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B2B Fraud

What Is B2B Fraud?

Fraud between companies can interrupt the flow of business and destroy reputations. Moreover, it is becoming increasingly difficult to identify and prevent. According to PYMNTS, global markets lost $4.2 trillion in 2019 alone due to B2B fraud. However, machine learning can identify fraud accurately before it has occurred.


Why Is It Important to Have a Good B2B Fraud Model?

Fraud detection is one of the most useful applications of artificial intelligence. Specifically, the fraud model reveals attackers’ patterns of behavior so you can identify them in real time. As a result, you can avoid the fallout of a missing or delayed B2B payment.

What Internal Data Should I Have for a Good B2B Fraud Model?

In order to build a good fraud model, you should have a secure client list that includes company name, address, and financial information. Additional data can include a list of payment methods and encoding formats as well as contact details of anyone who made a transaction with the company. The easiest and most important step in prevention of B2B payment fraud is to verify the information provided by new potential clients.

What External Data is Essential for a Good B2B Fraud Model?

A good B2B anti-fraud model must first have a large database of partners. Information on anyone who has previously visited the business website also helps.

What External Data May Prove Useful for a B2B Fraud Model?

A black list of known scammers, an archive of B2B payment fraud incidents, and access to a watch list of international organizations like the Interpol or the FBI.

What Are the Main Challenges of this Use Case?

The biggest challenge is to find system weaknesses during transactions while ensuring that it is still flexible and won’t harm casual visitors.

Interesting Case Studies and Blogs to Look Into

Securing B2B Payments Report
Securing B2B Payments Report: September 2019

Tangible Examples of Impact

$8.5 million was stolen in an embezzlement scheme at construction company Marco Contractors, according to Pittsburgh Post-Gazette reports. The former controller at the firm, Sue O’Neill, reportedly admitted to the fraud in federal court last week, a scam she said involved manipulation of the firm’s payroll processes as well as accounts payable (AP). Reports noted that O’Neill allegedly issued payroll checks deposited directly into a separate company account, while also initiating wire transfers and writing company checks made payable to that company, subsequently manipulating AP records to suggest they were legitimate vendor payments.

Corporates Brace for BEC Scam Ramp-Up

Relevant datasets

Quadrant – Point of Interest (POI) Data

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Quadrant – Point of Interest Data measures physical store and website visits so companies can evaluate their performance. Quadrant provides nineteen different PoI categories; they also update their data regularly to provide the most efficient analysis.

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Ranker Data

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Ranker Data manages online audience preference data across an impressive range of media and lifestyle categories, from music to travel

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EntGroup Box Office

by EntGroup

EntGroup Box Office tracks daily and weekly box office rankings for Chinese, Hong Kong, and North American showings

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Prosper Insights & Analytics Data

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Prosper Insights & Analytics Data crafts customer personas with intent & sentiment data as well as modeling, predictive analytics, & more

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