Key Takeaway

• It is important to note that an efficient credit management system is what streamlines credit data aggregation, credit scoring, and approval. And it gives real-time visibility to your portfolio risk globally.

• It is important to choose the right credit management system. This is  to identify your other existing problems while considering maintenance, cost security, and timeline.

• When you make use of AI-based credit management system software it will simplify your credit management, mitigate risk. And the allowance of cash flows, is accompanied with real-time credit visibility and perfect streamlined workflows.



While discussing this question, it will be important to use the United States as an example. In the United States, about 97% of B2B transactions are made on credit. This is because allowing credit sales allows your business to grow. This will give the right foundation for a business relationship. It also boosts revenue, and gives working capital optimization. Thereby allowing companies to invest a lot of time, resources, and even money. This is to effectively execute an effective credit management system.

When you have an inefficient credit management system, you will discover that business organizations will not have the ability and the required expertise to be able to predict upcoming risks. This is to relate to customers going delinquent, and this will eventually lead to the following:

collections will be delayed

An increase in bad debt

Adverse impact on customer relationships.

A good credit management system process, should be able to forecast impending business risks. This is where the credit teams are expected to give the first line of defense, for their various organizations.



In the traditional credit management system in the B2B world, it is done in a manual way. That is serially, and this can be time-consuming and prone to errors. I have written below the major challenges faced by the credit teams in the B2B world:

The Slowness of Paper–Based Customer Onboarding:

Here credit teams Onboard customers by making use of applications that are mainly paper-based. The disadvantage of this manual paperwork is that it can miss results. And the non-completion of business information and slowness in bank and trade reference verifications. As said earlier the consequence is the delay in customer onboarding and this will affect the overall customer experience.

Manual Credit Data Aggregation, Credit Scoring, And Approvals:

This is an outdated method, where the credit teams have to manually download financial or credit reports from the various portals and regional credit bureaus. When they finish downloading the reports, the credit analyst will then review the credit ratings and finances manually and then calculate the credit score. This process is crude plus time-consuming which automatically leads to credit errors in approvals.

Lack of Real-Time Consuming Visibility into Portfolio Risk Globally:

During the periodic review the credit teams will have to struggle to discover at-risk customers, especially in this unpredictable economy. They are packed with loads of customer portfolios hence it’s very difficult to regularly review and be able to track changes in customers’ credit profiles.

Manual Review and Release of Blocked Orders:

In this crude traditional system when a customer exceeds his or her credit limit, the upcoming orders are usually blocked. Credit teams can either release blocked orders insistence without payment commitment or they can wait for collectors to collect partial payment which leads to ship holds and very poor customer experiences.

To overcome these challenges, the modern B2B credit management teams are more data-oriented and use advanced tools like Artificial Intelligence (AI) and Robotic Process Automation to be able to reduce bad debt and also allow cash flows. By making use of the automation system, credit teams will be able to streamline credit data aggregation, credit scoring, and approvals and will be able to gain real-time visibility into portfolio risk globally. The advantage of this is that it leads to a more efficient credit management system and a better customer experience.

Factors to Consider While Choosing the Right Credit Management System.

We should note at this juncture that an effective credit management system should be able to bring transparency and proactivity to credit risk management. It should be able to streamline all the business processes linked to credit management and also will be able to allow business organizations to deal with their everyday challenges using the following:

Giving faster customer onboarding with lowered overhead complexities.

Real-time access that can handle access to critical credit data for accurate credit decision-making.

Giving us better transparency and accounting for all process hierarchies.

Very reduced financial impact effect from any changes coming from customers’ financial situations.

Centralization of all system data across all businesses globally.

The existence of wide enterprise of a standardized credit policy.

The increase in credit teams’ productivity and efficiency through the lowering of errors and manual work.

Giving excellent customer experience backed with strong support to top-line business growth.

When you are choosing the right credit management system for your business, certain things have to be evaluated like identifying the problems your unique credit system is not solving or not having in your organization. You should bear in mind that all problems can’t be the same because what you are experiencing in your credit management system will not be what others or other organization of the same prototype is experiencing. Finding what problems you are facing in your credit management system is the number one solution to your specific problems.

The four parameters you should consider while choosing the right credit management system unique to your organization are as follows,



Risk and Security


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