Data Integration Guide - E-Marketplace Seller Risk

Seller Onboarding & Vetting

Marketplace seller onboarding, as well as merchant vetting, are important drivers of DataVisor’s ability to identify marketplace seller risk. This document serves as a general integration guideline for identifying registration and catalog data as it pertains specifically to marketplace sellers.

Recommended Seller Registration Event Data

Fields that are helpful for marketplace registration use cases include (but are not limited to):

 

Category

Data Field

Description

Required


Datavisor Required Fields



Event Type

Seller Sign-Up/Registration

X

Event Time

Sign-up/Registration Time

X

Entity ID

Seller ID

X

Seller Profile Information















First Name

First Name

X

Last Name

Last  Name

X

Date of Birth

Sellers Date of Birth

X

SSN

Social Security # - Individual Seller

 

Business Entity Name

Legal Business Name

X

DBA Name

“Doing Business As” Name

X

Tax ID Number (EIN)

Tax Identification Number

X

Tax Classification

U.S.(W9 or W-8 ECI) or LLC, S-Corp

 

Business Entity Type

Private/Public

X

Incorporation State

State where business is registered

X

Business Address

Registered Business Address

X

Business Email

Email

X

Business Phone

Phone

X

Company URL

Associated Business URL

 

Bank Name

Bank Name Linked to Business

 

Bank Account Number

Bank Account Linked to Business

 

Registration Status

Status of Seller Registration

X





Device Intelligence






Device Identifier

Unique Device ID

 

Device Model

IPhone10

 

Device Operation System

IOS

 

Device OS Version

Operating System Version

 

Device User Agent

User Agent String

 

Device RIsk Score

Risk level of device

 

Geolocation

Ip Address

Ip

 

 

Existing Seller Data Hydration

The data fields listed above have proven effective when utilized in risk detection for marketplaces looking to onboard and verify prospective sellers. To ensure data from existing sellers is available within Datavisor, we typically execute a one-time profile dump to warm up the system. This seller profile dump can contain the same data elements seen with new registrations but the event time should reflect the original registration timestamp.

 

An example of seller registration data:

US Business Tax ID (EIN)

Legal Business Name

DBA Name

Entity Type

Seller First Name

Seller Last Name

Tax Class

Company URL

12-3456789


DataVisor, Inc.

Datavisor

Private

Mark

Frost

W9

info@datavisor.com

12-9932424

LowPrices Co.

Low Prices

Public

Grace

Smith

W-8 ECI

lowpricesco.com

 

Recommended Seller Catalog Listing Event Data

Fields that are helpful for marketplace catalog risk use cases include (but are not limited to):

 

Category

Data Field

Description

Required

Datavisor Required Fields

Event Type

Item_Listing

X

Event Time

Sign-up/Registration Time

X

Entity ID

Seller ID

X

Catalog Information

Item ID

SKU/UPC/ISBN

X

Item Name

Item Name

X

Item Description

Description of listed Item

X

Item Category

Category of Listed Item

X

Item Sub-Category

Product Sub-Category

X

Item Unit Price

Base Unit Price for Item

X

Available Item Quantity

Number of available units

X

Active Item Discount

Current Item Discount Rate

X

Device Intelligence

Device Identifier

Unique Device ID

 

Device Model

IPhone10

 

Device Operation System

IOS

 

Device OS Version

Operating System Version

 

Device User Agent

User Agent String

 

Device Risk Score

Risk Level of Device

 
Geolocation

Ip Address

Ip

 



An example of catalog listing data:

Item UPC

Item Name

Item Category

Item Sub-Category

Item Unit Price

Item Quantity

Item Discount

03600029145


Fraud Fighter

Collectibles

Action

45.89

400

0.00

03600023345

ATO Shield

Toys

Outdoor

123.65

50

0.00



Data Structure Report

Before sending the full data over, please send over a data structure report to your Technical Account Manager. This process allows DataVisor to ensure a faster turnaround time and a higher quality of results during the fraud assessment. This data structure report should contain the following for each data set:

  • Schema
  • Preview of 10 rows
  • Earliest date and latest date (If there is an associated timestamp)
  • Number of rows

Data Anonymization

DataVisor’s algorithm is able to work with anonymized data fields if required. For sensitive PII information, such as name and address, anonymized information can be processed by our algorithm as long as the data structure remains.

Choosing a Connection Type: Batched or Real-time data transfer

For a batch data transfer, the client sends data in bulk to DataVisor. The frequency of batch data transfer is determined by client’s use case and business requirements. Batch transfers are faster to implement, as they don’t require an integration with DataVisor’s APIs. Account application data should be given as is at the end of the batch time period, and included in the batch. 

Real-time data connection

For a real-time data connection, the client integrates DataVisor’s APIs to send a real-time stream of data. After a ~2 week observation and tuning period, DataVisor returns real-time results, which can be used as an additional signal in the client’s fraud detection infrastructure. All account application data should be uploaded at the beginning of the fraud assessment. 

Formatting and transferring data

Formatting Data

DataVisor can accept data in the following formats:

  1. JSON (preferred) 
  2. Tab Delimited
  3. CSV

For other formats, like TXT or report exports, please contact your Technical Account Manager.

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