The traditional accounts payable (AP) process involves human agents performing manual entries of invoices, payment processing, and approvals.

However, with the rapid increase in transaction volumes, manual AP workflows begin leading to issues and inaccuracies, such as overdue, duplicate payments, human errors, inefficiencies, delays, and increased costs. This is largely due to multiple stakeholders involved in the process.

As per reports, 40% of companies cite the inability to validate invoices as a primary reason for late payments. And that’s where emerging technologies, such as AI and machine learning-powered intelligent automation come in.

In this blog, you will learn how AI-based automation can transform and streamline the accounts payable (AP) workflows, improve efficiency and accuracy, and minimize the risks due to human errors and fraudulent activities.

1. Automate Invoice Processing

Traditionally, AP departments rely heavily on manual processes to manage invoices, such as manual data entries, approvals, payment schedules, etc. Financial institutions can leverage AI and machine learning-based models that can auto-learn the invoice processing rules and apply them to new vendors.

84% of companies that have fully automated their accounts payable processes report improvements in cash flow and cost savings

For instance, it can automatically scan invoices and extract relevant data such as vendor details, line items, amounts, and due dates, and enter this scanned and extracted data into an ERP system.

It can also auto-approve invoices that are within a predefined threshold and send others for manual sign-offs, enhancing the process efficiency. This will allow teams to focus on more strategic tasks.

2. Improve Payment Processing and Cash Flow Management

AI-powered automation can help financial institutions optimize payment processing and improve cash flow management. For example, it can analyze historical payment data and predict the best timing for payments based on factors such as cash flow, vendor terms, etc.

For instance, it can also check for available discounts and recommend early payments or push-out payments when cash reserves are low. This enables financial institutions to take advantage of cost-saving opportunities while maintaining a healthy cash flow.

It can also analyze trends and forecast cash flow needs that could help financial institutions proactively plan and allocate budgets for accounts payable.

3. Reduce Errors and Enhance Compliance

Compliance and error reduction are some of the most critical concerns for any financial institution. With AI-powered automation, financial institutions can efficiently improve accuracy and meet compliance requirements by continuously analyzing and monitoring transactions for anomalies and errors, such as duplicate invoices.

Further, it can detect missing line items or incorrect amounts and flag such discrepancies before the payment is processed. It is estimated that 76% of office workers spend as much as three hours a day on data entry tasks

Similarly, AI-based automation systems can intelligently log every action in the AP process and create a detailed and searchable audit trail to enable financial institutions to track every transaction back to its source/origins. This capability helps ensure that the financial institution is always audit-ready and reduces the significant time spent on manual reconciliations and reporting for audit and compliance.

Also, for cross border payments, AI can help manage currency fluctuations and optimize timing for foreign transactions—saving on exchange costs and effective cross-border payments.

4. Strengthens Fraud Prevention

Fraud prevention is a top priority of financial institutions. With an AI-based automation system, financial institutions ensure continuous monitoring of transactions, suspicious activities, and red flags and safeguard themselves against fraudulent activities in the AP process.

AI/ML-based intelligent automation systems can also learn from historical data and newly generated data and identify a baseline of normal transaction behavior. It can also adapt to changes and detect anomalies or suspicious transactions indicative of fraudulent activity.

Some examples include unusual vendor requests or abnormally large payments.

They can generate real-time alerts when unusual activity is detected. For instance, if an invoice submitted by the vendor lies outside the usual pattern or if there are unverified changes in bank details, the AI-based automation system can automatically flag the transaction for manual scrutiny.

5. Optimize Vendor Relationship Management

Vendor relationship management can directly impact the efficiency and reliability of operations. It’s a crucial aspect where AI-powered automation systems can help by:

• Streamlining interactions with vendors
• Providing real-time insights into payment statuses
• Ensuring faster resolution to invoice disputes
• Enhancing communication

For instance, AI-based automated systems can keep vendors updated on invoice and payment statuses via automated notifications. This helps in reducing the need for back-and-forth communication.

Additionally, AI can analyze vendor performance metrics and suggest improvements in vendor agreements to maintain better relationships with vendors and negotiate more favorable terms.

Conclusion

AI-enabled automation systems and models are helping financial institutions to upgrade their accounts payable process and overcome the operational challenges as discussed in this blog. It is becoming a vital tool for financial institutions and other organizations and helping them improve efficiency, enhance accuracy, and reduce fraud.

How do you see emerging technologies, such as AI shaping the future of accounts payable workflows in financial systems? Share your thoughts in the comments!