“Despite collection analysts spending 75% of their time dunning, timely collections are dreadful!”

This is one of the most common challenges we hear from credit leaders during our Leadership Profile interviews. A reactive dunning process is slow and tedious, with time lost in building customer lists, sending emails, tracking promise-to-pays, and notes. Eventually leading to longer collection cycles.

Modern 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. Artificial Intelligence (AI)-driven Proactive Collections is a prerequisite for preemptive dunning, empowering your collections team with capabilities such as:

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

A Glance of What AI-Driven Collections Process Looks Like:

An AI-driven solution automatically identifies accounts at risk of delinquency based on customer credit scores and collection rules defined by your organization. It then prioritizes the team's worklist based on system-configured parameters such as payment history trend and risk score, among others. The AI-driven prioritized worklist helps the collections analysts focus on specific, high-risk customer accounts. Moreover, automating repetitive tasks like creating P2Ps, notes, and emails allow collectors to focus on other priority collection tasks.

The message is clear. Organizations seeking a competitive edge should leverage platforms with embedded Artificial Intelligence (AI) and Robotic Process Automation (RPA) capabilities instead of procuring additional platforms and tools.

Deep Diving on How an Integrated Platform Can Drive These Changes:

1. Predictive Collections Risk Scoring

Using pattern recognition and predictive characteristics, collection teams can effectively target accounts that pose the highest risk. 

Example of AI in Action-

• Payment date predictor – predict when a customer is most likely to pay based on experience and payment behavior.
• Late payment forecasting – looking in several places for payment due dates in multiple currencies is always going to be a challenge for clients who are reactive. This can result in customers only being contacted when payment is already late which can impact the financial close.

2. Boost Employee Productivity

The collections department has many repetitive, routine tasks that often involve manually building customer lists, sending emails, and tracking promise-to-pays and notes. 

AI has the power to disrupt the traditional collections back office. Automation can speed up mundane tasks with AI mining the data for insights. Ultimately helping teams take up new operational practices and support complex processes that add more value to the organization.

Example of AI in Action-

• Dynamic worklist prioritization – organizes a collector analyst’s worklist sorted by priority.
• Intelligent dashboards – one version of the truth that identifies the most critical customer/ account based on the past-due date details and the collection amount.
• Faster search times – a single platform allows the collection teams to function faster, decreasing their search time by looking for different sources of data at the start of each day.

3. Transforming Customer Interactions

Dunning is the most vital function in collections!

However with reactive collections, despite collection analysts spending their major time dunning, timely collections are often dreadful. The workflow is tedious, inefficient, and unscalable, leading to longer collection cycles.

Example of AI in Action-

• Quicker decision-making – Analysts can make quick decisions based on the intelligent action items populated by the system from the call.
• Automated dunning - through emails and A/P portal integrations the system enables the analysts to scale up dunning outreach with automated emails, and fax. Also helps consolidate customer’s email responses in collection software to eliminate switching platforms
• Intelligence to predict the next best action – collate all emails into a single repository. Digital assistants enable further automation by following up phone calls with suggested emails and action items based on the discussion with the customer
  
  Relying on traditional practices can put your AR at risk. With automation technologies now available at affordable prices, businesses can now take better control of their ROI and grow faster. By using machines to handle the tedious work and letting your analyst focus on more critical tasks, companies can increase their collection volumes and close accounts before they become overdue.

AI can do wonders, not just according to us but also the top finance executives. Have a look-

“By leveraging an end-to-end accounts receivable platform, we have been able to increase turnaround and response times, improve the effectiveness of collections and increase Straight-Through-Processing rates. This has been a critical key success factor in demonstrating value to other parts of the organization.” - Paul Buckham |  Global Process Owner, Order to Cash, AstraZeneca

“You need an integrated system or a one-stop shop with all the information in one place. Otherwise, it’s just more effort for you to search for the data from different sources. It gives you a holistic view of customer data. With automation, we were able to achieve a 67% reduction in average days delinquent and a 28% decrease in days sales outstanding” - Kay Rogers | Vice President-North America Financial Transactions, Ferrero

If you are interested in learning more about Autonomous Finance, please let us know here!