How to create an effective Collections strategy? 

Collections as a process in O2C have never been an easy one, and previously it was highly dependent on a reactive dunning model. This model meant waiting for customers to go past due dates before collectors started following up with them. While this model may have been adequate in the old economy, the current state deems it high-risk, if not obsolete. With more customers turning delinquent or failing to pay, significant effort and cost are expended to capture overdue payments.

Collection teams need to develop a strategy that helps them ensure the promise-to-pays are honored by analyzing customer payment behavior proactively to optimize working capital.

Two key collection strategies:

1. AI-driven Proactive Collections
In collections management systems, Artificial Intelligence (AI) is a prerequisite for preemptive dunning. It can assist teams with capabilities such as:

• Generating prioritized worklists
• Identifying at-risk customers before they default
• Predicting the date on which a customer is most likely to pay

2. Leverage the payment date prediction tool to reduce DSO

AI and ML can help collections management become more proactive by predicting payment dates at a customer or account level based on past payment behavior and current open invoices.

Having this type of data enables collectors to act before invoices and customers go past due. This, in turn, reduces the cost of dunning activities and allows a 10-15% improvement in DSO while also increasing the available working capital. It additionally improves collector’s efficiency by 30% because they can focus on developing dunning strategies for the more critical accounts while automating the low-risk ones.

Three big shifts in the collections strategy

• While an increase in payment cycle time was anticipated, the teams that leveraged a cloud-based automated collection process exhibited a lower increase in payment cycle time than industry benchmarks.

• One of the critical metrics that helped us understand the relationship between O2C’s A/R departments and their A/P counterparts was the number of payment commitments honored.
• Many companies use payment commitments as input for their cash forecasting models. If these commitments are not honored it substantially impacts their ability to forecast and manage working capital accurately.
• Potential Causes for payment commitments not being honored:
  • Collectors set payment commitments with customers under increased pressure to deliver faster even when they knew the probability of getting paid by the buyers was low.
  • On the accounts payable side, many buyers were unsure about their cash flow. They were making payment commitments to avoid any impact on their credit lines.
  • These reasons point to the need for a system that enables collectors to analyze the integrity of payment commitments and understand the customer’s ability to pay.

• To have an impact on working capital, collections teams grew more aggressive in collecting payments faster. The economic uncertainty pushed them to focus more on the 0–30-day aging buckets instead of the 60+ day bucket, which was earlier a typical priority.
• This strategy may work in the short-term; however, it’s not a long-term solution for two reasons:
  • It is difficult to scale this activity (correspondence, disputes, payment commitments, and communications, etc.) across the entire customer portfolio without a collections management system in place.
  • A continuous aggressive collections strategy impacts the customer experience.

Conclusion

Collections operations within organizations are in dire need of innovations that could improve the overall process efficiency and help optimize working capital. Transitioning from traditional methods of operation to more data-driven futuristic and scalable digital solutions is the way forward. Additionally, having global visibility across all A/R operations with the help of a platform that consolidates all the data from internal teams helps break silos and contributes to faster revenue growth.