Automation: An Ally for Deductions and Collections Management

What you’ll learn


  • Discover the challenges in deductions and collections management
  • Learn how AI improves the current landscape of deductions and collections
  • Understand how Ferrero was able to reduced its DSO by introducing RPA

In today’s digital world, companies are investing in a wide variety of technologies for standardizing complex processes to achieve improved efficiency and productivity. Companies are moving towards automation to gain competitive advantage, improve employee morale, and redirect most of their effort into the principal activities in a smarter way. Moreover, executing core competencies could improve business agility allowing companies to remain successful in the rapidly changing market.

The same implies to accounts receivables through automation. Though the idea of introducing automation in accounts receivables is not new, its popularity seems to have escalated, particularly from 2016. In Accounts receivables, modern-day software could easily help A/R teams overcome challenges in the collections and deductions management processes. Some of the clerical tasks manually done in these two A/R departments include –

  • Aggregation of backup documents
  • Documentation and data entry
  • Prioritization of worklist
  • Collections correspondences

All of these tasks could be easily automated to ensure faster payment and positive customer experience.

The Four Pillars of A/R Processes

The tasks involved in collections and deduction management fall into one of these four categories:

1. Repetitive Standardized Work
2. Collaboration
3. Data-Driven Decisions
4. Human Insight Based decisions

Manual Approach

Let’s look at what these pillars are and understand the impact of a manual approach –

Repetitive Standardized work such as dunning, reporting, and coordinating with brokers are essential for reducing DSO and improving A/R KPIs. Most of these tasks, when done manually, eat up a lot of time in an analyst’s day-to-day life, resulting in lowering efficiency and productivity of the A/R Teams.

Collaboration with internal salespeople is as important as with external partners, brokers, and clients to develop and implement well-defined strategies. If done manually, the time consumed is more than needed for efficiency.

Data-Driven Decisions require analysis, research, and validation. Hence its strategic value is always high. Manually, visibility is lost, and hence the data and information required for such analysis are hard to identify.

Human-Insight Based Decisions include identifying invalid deductions, prioritizing worklist, and proactively establishing credit terms for minimal risk exposure. Manually, executing these processes is challenging and involves a lot of data crunching and to and fro communication with other departments and clients.

Challenges

Manual deductions and collections processes come up with a ton of challenges. Here are some –

1. Repetitive tasks take up about 55% of the employee’s time, whereas, in an ideal scenario, it is supposed to be up to 5%, highlighting the non-value-adding part of work.

2. In deductions, companies are spending more than 40% of their time gathering data and evidence to check the validity of a dispute without any automation. Moreover, siloed-operations tend to hinder inter-team collaboration resulting in slow dispute resolution and poor recovery.

3. In collections, manual dunning becomes a very hectic and time-consuming process in the absence of any prioritized worklist.

Automation+AI= The Way Forward

“Automation saved 70% of analysts/broker’s time while providing better visibility.”

-Kathleen Rogers | Sr. Credit and Financial Services Manager of Ferrero

Typically, Collections, and Deductions Management processes, are more reactive than proactive. Since both of these processes are highly rule-based and manual, companies end up investing a lot of time and resources on them. With the advent of Automation and Artificial Intelligence, proactive strategies could make both collections and deductions management processes technology-driven. Moreover, AI and analytics could be leveraged in these areas to analyze customer data and gain insights on customer behavior and the company’s cash flow. Let’s look at the impact of automation and artificial intelligence in detail:

Automation

Automation

In the case of deductions management, implementing Robotic Process Automation(RPA) could enable automatic aggregation of all backup documents to check the validity of the deduction claim. In the case of collections management, automation could help with creating a prioritized worklist with reference documents for analysts to get started with following up past due accounts. Apart from that, features such as automated correspondence and a central repository for backup documents could help the collection team in outlining proactive collection strategies.

Artificial Intelligence

AI is considered a marvel of modern technology, and yet it would be quite an understatement. The limits of pushing AI to make business operations more efficient are currently endless. And that applies too in the case of A/R processes. In the field of Deduction Management, AI could be used to auto-resolve valid deductions. In the case of Collections, AI enables automatic prioritization of the worklist and helps in predicting payment dates based on customer payment behavior, resulting in more efficient cash forecasting.

Conclusion

Ferrero, the world’s 3rd largest confectionery company, introduced Automation and AI into their A/R practices to deal with similar challenges. Automation brought a seismic shift within Ferrero to subdue the hurdles faced in manual processes. It helped them to reduce their DSO and DDO, resulting in an overall efficient A/R process.

DSO and DDO after automation

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HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.