Payment Data Enrichment
Mireia Tomàs

Advancements in Fraud Detection using Payment Enrichment Data

As you may already know, in the digital world we increasingly live in, fraudulent activities in finance are a major problem for both companies and individuals. Simultaneously, advances have been made to develop solutions that prevent risks and detect fraud in a timely manner. One of these solutions is data enrichment. Thanks to this technique, companies are able to enhance their security measures and protect themselves from potential threats. In this post, we will explore the concept of payment enrichment data and discuss the advantages it brings to fraud prevention.

Understanding payment data enrichment

FUnderstanding payment data enrichment

First, it is important to define the following concepts: data, enrichment, and payment.

  • Data: Data refers to raw and unprocessed facts, statistics, or information collected from various sources.
  • Enrichment: Inference of additional structured data based on the raw data available through various methods.
  • Payment: A payment is a financial transaction where funds are transferred from one party to another using various methods like cash, checks, cards, bank transfers, or online platforms. Payments serve various purposes, including purchasing goods/services, bill payments, or making donations/gifts.

If you want to know how a payment works and how a payment is enriched you can read our posts.

So now we have defined the concepts it will be easier to understand what is payment data enrichment. We have already established that data is the unprocessed facts collected from various sources, enrichment is the process of enriching raw data and finally payment is a financial transaction. Payment enrichment data is the process of adding additional information associated with a payment transaction beyond the essential details such as the transaction amount, date, and recipient. Payment enrichment data can include customer data, location information and other relevant contextual details.

As you can see in the left mobile, the data displayed lacks data enrichment. It only displays basic information, making it difficult to understand the transaction details accurately. However, the right mobile showcases enriched data, including the name and brand logo, category, whether the payment is online or offline, and if it is a subscription or not. This enriched data provides a clearer and more comprehensive view of the transaction.

The Role of payment enrichment data in fraud detection

Payment enrichment data enables the following aspects of fraud detection:

  • Risk Assessment and Scoring: By analyzing enriched payment data, it becomes possible to assess the risk associated with transactions. Additional attributes and information can be used to assign risk scores, helping identify potentially fraudulent activities.
  • Behaviour and Pattern Analysis: Enriched payment data provides a broader view of customer behaviour and transaction patterns. By analyzing this data, it becomes easier to identify deviations or anomalies that may indicate fraudulent activities.
  • Clustering and Learning: Through accessing a more structured and streamlined “clean” representation of the transaction data, it becomes easier to categorize the transactions and find similarities with earlier data points (potentially deemed fraudulent).

To illustrate the importance of data enrichment, let's consider a real-life example: 

"A user of a neobank noticed suspicious transactions appearing on their account, showing a purchase at Leroy Merlin (a home improvement store) that they did not make. Although the amount seemed familiar, the location did not match. Their initial reaction was to contact customer service to report the incorrect transaction, suspecting card theft. However, upon further examination, they realized that the payment was indeed correct but was made at a gas station, not Leroy Merlin. In this case, the payment enrichment data was incorrect, leading to confusion and a mistaken assumption of fraud."

By enriching payment data with additional attributes like geolocation and fraud scores, banks can detect suspicious patterns and proactively prevent fraud. This not only safeguards customers' accounts but also protects the bank's reputation and financial interests.

Benefits and challenges

Conclusion

Advancements in fraud detection using payment enrichment data have significantly strengthened the ability of businesses to combat fraudulent activities. By harnessing the power of payment enrichment data, organizations can enhance their fraud detection systems, mitigate risks, and protect both themselves and their customers. As technology continues to evolve, payment enrichment data will continue to play a crucial role in staying one step ahead of fraudsters and ensuring secure online transactions.

At Triple we analyze user transactions and identify any suspicious behaviour that may indicate fraudulent activity. If you want to talk to our sales team to know more about our solutions, we would be happy to see how we can help you.

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