The Mantra To Happiness For Accounts Receivable Teams

The Mantra To Happiness For Accounts Receivable Teams

For some AR Teams, it might feel like another time, another life, but for most AR teams, the process of payment matching had its own set of challenges which not only consumed time but was prone to errors:

1. Labour Intensive and Time Consuming

  • Manual Data Collection: AR teams had to manually retrieve bank statements and payment advice from different sources (emails, portals, etc.), which consumed a lot of time.
  • Slow Matching Process: Manually matching payments with invoices was extremely labour-intensive, especially if the amounts were different or if the payment involved multiple invoices.
  • Follow Up with Customers: If payment advice was missing, AR teams had to manually contact customers, and that used to cause additional unnecessary delays.

THE IMPACT:
The process slowed down cash application and delayed cash flow visibility. The time spent manually matching payments reduced AR team productivity.

2. High Error Rates

  • Data Entry Errors: Manually inputting data from bank statements and payment advice into ERP systems increased the likelihood of human error.
  • Incorrect Invoice Matching: Due to the complexity of matching, incorrect allocations happened frequently, leading to errors in financial records.
  • Miscommunication with Customers: Follow-up emails for payment advice were many a times mishandled or missed, leading to prolonged disputes or misunderstandings.

THE IMPACT:
Errors in payment matching can result in incorrect customer balances, inaccurate financial reporting, and prolonged reconciliation cycles.

3. Lack of Standardization

  • Varied Payment Advice Formats: Different customers provided payment advices in varied formats (PDFs, emails, handwritten notes), making it difficult for AR teams to standardize the process.
  • Nonstandard Bank Statements: Banks often provided statements in different formats, further complicating manual reconciliation efforts.

THE IMPACT:
Lack of standardization required additional effort to normalize data before processing, increasing the overall time and complexity of the task.

4. Inconsistent Cash Application

  • Delayed Posting in ERP: Due to manual bottlenecks, payments were not immediately applied to the corresponding invoices, delaying real time visibility into open receivables.
  • Complexity in Handling Multiple Invoices: Payments that covered multiple invoices or partial payments created additional complexity, making it difficult to ensure accurate allocation.

THE IMPACT:
Inconsistent cash application hindered real time financial analysis and forecasting, as receivables weren’t accurately reflected in the system.

5. Limited Scalability

  • Manual Processes Don’t Scale: As transaction volumes increases, suddenly the manual process became unsustainable, with more resources required to handle growing workloads which created even more pressure on the existing resourced or ended up in piled up work thus breaching TATs.
  • Resource Intensive: Handling increasing volumes of payments and invoices required hiring additional personnel or extending work hours, neither of which was cost effective.

THE IMPACT:
The need for additional resources made the manual process expensive and inefficient, especially for growing companies.

6. Inefficient Communication with Customers

  • Manual Email Chasing: When payment advices were missing, AR teams had to manually send follow-up emails to customers, which lead to delays and inefficiencies.
  • No Tracking or Automation: There was no automated system to track pending communications or send reminders, which resulted in frequent missed follow ups.

THE IMPACT:
The inefficiency in communication delays the payment matching process and results in longer reconciliation cycles.

7. Difficulty in Managing Complex Payment Scenarios

  • Multiple Customers with Similar Payments: When similar amounts were received from different customers, the AR team struggled to identify which payment belongs to which customer.
  • Partial Payments or Overpayments: Handling partial or overpayments manually was complicated and increased the likelihood of errors during allocation.

THE IMPACT:
These complex scenarios resulted in frequent mistakes that required later corrections, slowing down the reconciliation process and requiring manual intervention.

8. No Centralized Visibility or Tracking

  • Lack of Real Time Reporting: Manual processes didn’t offer real time insight into the status of payments, matched invoices, or outstanding balances.
  • Difficulty in Identifying Issues: Identifying and addressing discrepancies, unmatched payments, or errors required a time-consuming manual review and additional resources.

THE IMPACT:
Without centralized visibility, it was hard for AR teams to monitor performance and identify areas for improvement, leading to inefficient operations.

The solution to these challenges lies in mitigation through automation, here’s how those tools can help in matching payments:

1. Automating Data Collection and Integration

  • Automated Bank Statement Import: Use APIs or file imports to automatically fetch bank statements directly into the AR system, eliminating manual collection.
  • Automated Payment Advice Extraction: Employ (OCR)/ML to extract data from payment advice in various formats (PDFs, emails, scanned documents) and integrate it directly into the AR system.

Mitigation: Reduces the time spent manually retrieving and entering data, allowing AR teams to focus on higher value tasks.

2. Reducing Errors with AI Powered Matching

  • AI Based Payment Matching: Implement AI algorithms to intelligently match payments to invoices based on historical patterns, amounts, and customer profiles. Even when exact matches aren’t found, the system suggests the most likely invoices.
  • Automated Validations: Use automated checks and validations to prevent common human errors in data entry and invoice matching.

Mitigation: Automating the matching process minimizes human error and ensures accurate financial records, reducing the need for later corrections.

3. Standardizing Processes Across Formats

  • Unified Data Processing: Standardize and normalize data from various sources (bank statements, payment advice, emails) into a single format using automation tools. Use AI to recognize unstructured formats and standardize them for processing.
  • Centralized Repository: Store all payment advice, bank statements, and correspondence in a centralized system accessible to AR teams for easy reference.

Mitigation: Standardization reduces complexity and ensures consistent data processing, making the overall payment matching process more streamlined and efficient.

4. Automating Invoice Posting and Reallocation

  • ERP Integration for Real Time Posting: Automatically post matched payments to invoices in the ERP system, updating the customer’s account balance in real time.
  • Automated Reallocation Workflows: When an incorrect allocation is identified, implement an automated workflow to reverse the incorrect posting and correctly reallocate the payment.

Mitigation: Automating posting and reallocation ensure that the financial system remains UpToDate and accurate, with minimal manual intervention needed.

5. Scalable Automation for Growing Volumes

  • Automated Cash Application for Higher Volumes: Automating the entire payment matching process allows the system to handle increasing transaction volumes without needing additional personnel.
  • Cloud Based Scalability: Implement cloud-based AR automation solutions that can scale as transaction volumes grow, avoiding the limitations of manual processing.

Mitigation: Automation allows the AR process to scale effortlessly as business grows, without requiring proportional increases in staff.

6. Automated Communication and follow-ups

  • Automated Email Triggers: Automatically send emails to customers when payment advice is missing, asking for clarification on how payments should be allocated. The system can also follow up if no response is received within a predefined time.
  • Built in Communication Tracking: Track customer responses and ensure timely follow-ups with automated reminders, keeping the process moving without manual oversight.

Mitigation: Automation of communication reduces the time spent chasing customers for payment details and ensures consistent follow-ups, accelerating the matching process.

7. Simplified Handling of Complex Payment Scenarios

  • Smart Matching Algorithms: Use AI driven matching to handle complex scenarios such as partial payments, overpayments, or similar amounts from different customers. The system can automatically suggest the best invoice match or flag exceptions for review.
  • Automated Partial Allocations: Automatically allocate partial payments across multiple invoices, ensuring the remaining balance is tracked and recorded correctly.

Mitigation: Automating these complex scenarios ensures accurate and efficient allocations, reducing the need for later manual corrections.

8. Centralized Real Time Visibility and Reporting

  • Realtime Dashboards: Implement dashboards that provide real time visibility into the status of payments, outstanding balances, and matched/unmatched invoices.
  • Exception Reporting: Automatically generate reports that flag unmatched payments, incorrect allocations, or other exceptions, allowing AR teams to focus on resolving them quickly.

Mitigation: Realtime visibility and exception reporting allow AR teams to monitor performance, identify bottlenecks, and resolve issues before they cause delays.

ORGANISATIONAL BENEFITS OF AUTOMATING THE AR PROCESS

  • Reduced Manual Effort: Automation eliminates repetitive, manual tasks, freeing AR teams to focus on value added activities such as strategic analysis and customer relationship management.
  • Faster Cash Application: Automated matching and posting speeds up cash application, improving cash flow visibility and reducing DSO (Days Sales Outstanding).
  • Increased Accuracy: Automated processes reduce human error, ensuring accurate invoice matching and financial reporting.
  • Scalability: Automation can handle growing transaction volumes without needing additional resources, making the process cost effective as the business grows.
  • Improved Customer Experience: Automated follow-ups and faster payment matching result in fewer customer disputes and quicker resolution times, improving the overall customer experience.
  • Compliance and Audit Trails: Automated processes provide detailed audit trails, improving compliance with financial regulations and simplifying audits.

Now, returning to the purpose of this blog – how AR Automation can be the mantra to happiness for AR Teams:

  • Automating the Accounts Receivable process reduces repetitive, tedious tasks, allowing employees to focus on more meaningful work, which increases job satisfaction.
  • It minimizes errors, reducing the frustration of correcting mistakes and ensuring accuracy from the start.
  • Automation speeds up processes, improving time management and lowering stress by eliminating bottlenecks.
  • With automated follow-ups and real-time insights, AR teams experience better communication, fewer disputes, and quicker issue resolution.
  • The scalability of automation prevents burnout by handling higher transaction volumes efficiently, while providing opportunities to the team for strategic thinking as well as room for learning and professional growth, fostering motivation and happiness!

So, choose the road to happiness, and call us for a demo – sandeep@inebura.com

Author

Sudarshan Banerjee
Sudarshan Banerjee
Inebura , Head of Product & GTM

Sudarshan Banerjee is a Product, Process and Automation professional. His areas of interest include Sales Force Automation Tools, Sales Process Construction, Data Science, Data Analytics, Statutory Audit and Compliance, Project Management and Change Management.

He has over 19+ years of experience in Business Development, Sales, Process Planning, Business Strategy and Product Development spanning across various domains namely ITeS, FMCG,Financial Services, Travel& E-com.

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