Integrating Fingerprint.com Device Fingerprinting with Decisimo

Published on: 2024-08-10

In today's world, businesses and organizations must ensure that they are providing a safe and secure environment for their customers. One way to do this is by integrating device fingerprinting into their online systems. Device fingerprinting is a process that captures information about a user's device, including its configuration and software, to create a unique device ID. This ID can then be used to recognize connections between users, detect fraud and suspicious devices, and optimize user experiences.

These antifraud rules use fingerprinting to check whether a visitor is seen globally for the first time and whether this is their first visit.

Fingerprint.com is a popular device fingerprinting service that has helped many businesses to secure their online systems. In this article, we will explore how you can integrate fingerprint.com device fingerprinting into Decisimo.com decision engine to improve your online security and user experience.

Obtain a Fingerprint.com Account

The first step in integrating Fingerprint.com into Decisimo is to obtain an account with fingerprint.com. To do this, go to the Fingerprint.com website and follow the registration process. Once you have an account, you will be able to access their device fingerprinting services.

Get the Secret & Public API Key

In the App Settings part -> API Keys of your Fingerprint.com Dashboard, you will find two types of keys: a public key and a secret key.
To integrate Fingerprint.com into Decisimo, you will need the secret key. Look for the API Keys in the App Settings and copy the secret key.

Implement Fingerprint.com JavaScript into Your Website

The next step is to implement the Fingerprint.com JavaScript into your e-commerce website. This will allow Fingerprint.com to collect information about the user's device as they connect to your website, app, or server. Fingerprint.com provides a visitor_id for each user, which is used in the backend to retrieve the information needed for decision making.
Once you have the visitor ID, ask the AI Assistant in Data sources to connect Fingerprint.com and describe the API call you need. It proposes the configuration for you to review and apply, after which the provider’s response is available to the decision flow for antifraud rules.

Create a data source in Decisimo Portal

Connect Fingerprint.com through the AI Assistant. Describe the provider and its API; it proposes the HTTP method, endpoint, parameters, headers and Secret API key from the Fingerprint.com Dashboard. Review and apply its configuration.
In Data sources, describe Fingerprint.com's device-fingerprinting call to the AI Assistant. Review its proposed HTTP configuration in the form, then apply it.
Select New in Data sources, ask the AI Assistant to configure the provider, then check and apply its proposal.
In the External data definition page, change the API key to the Secret key that you have obtained from Fingerprint.com.

Evaluate the Response with Example Rules

Once you have received the results from Fingerprint.com, you can evaluate the response in Decisimo using our example rules. We provide a set of example rules that can serve as inspiration for your own rule set.

Example rules:
- First seen globally: Identifies if the visitor's unique identifier has been seen for the first time globally.
- First visit: Identifies if the visitor's unique identifier is making its first visit to the website.
- Inconsistent geolocation: Identifies if the visitor's geolocation has changed or shows significant variance from previous visits.
- Suspicious domain: Identifies if the visitor is not coming from a known domain or URL - the URL of e.g. your ecommerce site.
- Low confidence score: Identifies if the visitor's identifying information has a low confidence score or is potentially unreliable.
- Switching between incognito and regular browsing: If a visitor switches back and forth between incognito and regular browsing modes, it could be a sign that they are trying to hide their identity or behavior.
- Incognito browsing: Identifies if the visitor is using incognito mode, which may indicate an attempt to avoid detection.
These rules will help you to detect fraudulent activities and suspicious devices. By using our example rules as a starting point, you can customize them to suit your specific needs and requirements.

Build Decision Flow with Fingerprint.com

The final step is to build a decision flow that includes the connection to Fingerprint.com, example rules, and a decision table. In the decision step definition for the call to Fingerprint.com API, you will need to define the JSON path to the visitor_id that you will be sending from your system to Decisimo.

Decision flow for making decision using fingerprint.com

The decision table will be the final stage in the decision-making process and will be used to determine the appropriate action based on the device information obtained from Fingerprint.com.

Run the decision making

Release your decision flow, deploy to an endpoint and make decisions using data from Fingerprint.com.

Integrating Fingerprint.com into Decisimo is a straightforward process that can significantly improve your online security and user experience. By using device fingerprinting, you can detect fraudulent activities and suspicious devices, optimize your user flows, and measure marketing performance.

By following the steps outlined in this guide, you can easily integrate Fingerprint.com into Decisimo and begin reaping the benefits of device fingerprinting.

Frequently asked questions

How should we combine device fingerprint results with other fraud signals?

Use the device fingerprint as one input alongside account age, transaction velocity, payment details and prior confirmed outcomes. Let a single weak signal prompt review or verification, and reserve declines for combinations tied to your loss policy. Shared or reset devices are not proof of fraud.

Should incognito browsing or a change in geolocation trigger a decline?

No. Treat incognito use or a location change as context, then look for stronger evidence such as a risky transaction pattern or conflicting account details. Privacy settings, travel and network routing can all change these signals for legitimate customers. Escalating every such visit can add friction without reliably reducing fraud.

What should the decision flow do when Fingerprint.com is slow or unavailable?

Set a request-time budget that fits your checkout or application latency, then define a fallback for each risk band. Lower-risk transactions can follow your existing decision logic, while higher-risk transactions can receive additional verification or review. Failing open for every transaction can expose you to losses, and failing closed can reject legitimate customers during an outage.

How should we measure whether device fingerprinting improves fraud decisions after release?

Track fraud loss, false declines, verification completion and customer abandonment for transactions where device data was available. Compare results with a suitable group using the prior decision logic, and separate new from returning customers and major channels. Fraud outcomes can arrive late, so review mature results as well as early operational measures such as lookup failures and added latency.

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