BANKING TRANSACTION CATEGORIZATION: LEVERAGING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE IN THE FINANCIAL INDUSTRY - ICAP CRIF

BANKING TRANSACTION CATEGORIZATION: LEVERAGING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE IN THE FINANCIAL INDUSTRY

EXECUTIVE SUMMARY OF BANKING TRANSACTION CATEGORIZATION

Open Finance and Open Banking are revolutionizing the financial services industry by making structured and especially unstructured data available from multiple sources (banks, telcos, insurance companies…) through multiple channels (scraping, OCR, API, etc…) and at a very high rate.

It is imperative to bring order and structure to these unstructured assets in order to extract useful information for the customer, thus opening the door to the opportunities offered by the open data economy, which requires the use of advanced analytics tools.

Categorization engines enrich financial transaction information by adding a “category”: a name that gives a meaningful description of the nature of the transaction (e.g., “salary”, “mortgage”, or “food and daily expenses”). To accomplish this task, the engine classifies the data according to some sort of criteria, such as merchant, location, or transaction amount.

Read more and download the white paper, here.

 

 



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