User Defined Fields

Gain additional information for accurate decisions

Additional detailed business or industry information can be used in advanced analytics to gain insights to reduce fraud, improve business operations, or automate decisions

Make real-time decisions and adjust policies

With the control to create or edit UDFs, businesses can make decisions about their business or adjust policies, implementing UDFs as needed.

Reduce manual reviews and automate order acceptance

Additional customer information can be used to create “VIP lists” that can be used to automatically accept orders for known, good customers, or hold risky orders for further review.

Identify and accept more good orders

Additional information important to your business such as loyalty information or purchase or delivery details can signal good or bad customers, reducing or eliminating the need for manual review.

What Are User Defined Fields?

User Defined Fields (UDFs) are a Kount feature that allows businesses to capture additional text, dollar, numerical or date-related details from internal order management systems to help analyze orders and make improved and more automated accept/decline decisions. Up to 500 customizable UDF fields are available and can include information such as customer details, loyalty information, coupon codes, affiliate ID numbers, login details, purchase details, and event or travel dates and times. The additional data can be used post transaction to reduce chargebacks, as information to automate decisioning for known, good customers, and to analyze and improve business operations.

How Kount's UDFs Work

Businesses decide what factors are important to their vertical, industry, or unique needs and then add UDFs to collect the information that is meaningful to them. UDFs can be added in Kount’s Agent Web Console at any time. Each UDF has a name, description, and type that can be specified and immediately available for use.

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UDFs provide added insights for more accurate business decisioning

Up to 500 customizable UDF fields are available. The data helps businesses to analyze transactions for better, more accurate decisions resulting in reduced fraud losses and fewer false positives.

500 customizable fields

Capture unique business information

Real-time changes

Updates available for immediate use

Connected data

Aggregate multiple sources for better insights

Industry specific data

Additional industry-specific data for better decisioning

Types of User Defined Fields

Location information

In industries such as retail, travel and ticketing, details about location can be important to collect. For retail, this includes tracking details such as where the order originated. For travel, this includes departure and destination airports, countries, and flight routes. For ticketing, these details may include event location and ID. If the customer can’t be in that location at that time because the location doesn’t match other device and purchase-related details, this information triggers fraud alerts.

Customer and loyalty information

If a business has a loyalty program or members, automated decisioning can give these customers higher priority or preferential treatment to reduce friction and create an improved customer experience. Added customer information such as customer name and address, date of birth for the travel industry, account age, and more is highly valuable in any industry.

Purchase and delivery details

Industry-specific purchase details help to determine specialized fraud. Shopping cart data and coupon use is beneficial for retail, first and last purchase information is useful for digital retailers, device and payment type is useful for ticketing, and details such as booking source, payment amount and type, affiliate code, and voucher recipient are examples of useful travel-industry-related information.

Dates, times, and numbers

Account creation date, date of last transaction, and last account change date can help pinpoint account takeover fraud. Quantities such as the number of failed and successful login transactions and the quantity of previous transactions help determine good and bad customers, or fraudulent purchase information.

Login details

Dates and times of login as well as whether the customer made a purchase as a guest, can be significant fraud indicators.

Learn more about Kount’s UDFs

Download the Feature Sheet