Products > Data Science in Banking > Merchant Payment Cleansing

Merchant Payment Cleansing

How can you truly understand consumer transaction behavior when merchant payment descriptions are so varied?

The transaction data that is available to describe your customer’s retail purchases, payments to competitor and other services is often so complex it is unusable. The content of merchant payment transactions is often cryptic and non-descript. And, the significant number of transaction variants for a single merchant makes it difficult to distill into a merchant name.

However, as a result of Segmint’s merchant cleansing process, we can unify standardize, and transform this complex transaction data into actionable, easy-to-use customer insights for your entire institution.

Through Segmint’s pre-integrated access to complete core and transaction data, including more than 1000 financial institutions, we have been able to:

  • analyze and store hundreds of millions of transactions
  • establish data mapping to non-partners cores
  • cleanse and categorize over 30,000 merchants and financial institutions

How can you truly understand consumer transaction behavior when merchant payment descriptions are so varied?

Transaction Description Variation Examples

#1 – Retailer Identification

CHK PURCH PINT THE HOME DEPO

FIP NST THE HOME DE

BENEFIT MOBILE DEBIT E THEHOME DE POT

Quantifying the Problem

  • Multiply 4+ Variations by 3.8 M US Retailers
  • Furthermore, millions of local merchants are difficult to identify both name and industry at scale.

Transaction Description Variation Examples

#2 – Competitive Bank Identification

WELLS_FARGO CC ONLINE PMT

WF HOME MORTGAGE WELLS523 CHECKPAYMT

Quantifying the Problem

  • Multiply 2+ Variations by 11,179 federally insured banks and credit unions
  • Multiply by other private lenders, mortgage lenders, auto lenders, and fintechs

Transaction Description Variation Examples

#3 – Competitive Bank AND Product Identification

CAP-ONE CARD US CREDITCARD

CPT ONE CREDIT CAR CAPITAL ONE CREDIT CAR 877-488-0757 VA

CAP ONE CARD SERV ONLINE PMT

CAPITAL ONE CREDIT CRD CHECK PYMT

WELLS FARGO CARD WFBCARD CHECKPAYMT

WELLSF CARD CCPYMT

WF CC ONLINE PMT

Quantifying the Problem

  • Requires two-part identification of both the institution (e.g. Wells Fargo) and the product (e.g. Credit Card).
  • Multiply 7+ variations by 11,179 institutions and all banking products and services including mortgages, credit card, auto lending, wealth management etc.

How? We turn inaccurate merchant data into great customer insights with Key Lifestyle Indicator (KLI) taxonomy

Segmint’s proprietary KLI taxonomy is a robust classification system that categorizes descriptive data tags.

High-Level Segmint Process:

  • Analyzes transactions and banking behaviors
  • Matches the transaction to a merchant and applicable KLI data tag
  • Categorizes the KLI into a taxonomy of KLI data tags
  • Sense lifestyle, life event, and brand preference of consumers

A clear picture of product ownership and banking behavior.

When you have clean merchant data and KLI taxonomy throughout your core data you can engage with your data in a whole new way that expands both the view of customer’s lives as well as your opportunities for communication and creative problem solving.

Questions about how Segmint can help you?

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