequences of incorrectly flagging a legitimate user.

The purpose is not to treat every unfamiliar connection as suspicious. It is to add another piece of information to a wider assessment.

How an IP Address Becomes a Fraud-Risk Signal

An IP address does not contain a person’s name, intentions, or complete online history. Its value for fraud detection comes from the information that can be associated with the address and the patterns observed around it.

Network ownership and infrastructure

IP address ranges are assigned to network operators and organisations. These may include residential internet service providers, mobile carriers, hosting companies, cloud platforms, universities, businesses, and public infrastructure providers.

Identifying the organisation associated with an address can help distinguish between different types of connections.

For instance, an address associated with a residential provider may represent a household connection, while another address may belong to a commercial hosting network. Neither classification automatically determines whether the person using it is legitimate.

Hosting infrastructure can be used for perfectly valid websites, applications, automated services, and business systems. It can also be misused for abusive activity. Context is therefore essential.

Historical and neighbouring network signals

Fraud intelligence may draw on patterns observed across addresses and related network ranges. Scamalytics describes using reported fraud feedback and applying risk intelligence to surrounding IP neighbourhoods.

This can help identify connections associated with infrastructure where suspicious activity has previously been observed.

There is an important limitation, however. Network relationships do not mean that every address within a range has the same user or purpose. A hosting provider may serve thousands of unrelated customers. One customer could misuse its infrastructure while others operate legitimate services.

A network-level risk signal should therefore guide further assessment rather than establish individual responsibility.

Shared and changing IP addresses

Many people do not have a permanently assigned public IP address. Internet service providers may allocate addresses dynamically, meaning a customer can receive a different address at another time.

Mobile networks may also place multiple customers behind a shared public address through carrier-grade network address translation. In these circumstances, many unrelated users can appear to originate from the same public IP.

Public Wi-Fi and corporate gateways create similar challenges. A large number of people may access the internet through one outward-facing connection.

These arrangements explain why an IP address cannot always be tied to one individual. A score reflecting previous traffic from a shared address may describe a mixture of legitimate and suspicious activity.

Understanding the Scamalytics Fraud Score

One of Scamalytics’ central features is its numerical fraud-risk score. Its published API documentation describes a scale from 0 to 100, alongside risk classifications such as low, medium, high, and very high.

The number is intended to summarise the provider’s assessment of potential fraud risk associated with an IP address. It helps businesses interpret network intelligence in a consistent format and incorporate it into their own workflows.

It should not be interpreted as a court finding, a verified identity, or a universal probability that a particular person will commit fraud.

What the numerical score means

Scamalytics explains its scoring in terms of the proportion of observed traffic from an IP address that it suspects may be fraudulent. Its product documentation gives an illustrative interpretation in which a score of 70 corresponds to approximately seven out of ten observed users from that address being linked to fraudulent activity.

That interpretation requires care. It refers to the provider’s assessment of traffic associated with an IP address, based on the information available to it. It does not mean that a person receiving a score of 70 has a 70% chance of being a criminal.

The distinction is particularly important when an IP address is shared, reassigned, or used by a network operator serving many unrelated customers.

The score is a decision-support signal, not an individual verdict.

Risk categories and proportionate responses

Scamalytics publishes suggested response ranges for businesses using its score. These ranges are starting points rather than universal rules, and the provider recommends adjusting them according to a business’s own fraud data and customer experience requirements.

Published score range	Suggested interpretation	Possible response
0–19	Low risk	Allow ordinary access where other signals do not raise concerns
20–59	Medium risk	Consider additional verification, such as a CAPTCHA
60–89	High risk	Consider stronger verification or manual assessment
90–100	Very high risk	Consider blocking or flagging the request for review, depending on context

These recommendations should not be implemented blindly. A business with low-risk, low-impact interactions may use different thresholds from a financial service handling high-value transactions.

The cost of a false positive also matters. Automatically blocking a legitimate customer can lead to lost business, account-access problems, unnecessary support requests, and unfair treatment.

Why a high score does not settle the question

Suppose a user registers for a service through an IP address associated with elevated risk. That finding may justify checking whether the account details, transaction behaviour, and other available information are consistent with legitimate use.

It does not establish that the person is acting dishonestly.

Conversely, a low score does not guarantee that an interaction is safe. A malicious actor may use a residential connection, a newly assigned address, or infrastructure that has not accumulated meaningful risk signals.

The score should be treated as one component of a broader assessment rather than the sole basis for a consequential decision.

What the Scamalytics IP Lookup Tool Can Reveal

Scamalytics offers a public IP lookup service that allows visitors to check an IP address and examine available risk information. The returned information depends on the address and the fields supported by the service.

The public lookup can display a fraud score and supporting network information, including the apparent operator, country, proxy status, and Tor-related indicators where relevant.

The API offers structured data for integration into applications, with fields and enrichment depending on the subscription tier.

Fraud score and risk classification

The score provides a numerical summary of the platform’s risk assessment. A corresponding classification makes the result easier to interpret without requiring every user to build their own scoring model.

Businesses can use both values to establish review rules. An organisation might send medium-risk requests for an additional check while directing very high-risk requests to a more detailed investigation.

Those rules should be validated against the organisation’s own experience. A threshold that works for one business may create too many false positives for another.

Internet service provider and network organisation

Network information can identify the ISP or organisation associated with an IP address. Depending on the data source and plan, an API response may also include an autonomous system number, which identifies a network under a particular administrative system.

This information helps explain whether an address belongs to a consumer internet provider, hosting company, cloud platform, or another type of network.

It does not identify the individual customer using the address. The organisation associated with an IP range may be only the network provider rather than the person or business responsible for a specific request.

Geolocation information

IP geolocation estimates the location associated with an address. Depending on the product and data source, the information may include a country, region, city, or coordinates.

These results should not be confused with GPS data or a verified physical address. IP location databases can differ, and an address may be registered to a network operator whose infrastructure is located somewhere other than the user.

A location mismatch may be relevant when investigating a transaction, but it should not be treated as proof of fraud. People travel, use mobile networks, connect through corporate gateways, and use privacy services that affect apparent location.

Proxy, VPN, Tor, and blacklist indicators

Scamalytics’ products can provide information about proxy and anonymisation signals, including VPN and Tor-related indicators. Other network intelligence may include public-proxy detection, hosting infrastructure, or information from external IP lists.

Not every field is included in every plan. The official API documentation distinguishes between its Essential data and premium enrichment fields, so businesses should confirm the exact information available to their accounts.

A proxy indicator means the connection appears to use a particular type of intermediary. It does not establish why the user chose that connection or whether the activity is fraudulent.

Similarly, an IP address appearing on a blacklist is a signal that requires context. Businesses should understand the list’s purpose, scope, and update timing before deciding what action to take.

VPNs, Proxies, Tor, and Shared Connections

Anonymisation tools can make IP-based risk assessment more complicated because the public address may identify an intermediary rather than the user’s ordinary internet connection.

These tools are used for legitimate reasons as well as for activities that may violate a service’s rules.

Virtual private networks

A virtual private network, or VPN, routes a user’s traffic through a VPN server. A website generally sees the server’s public IP address rather than the user’s ordinary public address.

People use VPNs for privacy, secure remote work, and protecting connections on networks they do not fully trust. Some organisations require employees to connect through managed VPN services to access internal systems.

VPN use can also make it harder to determine the user’s approximate location or original network. For this reason, a fraud-prevention system may consider a VPN signal relevant when evaluating a particular transaction.

However, using a VPN does not automatically mean a user is dishonest. A privacy-conscious customer may use one for entirely legitimate reasons.

Proxy servers

A proxy acts as an intermediary between a user and another service. Different proxies operate in different ways and can serve purposes ranging from network management to privacy, content delivery, automation, and testing.

Some proxies are used to disguise the source of abusive traffic. Others support legitimate business operations.

A proxy indicator is therefore useful context, but the type of proxy and the surrounding activity matter more than the mere presence of an intermediary.

Tor exit nodes

Tor routes traffic through a network designed to improve anonymity. A website receiving a connection through Tor may see the IP address of a Tor exit node rather than the user’s ordinary address.

People may use Tor for privacy, research, journalism, or protection against surveillance. Some online services may also experience abusive activity through Tor.

A Tor indicator can explain why the connection’s apparent origin differs from the user’s usual network, but it cannot establish the user’s intentions.

Shared residential and mobile connections

Residential and mobile connections can be shared by multiple users or reassigned over time. An address that previously generated suspicious activity may later be assigned to a different customer.

Businesses should account for these circumstances when interpreting a score. Otherwise, they may treat an address’s history as if it belonged permanently to one individual.

How Businesses Can Use Scamalytics

Scamalytics can support different stages of online risk management. Its usefulness depends on where the check is placed in a workflow and how the business interprets the result.

Screening new account registrations

A platform may check the source IP when a new account is created. The score can help identify registrations that deserve additional review, especially when other details also appear inconsistent.

For example, repeated registrations from a related group of addresses might warrant closer examination. But shared networks, household connections, and public Wi-Fi can produce similar patterns without proving that accounts are controlled by the same person.

IP intelligence should therefore be combined with relevant account information and proportionate verification.

Adding risk information to payment workflows

Businesses handling payments may use IP intelligence as one factor in assessing a transaction. The result can help a risk system decide whether a request should proceed normally, receive additional authentication, or be reviewed.

The IP score should not replace payment verification, fraud monitoring, or other controls. A legitimate customer can use an unfamiliar network, and a fraudulent transaction can originate from an address that does not appear risky.

The objective is to improve the overall assessment rather than make a decision based on one field.

Investigating suspicious activity

Fraud investigators may examine groups of IP addresses associated with reports, account activity, or transactions.

Scamalytics can enrich these addresses with risk scores and network information. Analysts can then compare the results with other evidence to identify patterns that deserve investigation.

This may help prioritise cases, but it does not establish who controlled the addresses or prove that related activity was coordinated.

Protecting platforms and online communities

Marketplaces, review platforms, dating services, and other online communities may encounter fake registrations, spam, automated abuse, or attempts to evade account restrictions.

IP risk intelligence can contribute to screening and investigation processes. Its effectiveness depends on the type of abuse, the quality of other signals, and the way the platform handles legitimate users who share infrastructure with suspicious traffic.

Businesses should measure both the reduction in abuse and the impact on genuine customers.

API, Bulk Lookup, and MMDB: Choosing the Right Scamalytics Product

Scamalytics provides several ways to access its IP risk intelligence. The main differences concern how the data is requested, the volume of lookups, the technical environment, and whether the organisation wants to process addresses individually or in batches.

IP Fraud Risk API

The API is designed for businesses that want to integrate IP checks into their own applications and services.

A typical workflow sends an IP address to the API and receives a structured JSON response. The application can then read the score, risk classification, and available enrichment fields.

This approach is useful when a check needs to happen during an account registration, login, or transaction. Developers can connect the result to an existing decision process rather than asking staff to look up every address manually.

Scamalytics publishes API documentation describing real-time lookups, authentication requirements, response fields, and credit usage. Its documentation states that requests are processed in under 50 milliseconds excluding network time; actual end-to-end performance depends on the customer’s infrastructure and connection.

API access requires appropriate account credentials. Businesses should protect their API keys, monitor usage, handle errors, and avoid making access decisions when a response is missing or invalid.

Bulk IP lookup

Bulk lookup is intended for users who need to examine many addresses without writing an integration.

The workflow allows users to upload or paste a list of IP addresses, process the entries, and download enriched results in a CSV file. The resulting data can be reviewed in a spreadsheet or used in further analysis.

This can be useful for fraud analysts investigating historical traffic, reviewing a collection of reported addresses, or comparing network information across multiple records.

Bulk processing does not itself establish a connection between the addresses or prove that they were used by the same person. Analysts still need to interpret the results carefully and connect them with the relevant activity records.

Scamalytics states that bulk lookup is included with its accounts, including the free tier. Report retention and deletion policies should be checked before processing sensitive datasets.

On-premises MMDB database

The MMDB option is designed for organisations that want to keep the lookup process within their own infrastructure.

Rather than sending every queried IP address to a remote API, a business can use a locally hosted database file and perform lookups inside its own environment. Scamalytics describes this option as supporting unlimited lookups for a flat fee, with database updates delivered over HTTPS.

This approach may suit high-volume systems, environments where low lookup latency is important, or organisations that prefer not to transmit query addresses to an external service during individual lookups.

The MMDB file can include the Scamalytics risk information and network enrichment supported by the product. The exact implementation depends on the database file, the software library used, and the infrastructure hosting the lookup process.

Local processing can reduce the amount of query data sent to the provider, but it does not eliminate every privacy or security responsibility. Organisations still need to protect the database, manage update credentials, restrict access, and handle any personal information stored in their own systems appropriately.

Comparing the three approaches

Option	Best suited to	Main consideration
API	Live checks within websites, applications, and transaction workflows	Requires integration, credential management, and usage monitoring
Bulk lookup	Analysts reviewing large lists of IP addresses	Works well for batch investigations but does not automatically establish relationships between addresses
MMDB	High-volume or locally hosted lookup environments	Requires infrastructure to store, update, and query the database

The most suitable option depends on the organisation’s expected traffic, technical resources, data-handling requirements, and need for real-time decisions.

Scamalytics Pricing and Plan Considerations

Scamalytics publishes a monthly pricing model for its API and bulk lookup services. The official pricing page lists a free allowance of 5,000 monthly requests and paid tiers beginning at $25 per month for 25,000 lookups. Higher-volume plans are also listed.

The provider states that API and bulk lookup allowances can be shared. Unused monthly lookups do not carry over, and annual billing is available at a discounted rate on the published pricing page.

Additional data sources can be purchased as premium add-ons. Published options include enhanced proxy information, premium geolocation, more detailed ISP and organisation attribution, and residential proxy intelligence. The exact cost depends on the add-on and billing arrangement.

The MMDB product uses a different pricing model, described as a flat fee for on-premises access. Businesses interested in this option should confirm the current quote and access terms directly with the provider.

Prices and plan details can change. Before choosing a tier, a business should estimate its expected monthly lookup volume, determine which fields it actually needs, and confirm the current terms rather than assuming every feature is included in the free plan.

Three Hypothetical Examples of IP Risk Assessment

The following scenarios are illustrations of how IP intelligence might be used. They are not actual Scamalytics customer cases or reports of verified outcomes.

Example 1: A registration with an elevated score

An online service receives a new registration from an IP address associated with elevated fraud risk. The registration also includes unusual account details, so the service decides that additional verification is appropriate.

The IP score helps explain why the request deserves attention, but it does not establish that the person is a scammer. The service could request a stronger authentication step or refer the case for review.

If the remaining evidence supports legitimate use, the account should not automatically be rejected merely because the IP score was high.

Example 2: A legitimate customer using a VPN

A customer connects to a website through a VPN while travelling. The lookup identifies the connection as an anonymised network, and the apparent country differs from the customer’s usual location.

Those details could be relevant to a risk assessment, but they also have an ordinary explanation. The customer may simply be protecting their traffic on a public network.

The business can consider the VPN signal alongside account history, authentication status, and transaction context. VPN use alone should not be treated as proof of fraud.

Example 3: An analyst reviewing a list of suspicious addresses

A fraud analyst receives a list of IP addresses associated with unusual account activity. Instead of examining each address separately, the analyst uses bulk lookup to obtain scores and network information.

The enriched report may reveal that several addresses belong to hosting infrastructure or that some have proxy indicators. This helps the analyst decide which entries deserve further investigation.

The results do not prove that every address is related or that the same individual controlled them. The analyst must compare the IP data with timestamps, account records, and other relevant evidence.

Limitations, False Positives, and Fair Treatment

No IP intelligence service can reliably establish every user’s identity or intention from an address alone. The quality of the assessment depends on the available observations, the age and scope of the data, and the way the result is interpreted.

Shared infrastructure can create false positives

A public IP address may represent a household, office, mobile carrier, school, or public network. Suspicious activity from one user can affect how later traffic from the same address is perceived.

This is particularly important where an address has been reassigned or where multiple customers use a shared gateway.

A business should consider these possibilities before applying restrictions that could affect unrelated users.

Low risk is not the same as no risk

An IP address may have a low score because the available information does not indicate elevated risk. That is not a guarantee that the current request is legitimate.

Fraudsters can use ordinary residential networks, new infrastructure, or compromised devices. Some harmful activity may not yet be reflected in the available intelligence.

Businesses should maintain appropriate controls even when an IP check returns a low-risk result.

High risk is not proof of individual wrongdoing

Likewise, a high score does not prove that the current user has committed fraud. The address may be shared, reassigned, or used by someone with legitimate reasons for connecting through the associated network.

When a decision has meaningful consequences, the business should consider additional evidence and provide a reasonable way to verify legitimate use where appropriate.

Decisions should match the level of risk

Not every suspicious signal warrants the same response. A low-impact action, such as requesting an additional verification step, may be more proportionate than permanently disabling an account.

A business should also review the outcomes of its rules. If many legitimate users are being challenged or blocked, the thresholds or supporting signals may need adjustment.

The aim is to reduce abuse without creating unnecessary barriers for genuine customers.

Privacy and Responsible Use of IP Intelligence

IP addresses can constitute personal data in some circumstances, depending on the jurisdiction and the context in which they are processed. Organisations using IP risk intelligence should therefore consider their legal obligations and data-handling practices.

The correct approach depends on the organisation’s activities, the data it collects, and the purposes for which it uses the results.

Limit access and retention

Businesses should collect and retain only the information they need for a legitimate purpose. Access to IP logs, fraud scores, and investigation records should be limited to authorised personnel.

Retention periods should reflect operational needs and applicable legal requirements. Keeping detailed records indefinitely can increase exposure if the information is later accessed without authorisation.

Protect API credentials and database files

An API key should be treated as a sensitive credential. It should not be embedded in public-facing code where visitors can retrieve it, and access should be restricted to the systems that need it.

Organisations using MMDB files should protect the files and the mechanisms used to obtain updates. Local hosting changes where lookups take place, but the organisation remains responsible for its own infrastructure and access controls.

Be transparent about consequential decisions

When IP risk contributes to an important decision, organisations should consider how that decision can be explained and reviewed.

A risk score should not become an unexplained substitute for evidence, particularly when a decision affects account access, a payment, or a person’s ability to use a service.

The appropriate level of explanation depends on the context and applicable law. At minimum, businesses should understand their own decision rules, test their effects, and provide suitable review procedures where needed.

Scamalytics Compared With Other Fraud-Prevention Methods

IP intelligence answers a specific question: what risk signals are associated with the network connection involved in an online interaction?

Other fraud-prevention methods examine different aspects of the same interaction. They are often complementary rather than interchangeable.

Email verification checks whether an account can access a particular email address. It does not establish that the person is honest or that the address has not been misused.

Multi-factor authentication adds another step to confirm access to an account. It can reduce certain forms of unauthorised access, although it does not prevent every type of fraud.

Device signals can help identify patterns associated with a device or browser. These signals have their own limitations, including shared devices, privacy settings, and changes in device configuration.

Payment verification helps assess payment details and transaction authenticity. It addresses risks that an IP score alone cannot resolve.

Behavioural analysis examines activity patterns, such as repeated attempts, unusual navigation, or rapid account creation. These signals may reveal patterns that are not apparent from network information alone.

Manual review allows a trained reviewer to consider context that automated rules may overlook. It can be useful for complex or high-impact cases, although it requires time and consistent procedures.

Scamalytics can complement these methods by supplying IP-related intelligence. The strongest workflow is one in which each signal has a clear purpose and the final decision reflects the available evidence rather than a single score.

When Is Scamalytics Worth Considering?

Scamalytics may be relevant to organisations that receive substantial online traffic and need to assess IP-related risk as part of their fraud-prevention process.

An online marketplace, payment service, review platform, or account-based application may benefit from adding network intelligence to its existing controls. Investigators who need to examine many IP addresses may prefer bulk lookup, while developers building real-time checks may consider the API. Organisations requiring local processing may evaluate MMDB.

The value depends on the problem being addressed. A business experiencing coordinated account abuse may have different needs from one that mainly handles low-risk informational traffic.

Before adopting a product, a team should ask several practical questions:

• What kind of abuse are we trying to detect?
• How many IP lookups will we need each month?
• Which fields are necessary for our decisions?
• How will we handle missing results and false positives?
• Do we need real-time API checks, batch analysis, or local database access?
• What privacy and retention requirements apply to our workflow?
• How will we measure whether the system improves outcomes without unfairly restricting legitimate users?

Answering these questions helps determine whether IP intelligence is likely to be useful and which delivery method best matches the organisation’s requirements.

Frequently Asked Questions About Scamalytics

1. What is Scamalytics used for?

Scamalytics provides IP fraud intelligence that helps businesses assess potentially risky internet connections. Its tools include an IP lookup service, an API, bulk IP lookup, and an on-premises MMDB database option.

2. How does the Scamalytics fraud score work?

Scamalytics uses a numerical score from 0 to 100 alongside a risk classification. Its published methodology draws on fraud feedback from a network of operators and applies risk intelligence to related IP infrastructure. The result represents an assessment of potential network-related fraud risk, not a definitive judgment about an individual.

3. Can Scamalytics determine whether a person is a scammer?

No. An IP address does not independently establish a person’s identity or intentions. A high score may justify further checks, but the decision should consider other relevant evidence and the possibility of shared or reassigned addresses.

4. Does using a VPN automatically make an IP address suspicious?

No. VPNs have legitimate uses, including privacy protection and secure remote work. A VPN indicator can provide useful context, but it does not prove that the user is committing fraud.

5. What information can the Scamalytics IP lookup reveal?

Depending on the product and plan, results can include a fraud score, risk classification, network operator, geolocation, proxy or anonymisation indicators, and external IP risk information. Not every field is available in every subscription.

6. Can businesses integrate Scamalytics with their own platforms?

Yes. Scamalytics provides an IP Fraud Risk API for application integration. Developers can request an IP assessment and process the structured response within their own workflows. API access and usage are subject to account terms and available credits.

7. Does Scamalytics support bulk IP checking?

Yes. Its bulk lookup service allows users to process lists of IP addresses and download enriched results. This is useful for analysts reviewing larger datasets without developing an API integration.

8. What are the limitations of IP-based fraud detection?

IP addresses can be shared, reassigned, or routed through VPNs, proxies, mobile carriers, and corporate networks. Risk data may also be incomplete or out of date. Consequently, an IP score should support a broader assessment rather than act as standalone proof of fraud.

Conclusion: Turning IP Risk Signals Into Better Decisions

Scamalytics provides tools for examining IP addresses and assessing the potential risk associated with online connections. Its lookup service, fraud-risk API, bulk processing option, and MMDB database give businesses different ways to incorporate network intelligence into fraud prevention and investigation workflows.

The score and supporting data can help identify connections that deserve closer attention, particularly when they are considered alongside account activity, transaction details, device information, and other relevant evidence. The right implementation depends on the organisation’s needs, technical environment, privacy obligations, and tolerance for false positives.

The most important principle is that an IP fraud score is a signal—not a verdict. A high score does not prove that an individual is a scammer, and a low score does not guarantee that an interaction is safe. Responsible use means interpreting the result in context, applying proportionate checks, and allowing additional evidence to inform consequential decisions.

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