# ThreatMetrix alternative: explained decisions without a shared network

Source: https://kavralab.com/compare/threatmetrix-alternative/

**LexisNexis ThreatMetrix** is a risk decision engine that scores logins, account openings and payments using device, location, identity and behavior signals from its shared Digital Identity Network. **Kavra** assesses every request from what it observes directly, keeps each customer's data isolated, and returns a plain-language finding with a recommended action.

- **Kavra approach:** Explained assessment per request, data isolated per customer
- **ThreatMetrix approach:** Consortium intelligence from the Digital Identity Network
- **Integration:** Kavra: one script and one API call. ThreatMetrix: full decision platform
- **Best for:** Kavra: bots and spoofed devices. ThreatMetrix: large identity programs

## What LexisNexis ThreatMetrix does

ThreatMetrix is part of LexisNexis Risk Solutions. LexisNexis describes it as a risk decision engine that brings several risk technologies into one place for new account opening, logins and account management, account takeover and payments. It analyzes device, geolocation, IP address, email address, phone, behavioral patterns and transaction details, and looks at distance anomalies, age, history, velocity and previous risk associations.

The center of the product is the **Digital Identity Network**. According to LexisNexis, it spans 200+ countries and territories, processes about 3 billion transactions a month, and holds a tokenized identifier for about 1.4 billion recognized users. Its intelligence is crowdsourced from participating organizations and covers web and mobile device identification, true location and behavior analysis, identity and link analysis, and bot and malware threat intelligence. **LexID Digital** is the network's identifier; LexisNexis says it merges offline and online data to give confidence and trust scores for a digital identity.

Around that sit **BehavioSec** behavioral biometrics (typing rhythm, mouse and touch patterns), machine learning models configured in a no-code environment, and the **Dynamic Decision Platform** for forensics, case management, reporting and workflow orchestration.

## How Kavra approaches the problem differently

ThreatMetrix leans on what a large shared network already knows about an identity. Kavra relies on what it can observe and prove about the request in front of it, and **never shares one customer's data with another**. Every assessment comes back with a plain-language headline, the findings behind it, risk by domain (automation, impersonation, network, tampering, abuse), network context and a recommendation: allow, verify or block. Your backend decides.

Kavra analyzes 3,000+ data points on every visit and looks for contradictions between layers, because a disguise that fools one layer rarely fools all of them. For [account takeover](https://kavralab.com/solutions/account-takeover/), it compares each login with the account's own history: new device, new network, impossible travel, known-bad device. Trusted devices are kept per account, and devices can be revoked through the API.

- **Bots and automation across layers**, including headless browsers, stealth plugins and HTTP clients posing as browsers.
- **The real connection**, seen on Kavra's own edge network instead of trusting what the browser reports.
- **Own proxy intelligence**: real exit IPs of commercial [residential and mobile proxies](https://kavralab.com/detect/residential-proxies/), measured continuously, on top of 30+ public feeds.
- **Antidetect browsers, emulators and virtual machines** exposed by what they claim versus how they behave.
- **Fingerprint rotation kept as one actor**, with the number of rotations as evidence.

## Kavra vs ThreatMetrix: capability comparison

Both products are built to score risk in real time and leave the outcome to your systems. They differ in where the evidence comes from and how much platform comes with it.

|  | Kavra | LexisNexis ThreatMetrix |
|---|---|---|
| Main evidence | What Kavra observes on each request across layers | Device, location, identity and behavior, enriched by the Digital Identity Network |
| Cross-customer data | None; strict tenant isolation | Crowdsourced consortium intelligence, tokenized |
| Offline identity data | Not used | LexID Digital merges offline and online data |
| Output | Headline, findings, domain risk, recommended action | Confidence and trust scores, with workflow orchestration |
| Bot detection | Across network, device, browser integrity and behavior | Bot and malware threat intelligence in the network |
| Proxy intelligence | Own measurement of commercial proxy exit IPs plus 30+ feeds | IP and true location analysis; proxy methods not publicly detailed |
| Behavioral biometrics | Behavior is one of Kavra's analysis layers | BehavioSec, a dedicated behavioral biometrics product |
| Case management | Investigate view with evidence per assessment | Forensics, case management and orchestration in the Dynamic Decision Platform |
| Integration | One script plus one API call, first results the same day | Delivered through the Dynamic Decision Platform; deployment timeline not publicly documented |
| Data you must send | No names, emails or phone numbers; technical signals only (see privacy policy) | Email, phone and identity signals among inputs, tokenized per LexisNexis |

## When ThreatMetrix may be the better fit

ThreatMetrix suits large identity and risk programs, and some needs point clearly to it or to a platform like it.

- You are a bank, lender or large enterprise that wants **consortium intelligence**: knowing how a device or identity behaved at other organizations.
- You need **offline identity data** joined to digital signals, which LexisNexis offers through LexID Digital and its wider identity products.
- You want **dedicated behavioral biometrics** for continuous authentication through BehavioSec.
- Your fraud operation runs on one vendor's **case management, forensics and orchestration** layer across many channels.
- You serve citizens online; LexisNexis markets a dedicated ThreatMetrix for Government version for agencies.

## When Kavra is the better fit

- You want each decision explained in plain language for analysts, support and appeals, not only a score.
- Your policy or customers require that **fraud data not be pooled across companies**.
- Your biggest problems are automated: [credential stuffing](https://kavralab.com/solutions/credential-stuffing/), scraping, card testing, scripted signups or [antidetect browser](https://kavralab.com/detect/antidetect-browsers/) farms.
- You want to go live the same day with one script and one API call, and start in observe-only mode.
- You want no names, emails or payment details sent to a fraud vendor at all.

The two can also coexist. A bank can keep an enterprise identity platform for onboarding and payments, and add Kavra in front of login, signup and high-value API endpoints to catch bots and spoofed devices with a readable reason. See how this works in [fintech](https://kavralab.com/industries/fintech/).

## How to evaluate the switch

1. **Pick one flow**: Login or signup is usually best: high volume, clear outcomes and a known fraud rate.
2. **Run Kavra in observe-only mode**: Add the script and API call next to your current setup. Nothing is blocked.
3. **Compare case by case**: Look at where the two disagree. Read Kavra's findings for each request and check them against confirmed fraud.
4. **Choose a preset and act**: Start with cautious, balanced or strict, map allow, verify and block to your flow, and label outcomes back through the API.

> **The short version:** ThreatMetrix asks **what does a global network know about this identity?** Kavra asks **what is really behind this request, and what gave it away?** Choose ThreatMetrix for consortium and offline identity data at enterprise scale. Choose Kavra for explained, per-request bot and fraud decisions with your data kept to yourself.

## Why teams choose Kavra

Evidence you can read, from data that stays yours.

- **Explained decisions**: Headline, findings, domain risk and a recommended action on every assessment.
- **Your data stays yours**: Strict tenant isolation, opaque visitor IDs, no names or emails required.
- **Real connection seen**: Kavra's own edge network sees how a visitor actually connects.
- **Login history per account**: New device, new network, impossible travel and trusted devices per account.
- **One script, one call**: First results the same day. Kavra recommends; your backend decides.

## FAQ

### What is LexisNexis ThreatMetrix?

ThreatMetrix is a risk decision engine from LexisNexis Risk Solutions. It scores account openings, logins and payments using device, location, identity and behavior signals, enriched by the Digital Identity Network, a crowdsourced and tokenized pool of transaction intelligence from participating organizations. It comes with forensics, case management and workflow tools through the Dynamic Decision Platform.

### What is the difference between a consortium network and Kavra's approach?

A consortium pools intelligence from many organizations so a device or identity seen elsewhere carries its history with it. Kavra keeps each customer's data isolated and instead proves what it can about each request: the real device, the real connection, proxy exits, automation and rotation. Both approaches are valid; they suit different privacy and data-sharing policies.

### Can Kavra replace ThreatMetrix?

For bot detection, spoofed devices, multi-accounting and login risk, often yes. Kavra does not offer offline identity data, consortium lookups or dedicated behavioral biometrics, so if your program depends on those, keep them and add Kavra where automated and disguised traffic is the main threat.

### How does Kavra decide when to step up a login?

Kavra compares the login with the account's own history: known or new device, usual or new network, impossible travel, and devices already marked bad. It also checks for automation and tampering. When evidence is mixed, it recommends verify, and your backend chooses the step-up, such as a one-time code or a trusted-device prompt.

### Does Kavra need names, emails or phone numbers?

No. Kavra assesses requests from technical and network signals, not from identity data. Those signals, such as the IP address, can still be personal data under GDPR, so Kavra applies the legal basis per visitor region, respects your consent manager and documents the processing in its privacy policy. Visitor IDs are pseudonymous and each customer's data stays isolated.

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