This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Photo by Keren Fedida on Unsplash Each business customer presents a unique set of circumstances. Identifying the groupings within your customer accounts receivable (AR) portfolio enables you to deal with them all more effectively and efficiently. PLEASE NOTE: Due to the July 4th holiday there will be no post next week.
In this blog, we will explore the crucial role AI plays in accounts receivable, how it can benefit businesses, and the challenges it presents. What is Accounts Receivable? Accounts receivable refers to the outstanding money owed by customers to a business for goods or services provided.
They understood the dynamics that affected their customers and marketplace, as well as the credit controls needed to keep credit risk in check in this environment. They also kept very good records on their customers and their purchases, so there were no issues with transactional visibility.
Overall, it is an omni-channel solution that can plug into your transaction management system and start working right away. Note that with a high-risk merchant account you will likely have to accept higher monthly and per-transaction fees. In addition, card-not-present customers must verify their address.
Risk Segmentation Model With a standardized risk scoring system in place, the next step is to understand the results delivered and the differences between accounts that pose a highrisk of default and those that pose a low risk. They are also an additional source of variance across different AR departments.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content