What Are Automated Business Credit Decisions?
Automated business credit decisions are generally achieved via specific software that automates and manages the credit assessment functions of a company. Through the use of credit scorecards, the software is able to make a credit assessment using decision parameters to assess suitability and payment risk. Using automation, a typical credit transaction can be quickly completed, with the credit controller simply collating key information and entering it into the system.
The system will have pre-set criteria, and using those criteria will be able to assess the risk-level of an account and make a judgment on the correct course of action.
Generally, an automated business credit solution will provide the following :
A data interface or screens;
The ability to check a credit application against any blacklists or internal watch lists;
Flagging specific organizations or industries that may require detailed assessment;
Checking credit limits and payment histories of existing customers;
Appropriate bureau files for the company, its principals, and any potentially associated organizations;
Inspecting bureau files for pre-defined adverse rules;
Utilizing a bureau score or calculating risk scores;
An accept or decline decision, which could be conditional;
A link direct from the accounting/billing system to approved applications;
Workflow queues for required manual tasks;
Analysis and reporting to assist in reviewing the implemented rules.
Other Benefits of Automation
With automation, it allows the existing credit managers of the company to focus their attention on compliance management and complex transactions. Again, this reduces risk and exposure. The beauty of credit automation systems is that they can be added to or added onto existing IT infrastructure, outsourced via a third party company, or hosted through the Internet and accessed via a gateway or secure link. With the automation of credit decisions, the knowledge and skills of credit management professionals are still required in order to assess both high-risk and high-value decisions, but it does reduce the amount of time these skilled credit managers are spending on day-to-day credit decisions.
Through tighter controls of the accounts receivable process, automation increases the ability to track fraudulent payment behavior, in addition to improving adherence to corporate governance standards. In conjunction with scoring, automation helps improve cash flow through more consistent decisions and faster response times. It is also ideal for companies in managing their existing accounts because it quickly identifies both accounts that require attention and worrying risk patterns.
Is Automation Right for My Company?
The question is this: If automation is best practice, why it has not been adopted by more organizations? Perhaps the answer lies in challenging the status quo of operations. The barriers to adoption, or maybe we should say the perceived barriers, will generally fall under the following headings :
Technology: Will the technology I implement interact efficiently with my existing systems (ERP, CRM) and can the data be shared across the systems?
Cost, or Capital Expenditure: How much will it cost to both implement and manage a large piece of IT infrastructure?
Accurate Decision-Making: How can I be sure that the automated credit decisioning process will provide me with accurate information and provide data enabling me to make sound business decisions?
And there is another issue: Some credit teams believe that automated credit systems will make their expertise redundant; but in fact, nothing could be further from the truth. Yes, automation will make simple decisions quicker, thus allowing experienced credit managers to focus their skills and efforts on high-risk credit matters. In addition, introducing an automated credit decision system will benefit the credit collection function in the following ways:
Reducing duplication by keying in information at the point of sale;
Automating data entry and linking that data with existing customer relationship management systems;
Increasing revenue by freeing up time for skilled credit managers to increase overall approvals;
Reducing potential errors in opening accounts and reducing time spent in administering mundane tasks.
For many organizations, automated decisions and credit scoring play a critical role in the risk assessment process.
Automated credit systems also reduce the risk and potential for fraud by eliminating human interaction in the assessment process; making it easier to petition the accounts portfolio. In addition, it leaves credit managers with additional time to use their industry knowledge in making accurate risk assessments.
And finally, implementing an automated credit decisions process positions companies for growth, it adds agility to the new business process. Because automation speeds up a credit decision response, new customers are up and running and, more importantly, being billed much quicker than manual methods of approval.
So yes, there will be an initial outlay of cost; however, when building a case for an automated credit decisions process the following positives must be taken into account, improved efficiency, decreased fraud risk, simpler adherence to corporate governance requirements, and increased approval rates.
A key challenge with IT implementation is how will it interact with the IT infrastructure and existing systems of a company, and it is the same when you are developing a tool to automate credit decisions. In ensuring this concern is addressed, many of these automated tools deliver functionality by utilizing Web services, therefore not impacting the existing infrastructure on a company.
Software as a service works by hosting via the Internet, and the company uses the solution on an as-needed basis. There are a number of distinct advantages of using software as a service, including :
Saving Money: Lower IT costs Pay As You Go;
Technology budgets can be focused on competitive advantage;
You will have immediate access to the latest innovations;
Zero setup costs for supporting infrastructure upgrades, Fees are managed on a subscription basis;
If your business subscribes to a web hosted application using software as a service, your business will be free from supporting time-consuming, high cost IT functions to support the application. These costs might include:
The purchase and support of the server infrastructure required to both install and maintain the software inhouse;
Maintaining a patch and upgrade process, which can be labor intensive;
Providing the equipment redundancy and housing required to ensure reliability, security, and scalability.
Software as a service is as easy to use as simply flicking a switch, and it makes the application and updates readily available to the user. Companies are free to update to the latest technology when the vendors do, and costs can be managed via a regular subscription model. Obviously, the software as a service model woould not suit all business models, but it does offer a high degree of flexibility, especially for small companies who do not have the necessary infrastructure to warrant an embedded automation application. And this means that the cost savings mentioned above are even greater because there is not the same initial upfront cost.
The major aim of automating credit decisioning is to harness the skilled credit management resources of a company in order to focus on more important credit decisions. We are living in an era of continuing economic concerns and record unemployment, so the credit staff of a company must be maximizing their potential. Because we now have lower-cost automated solutions using technologies such as software as a service, the technology barrier is no longer prevalent. The cost barrier can easily be overcome because the skilled credit managers of the company are now free to focus on their high-value transactions, and the barrier of accuracy can be addressed by using multiple sources of independent data to wash against internal sources. In addition, because the skilled credit managers have more time to focus on the at risk clients, the organization is able to reduce bad debt through thorough investigations of potentially marginal deals.
More importantly, though, credit managers can concentrate on building a good credit profile which will enable sales teams to target specific customers that are attractive to the company.
Fortunately, the idea that automated credit decisioning results in a reduction of staff is rapidly being dismissed. The truth is that, in this current economic environment, automating credit decisioning allows for cheaper, faster, and more effective credit decisions, whilst allowing skilled credit managers to use their skills and knowledge to fulfill their capabilities in their given roles. In order to ensure that income continues to flow and organizations stay afloat, it is critical to have customers online and bill as quickly as possible.
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