AR Intelligence—Bank Utilization

The Bank Utilization Dashboard lets you review the customer landscape by consolidating customer accounts for a holistic view of a customer’s indebtedness based on the bank account they pay from.

Data quality is a challenge for most companies that operate with large volumes of trading customers.

For several reasons, customer master data can be difficult to maintain. For example, a fictional customer, Joe Suggs Builders, may have several different accounts on the sales ledger with different naming conventions. This means that there is no awareness that it’s the same business that is trading. This same customer may be listed in many ways in your systems:

• Joe Suggs Builders Limited

• J. Suggs

• J. Suggs Builders

• JS Builders Ltd

• Joe Suggs

This can occur because of acquisitions, when there are multiple trading divisions and/or business units, or simple human error.

This dashboard and report provide an understanding of the overall risk exposure by viewing customer accounts linked by the same bank details, or sales ledger accounts linked by payee details, to understand how customers are paying and for which accounts.

As you can see from the example below, we have grouped the entire sales ledger by customers paying from the same bank account (note: one-to-one payments are excluded).

With the dashboard, we can instantly provide intelligence to report on these kinds of scenarios and provide data that lets you act more easily and quickly. By going into one of the accounts, we provide you with the listing of all accounts linked to the one bank account with the following information:

• List of all accounts’ total debt, split by debt that is overdue and debt not yet due for payment

• Overall sales trend of the customer using all accounts listed

• Payment trend of the customer using all accounts listed

• Summary of the accent activity including total number of invoices, total value of invoices (less credit notes), and the total value of payments received from the customer across all accounts

• Summary of current position for debt outstanding split between overdue debt and debt not yet due

This view, built by intelligence gathered through allocating payments through the Cash Application platform, overcomes data challenges of accounts not associated by name on the sales ledger.

This intelligence can be used across divisions or trading entities and helps eliminate multiple credit team members contacting the same customer, while helping you make better decisions on credit extension and debt collection. Decisions are now made from a platform of knowledge across all the associated accounts.

This new-found intelligence may prompt you to address questions such as:

• View total debt split by due/not due values. Is the credit limit cover sufficient for the group of trading accounts? What impact does the total have on the confidence of credit given?

• Does the payment pattern differ between accounts? If so, why? Is it because the collection strategy is different and there is an opportunity to improve?

• By viewing the volume of sales and payments by the grouping of customers, would this take them into a different commercial agreement?

You can also use the bank utilization intelligence to:

• Assess unusual activity or trends, for example, perhaps the largest of the accounts has moved from electronic payment to check, or there has been an increase in credit card payments in recent months

• Observe changes in sales activity, for example, are any of the accounts frequently maxing out their credit limit and then paying beyond typical payment performance

• View last 12 months of activity regarding the number of invoices, value of invoices, and value of payments received for a group

• View the method of payment received for each sales ledger account in a group and ascertain if there any unusual trends (like our example above with the largest account moving from electronic payment to check)

Risk – Visibility of Global Exposure

Using the previous example for Joe Suggs Builders Limited, you many well be confident in providing a £10,000 credit limit for that business. But, if the same criteria are applied to each of the five accounts in the previous example, would you confident in wanting to offer £50,000 credit in total?

This allows closer control of the risk being granted to customers and highlights, quickly and easily, any accounts that need consolidation and review of the total credit being granted.

Productivity

Time is valuable. So, you need to be sure you have an efficient utilisation of the AR and Credit Control teams, which result in increased cash collections through greater coverage of outgoing calls and general collections tasks.

You don’t want your AR team sorting data or correcting misallocations because accounts were not linked. Rather, they should spend time collecting cash and managing risk.

Data Integrity

The utopia for any department is to have clean and up to date information. This reporting functionality enables you to cleanse your data easily and quickly without using costly third-party providers.

Having up to date data means you are making better informed decisions on customers, whether it be collection strategies or risk.

Also, you’ll eliminate the need for large data cleansing exercises and spend time and resources on actions that will drive results and add value.

Customer Experience

This could impact customer experience in several ways such as reducing the chance of being contacted by multiple people at different times for payment or the misallocation of payment to one or several accounts, which could lead to some of the accounts suspending services incorrectly.

Get your copy of the exclusive white paper New Questions to Gain New Intelligence in Accounts Receivable to discover the questions that can challenge your assumptions and help improve your outcomes, objectives, and critical results.