Open DataThe “Secret Sauce” for Fraud Detection Success?

March 14, 2023 | 10 min read

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Open Data

In a Nutshell

Revenue streams are under constant attack from criminal activity, unauthorized transactions, illegitimate chargebacks, and other threats. But what if merchants could cast a wider net for the information they need to protect their businesses? Open data sharing could be the solution you’ve been searching for.

How Open Data Can Help Fight Fraud, Prevent Chargebacks, & Grow Your Revenue

Open data is information that can be freely used, re-used, and redistributed by anyone. In the context of eCommerce, getting access to a big reserve of open transaction data makes it easier to observe macro trends in consumer behavior, as well as in criminal activity.

How exactly can open data improve merchants’ fraud prevention efforts, though? Is it really as secure as everyone says? Let’s find out.

What is Open Data?

Open Data

[noun]/ō • p(ə)n • dā • də/

Open data is any non-proprietary data available to be freely used and redistributed. The conditions under which this data is provided are what allow for redistribution and intermixing with other information.

For a more thorough breakdown, open data is any data which is:

Accessible & Available

In order to be usable, data must first be accessible and readily available at a limited cost to the user. Preferably, it should be contained in a downloadable file from a secured browser. Also, the data must be conveniently sized and modifiable.


Users must be able to share data, and it must be reusable and redistributable between databases, as far as is allowed under data privacy laws and regulations.


Each participating database must maintain and provide access and redistribution compatibility as a shareable commodity. For example, “non-commercial” restrictions cannot be placed on open databases that are inherently “commercial” in nature.


Open data relies on interoperability to communicate between databases. Having data that’s agnostic regarding the database in question is important when one is sharing information between two or more datasets.

Without openness between access points, information shared could not be used to structure larger systems. This means that in order for information to be shared equally between systems, every participant must provide open access to utilize core data.

Giving strangers access to secure data sounds like a strange idea. As we’ll see below, though, it can pay serious dividends. 

The Value of Open Data

Open data is a valuable resource for major organizations and institutions that require a broad range of data to perform tasks. Open government is one example of how this data collation technique could be used to the fullest effect.

Governmental data is already public by law. Therefore, it could be enormously useful to open data proponents by virtue of the centrality and quantity of the data that governments collect.

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Many groups and organizations could benefit from having faster, more secure, and more reliable access to governmental data systems. Consider it this way: if you were a fraud manager at a bank, access to a large collation of government databases could save hours of legal research and overhead with a simple cross-database search. 

Open, searchable databases made shareable between interdependent agencies (like between banks and merchants) could deliver the following benefits:

  • Industry Transparency
  • Shared Alert Systems
  • Greater Efficiency
  • More Accurate Data Analysis
  • More Informed Policies
  • Improved Products & Services

Most importantly, open data can have a profound impact on fraud detection and prevention methods.

With access to shared databases, companies can track and communicate incoming threats to other parties. They can share information regarding blacklisted users, detail data breaches, and pinpoint data insecurities much more effectively. 

How Can Open Data Improve Fraud Prevention?

Open data is used for countless different purposes by millions of people around the world every day. But how can this data help specifically address long-term fraud threats?

Open data is:

There When You Need It

Data analysis is a useful process that yields valuable intelligence. That said, determining where pertinent information is located and knowing how to collect it can be challenging. Many merchants assume they need to collect their own data, and if they don’t amass the information, there is no data available to analyze.

Fortunately, this is an incorrect assumption. An abundance of relevant consumer information is already available. As long as merchants know what information can help their fraud-fighting cause, they can start asking the right questions and getting the right answers.

Always Growing & Improving

Since databases are updated daily, open data is always growing and often improving in quality. The more contributions of data, the more comprehensive the resource becomes. Thus, open data is constantly growing in value and significance.


The fact that open data is evolving, growing, and changing in real-time means the information is dynamic. It’s far more valuable than static data generated by closed-circuit platforms.

Address verification, for instance, is not an open-source solution; rather, the data AVS relies on is proprietary information owned by the card networks. If a cardholder moves and forgets to inform the bank, AVS will yield a false positive. In this scenario, the merchant loses a legitimate sale. If merchant was relying on a dynamic solution to detect potential indicators of fraud, though, they could have saved that sale.


Not all data sources are universal. The relevance of a platform in regard to fraud prevention can often be limited to specific regions or localities due to differences in data infrastructure, regulatory requirements, and practices.

Proprietary, closed-data systems are limited by infrastructure constraints. Revisiting AVS, for example, one of the primary reasons it can’t scale on a global basis is that it would require credit card rails to be connected to issuing banks in other countries. This requires installation and agreements with each bank since the platform utilizes proprietary information. As a result, the owner of this system has only made an effort to connect with issuers in the US, Canada, and the UK.

Open Data Helps Prevent False Declines & Invalid Chargebacks

Open data may help eliminate many chargebacks that are not tied to third-party (“criminal”) fraud as well.

Unfortunately, illegitimate chargebacks are popular because many consumers tend to perceive first-party (or “friendly”) fraud as a “victimless crime.” After all, if the bank lacks an internal system to determine when a consumer has a history of disputing legitimate transactions, these customers are encouraged to offend repeatedly. 

Open data can help solve this problem. Access to open data enables merchants to definitively identify more cases of friendly fraud and successfully fight back. Each successful chargeback reversal helps enhance the education of cardholder responsibility and correct faulty consumer behavior in the shared pool of open data.

Open data could mean fewer false declines as well.

Merchants lost $443 billion to fraud detection false positives in 2020; that’s exponentially more than the actual cost of credit card fraud. Open data introduces another layer of data analysis, enhancing the manual review process by exposing assumed fraud indicators as benign threats.

Merchants may be able to better distinguish between valid transactions that might raise one or two red flags, and genuine fraud attacks. This lets them reduce unnecessary declines, consumer frustration, and revenue loss.

Are There Any Security Concerns Regarding Open Data?

There’s a preponderance of data breaches in the media and the cost of fraud climbing into the billions every year. It’s no wonder the term “open data” is so alarming for some. However, those fears are largely unfounded.

To clear up frequent confusion regarding this topic: open data doesn’t generally include any personal information. This isn’t to imply that personal data can never be shared through open data, but that it’s just not much of a threat.

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In theory, fraudsters could cobble personal attributes together and cross-reference them through various databases to identify specific individuals. However, the process of parsing and stealing that data would be extremely complex and difficult. The amount of work required means it simply wouldn’t be worthwhile to do.

Merchants can easily access open data with just the information already associated with an order—like email address, location, or phone number. The merchant has greater intelligence, advanced consumer authentication capabilities, and reduced fraud exposure. At the same time, consumers won’t be forced to supply additional information, and the process will not see any additional friction. 

Open data allows merchants to gather and analyze data they might not otherwise have access to. They can also benefit from valuable information without fearing security non-compliance. 

Have Other Questions About Open Data & Fraud Management?

Open data can be a valuable tool in the battle against online fraud… if merchants have the required insight and know-how to effectively leverage the information.

Even if merchants are capable of analyzing available data, the process demands significant resources, time, and money. This is where Chargebacks911® can help.

Chargebacks911’s proprietary technology is integrated with a multitude of intelligence sources. Our advanced data analysis capabilities produce unrivaled fraud detection and chargeback management results. In other words: merchants can reap the rewards associated with open data analysis without actually exerting the effort themselves.

If you’d like to learn more about the technologically-advanced capabilities of Chargebacks911 and how they can complement your current efforts, contact us today.


What is the main idea of open data?

Open data is any non-proprietary data available to be freely used and redistributed. The conditions under which this data is provided are what allow for redistribution and intermixing with other information. In the context of eCommerce and fraud prevention, for instance, open data is information that can be freely used and redistributed by different entities to validate digital transactions.

What is the difference between open data and public data?

Public data is made readily available by law and is searchable only within the public context of relevant data. Open data is a free and open series of databases maintained by commercial and governmental organizations intended to be shareable by anyone. While open data can contain public data, public data isn’t necessarily open data.

Does open data mean free?

Yes and no. Open data is intended to be freely exchanged by institutions and agencies. However, it does not necessarily provide access to personal or proprietary data that each industry may have access to. This means if you’re an agent or merchant with access to open data collection, you may — or may not — choose to offer access to select data elements through your platform.

What are the pros and cons of open data?

The main benefit of open data is that it is a self-improving, self-indexing, and  consistently growing information resource. This resource could be utilized by commercial entities and financial institutions to quickly and succinctly access necessary commercial databases with regard to whitelists and blacklists, fraud detection, etc.

Conversely, open data can cause data privacy concerns among consumers. In theory, fraudsters could cobble personal attributes together and cross-reference it through various databases to identify specific individuals. However, the process of parsing and stealing that data would be extremely complex and difficult. The amount of work required means it simply wouldn’t be worthwhile to do.

Who benefits from open data?

Everyone would benefit from open data over time. Merchants can easily access open data with just the information already associated with an order — email address, location, or phone number, for instance.

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