How Segmint transforms a financial institution’s transaction data into Key Lifestyle Indicators (KLIs)
Banking transaction data is notoriously difficult to wrangle. Transaction data is comprised of millions upon millions of rows of dirty, un-normalized, and often cryptic transaction strings. Segmint’s expertise lies in our ability to take this mess of data and transform it into a clean, normalized, and categorized set of labels called Key Lifestyle Indicators, or KLIs
KLIs are labels describing the type of transaction or behavior that a customer or member is engaging in. These are just a few examples of how transaction strings are transformed into KLIs:
Transaction String
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KLI
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*DEBIT AUTHORIZATION DEC02 02:38P XXXX AT 14:38 SBUX RIVERSIDE #0 RIVERSIDE
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Starbucks → Coffee Drinker
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SMITH NMAH WASHINGTON DC
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Smithsonian National Museum of Natural History → Museum Patron
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AB CXFOL WFHM
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Wells Fargo Home Mortgages → Competitive Mortgages
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We assign KLIs at scale and are capable of cleansing billions of transactions in a short period of time.
The great news is Segmint has already solved the data cleansing and labeling problem for financial institutions. This means, if you’re a financial institution, the most time consuming and laborious step in a predictive modeling initiative is already done.