Capability of Speed, Accuracy and Scale Unparalleled in the Industry; Executed project that classified $1 trillion in transaction dollars in one day
Segmint Inc., a fast-growing global leader that has been causing disruption in the financial services industry with its data-driven customer insights and analytics platform, announces it recently classified through data cleansing $1 trillion in payment dollars in a single day for a large financial institution. Transaction cleansing is a critical tool that allows financial institutions to better understand customer transaction behavior and model spend patterns.
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This work was executed with Segmint’s Merchant Payment Cleansing service, designed to remove the complexity of transaction detail data for financial institutions. With the normalization and classification of $1 trillion in payment dollars, this financial institution was able to realize the flow of payments through their systems, while signaling and modeling the impact of economic activity.
The Merchant Payment Cleansing service leads the industry in terms of the speed, accuracy and scale of transaction processing. These differentiators also drove Redstone Federal Credit Union to select Segmint as its Merchant Payment Cleansing provider, after conducting a rigorous head-to-head comparison of vendors in this space. In this bake-off, 17 million transactions were cleansed totaling $2.3 billion, allowing Segmint to set the bar in the industry in both total count records where the merchant was identified and the granularity of merchant categorization. More than 10x the number of detailed merchant categories were assigned than the leading competitor.
“Segmint provided us clean data to fully identify member transaction activity, unlocking new insights that will influence critical decisions about products and services offered to our members. Additionally, this cleansing produced unique data that allows us to better serve and preserve our relationships with member cardholders and drive strategic product decisions,” said Raj Prasad, Sr. Assistant Vice President, Data Science and Analytics from Redstone Federal Credit Union.
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The content of merchant payment transactions is often cryptic and non-descript, with a significant number of transaction variants for a single merchant, making it difficult to distill into a merchant name. The variations can be significantly widespread, even on major brands such as Amazon, which alone encompasses more than 1.1 million variations of transaction detail. Segmint’s extensive transaction analytical toolkit has distilled over 90 million variations of transaction descriptions into over 44,000 merchant tags describing the merchants and institutions that customers transact with. To date, Segmint’s automated process combined with the granularity of human scientific research has scrubbed more than 20 billion customer transactions to deliver merchant name and levels of merchant categorization; this process produces highly accurate result with specificity on the data.
“Our data cleansing services lead the industry in speed, accuracy, and scale, giving our clients data analytics usage and the ability to model spend and behavior patterns. We add ‘real humans’ to our process to ensure that the quality of our data lives up to the absolute highest standards”, said Adam Craig, President of Segmint, Inc. “This ranks us at the top amongst the competitors in the market.”
