Gartner’s Insights: Four AI-Powered Accounts Receivable Use Cases For Order to Cash

15 July, 2022
6 min
Vipul Taneja Vipul Taneja, VP, Finance Transformation

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12 min

Table of Content

Key Takeaways
Introduction
1. Blocked Order Prediction
2. Proactive Collection Prioritization
3. Disputes and Deductions Validity Predictor
4. Data Capture from Remittances
Conclusion

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Key Takeaways

  • The modern CFO’s priority has shifted towards automating Order to Cash (O2C) operations. AR leaders need a robust tech stack to transform O2C processes and improve financial performance.
  • Blocked order prediction, proactive collection prioritization, disputes and deductions validity prediction, and data capture from remittances are some of the in-demand AI-driven capabilities for AR solutions.
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Introduction

Gartner’s Magic Quadrant is a research methodology and visualization tool that assesses technology markets. It visually represents vendor positions based on their vision and execution within a specific market segment. The Magic Quadrant aids organizations in vendor evaluation by considering factors like product offerings, market presence, and customer satisfaction. While widely used, it’s essential to consider other factors before making procurement decisions.

Gartner has traditionally focussed on publishing Magic Quadrant reports for the critical office of the CFO functions like Financial Planning and Analysis (FP&A) and Procure to Pay (P2P). They released the first-ever Magic Quadrant report for Integrated Invoice-to-Cash Applications in 2022, signifying a shift in the CFO’s priority towards automating Order to Cash (O2C) operations.

Most O2C processes like credit monitoring, collections, deductions/disputes, and cash application have been operating in silos, making it challenging for businesses to recover their working capital trapped in receivables. AR leaders today need to build a robust tech stack that addresses the limitations of the traditional legacy software to transform O2C operations and create an agile function. In the Magic Quadrant report, Gartner elaborates on the technologies that are changing the entire landscape of O2C transformation today.

Gartner predicts that integrated I2C vendors are enhancing their AI capabilities with advanced analytics, leveraging customer and market data to offer actionable insights. This includes early AR risk identification, intelligent collection prioritization, and predictive insights. These AI-driven capabilities are expected to become a standard offering among vendors in the future.

Additionally, it predicts that vendors in the I2C market are increasingly expanding into new geographies through mergers and acquisitions (M&A), with a focus on North America and Europe. These strategic M&A activities help vendors broaden their solutions, tap into new customer bases, and address localization needs. Gartner anticipates a continued increase in M&A as vendors consolidate and expand their offerings.

This blog draws insights from the Gartner report and deep dives into the four must-have Order to Cash use cases where Artificial Intelligence(AI)-powered technology can help AR leaders create significant working capital improvements in the office of the CFO.

1. Blocked Order Prediction

Gartner’s Recommendation – A solution that predicts upcoming orders likely to get blocked by processing a customer’s historical transactional data (like their credit scores and credit limit) and analyzing their payment history and credit utilization to look for credit risk level changes.

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Blocked order prediction is a crucial component of efficient accounts receivable management that harnesses the power of artificial intelligence (AI) to proactively anticipate and prevent order blockages. In Gartner’s comprehensive report on AI-powered accounts receivable use cases, they delve into the significance of this predictive capability. By leveraging AI algorithms to analyze historical data and real-time factors, organizations can identify patterns and indicators that may lead to order blockages.

The implementation of blocked order prediction allows businesses to take proactive measures, addressing potential issues and ensuring a smooth order processing workflow. The report emphasizes the wide-ranging benefits of this approach, including enhanced operational efficiency, reduced revenue loss, and improved customer satisfaction. With AI-powered predictive analytics, companies can identify potential bottlenecks such as credit limit breaches, payment delays, or delivery issues before they occur. This enables timely intervention, such as reaching out to customers to resolve outstanding issues or making necessary adjustments to credit limits, thereby avoiding order blockages.

By integrating blocked order prediction into their operations, organizations can optimize their order-to-cash process, minimize disruptions, and deliver a seamless customer experience. This AI-powered solution empowers businesses to stay ahead of potential challenges, effectively manage their accounts receivable, and maintain strong relationships with their customers.

2. Proactive Collection Prioritization

Gartner‘s Recommendation – A solution that analyzes customers’ payment trends to segregate and prioritize the customers for dunning activities like sending follow-up correspondences.

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In the realm of accounts receivable management, proactive collection prioritization emerges as a key AI-powered use case, as highlighted in Gartner’s insightful report. This approach leverages artificial intelligence (AI) algorithms to analyze a variety of data sources, both internal and external, to prioritize collection efforts effectively.

By leveraging AI capabilities, businesses can analyze customer data, payment histories, and external factors such as economic indicators and industry trends to identify accounts with the highest collection priority. This approach allows companies to allocate their collection resources more efficiently, focusing on high-risk accounts or those likely to generate the most significant returns.

The benefits of proactive collection prioritization extend beyond improved efficiency. By targeting collections efforts where they are most needed, organizations can accelerate cash flow, reduce days sales outstanding (DSO), and minimize bad debt write-offs. Additionally, this approach facilitates more personalized and strategic customer engagement, fostering stronger relationships and customer satisfaction.

In summary, proactive collection prioritization powered by AI empowers organizations to make data-driven decisions and optimize their collections process. By identifying high-priority accounts and implementing tailored strategies, businesses can enhance their financial performance, improve cash flow, and strengthen customer relationships. If you’re looking to improve your accounts receivable management, consider leveraging AI-powered collection prioritization to streamline your processes and improve your bottom line.

3. Disputes and Deductions Validity Predictor

Gartner’s Recommendation – A solution that leverages insights from shipment and delivery data like Bill of Lading (BOL) and Proof of Delivery (POD) and analyzes the historical trends of the customer making payments and raising dispute claims to predict the validity of a new dispute/deductions.

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The ‘Disputes and Deductions Validity Predictor’ is an innovative tool that empowers organizations to proactively manage disputes and deductions in their accounts receivable processes. Gartner’s report emphasizes its significance in enhancing efficiency and effectiveness in dispute resolution.

By harnessing advanced analytics and AI algorithms, the Disputes and Deductions Validity Predictor analyzes historical data, customer behavior patterns, and other relevant factors to accurately predict the validity of disputes and deductions. This enables businesses to optimize resource allocation, focusing on cases with higher chances of success.

This powerful tool provides valuable insights that drive data-driven decision-making, streamline dispute resolution processes, and mitigate the overall impact of disputes on financial performance. Prompt and accurate resolution of legitimate disputes further enhances customer satisfaction.

In summary, the Disputes and Deductions Validity Predictor leverages analytics and AI to predict the validity of disputes and deductions, enabling organizations to optimize resources, improve efficiency, and foster stronger customer relationships. Enhance your accounts receivable processes by leveraging this innovative tool for streamlined dispute management.

4. Data Capture from Remittances

Gartner’s Recommendation – A solution that can aggregate and process the payment and remittance information from various sources (emails, EDIs, customer A/P portals) and multiple payment formats (EFTs, cheques) to match the customer payments against the open invoices automatically.

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Data Capture from Remittances is a crucial process that enables organizations to extract valuable information from remittance documents, driving efficient accounts receivable management. Gartner’s report underscores the significance of automated data capture in enhancing accuracy and streamlining workflows.

By harnessing advanced technologies such as optical character recognition (OCR) and intelligent data extraction, organizations can extract relevant data from remittance documents, including payment details, invoice numbers, and customer information. This automation minimizes manual data entry errors and accelerates processing time.

Automated data capture from remittances delivers numerous benefits. It improves data accuracy, eliminates bottlenecks caused by manual data entry, and enhances overall accounts receivable process efficiency. Timely and accurate remittance data capture enables improved cash flow management, reduced processing costs, and heightened customer satisfaction through faster payment reconciliation.

In summary, Data Capture from Remittances plays a critical role in modern accounts receivable management. By embracing automated data extraction, organizations can optimize workflows, enhance accuracy, and unlock operational efficiencies. Implementing cutting-edge data capture technology yields significant improvements in financial performance and customer relationships. Empower your accounts receivable processes with automated data capture from remittances today.

Conclusion

Insights from the Gartner Magic Quadrant report on Integrated Invoice-to-Cash Applications highlights the importance of a strong tech stack with integrated capabilities to reduce DSO, DDO, bad debt, and enhance financial performance.

There are four quadrants in Gartner’s Magic Quadrant:

  1. Leaders: Vendors in the Leaders quadrant are considered to have a strong ability to execute their strategies and a clear vision for the market. They typically have a significant market presence, offer comprehensive products or services, and demonstrate a track record of customer satisfaction.
  2. Challengers: Vendors in the Challengers quadrant have the ability to execute their strategies but may have a less complete vision for the market. They may have a strong market presence, but their offerings may lack certain features or innovation compared to Leaders.
  3. Visionaries: Vendors in the Visionaries quadrant have a strong vision for the market and may demonstrate innovation and differentiation in their offerings. However, their ability to execute their strategies may be less proven or may lack a significant market presence.
  4. Niche Players: Vendors in the Niche Players quadrant have a more narrow focus, specializing in specific market segments or offering niche products or services. They may have limited market presence or a less complete vision compared to other quadrants.

HighRadius is a global provider of integrated solutions for AR teams, addressing the limitations of traditional O2C software through data and advanced technologies. In the 2022 Gartner Magic Quadrant report, HighRadius was recognized as a ‘Leader’, securing the top position with the highest scores for ‘Ability to Execute’ and ‘Completeness of Vision’.

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