Remittances play a crucial role in the global economy regarding the flow of capital between businesses and individuals. Remittance advice is a proof of payment letter a customer sends to a supplier that verifies they have paid their invoice. Remittance advice notifies the recipient of a payment, including the details. Paper remittances include a detailed check stub, perforated invoice, or billing account statement section that is detached and mailed with the payment indicating the amount paid.
The process for accounts payable remittances typically involves receiving invoices, verifying their accuracy, obtaining necessary approvals, and initiating payments through various methods such as e-transfers, wire transfers, or checks.
For accounts receivable remittances, finance teams focus on invoicing customers, tracking incoming payments, reconciling accounts, and following up on overdue payments. The key difference between AP and AR remittances lies in their direction and purpose. AP remittances are outgoing payments that reduce a company’s liabilities, while AR remittances are incoming payments that increase its assets.
Currently, AP and AR remittances are a manual, time-consuming activity for many finance teams. Integrating automation into these teams’ workflows will allow accounting professionals to focus on value-added tasks and increase the efficiency of their companies’ cash flows. Professionals must carefully manage both types of remittances to maintain a healthy balance sheet and ensure optimal cash flow.
Remittance processing presents numerous challenges for finance professionals, including time-consuming data entry, complex reconciliation tasks, and the potential for errors. Artificial Intelligence is revolutionizing the way accounts payable and accounts receivable teams handle remittances, offering significant improvements in efficiency, accuracy, overall financial performance, and cost reduction.
Accounts payable and accounts receivable teams are increasingly adopting digital solutions to streamline remittance processing. As artificial intelligence and machine learning algorithms continue to evolve through ongoing learning and the expansion of big data, their applications in the payments sector are set to multiply.
The accounts receivable and accounts payable automation market is expected to grow 17.65% to reach $7.8 BN in 2029
According to Androit Market Research, the accounts receivable and accounts payable automation market is expected to grow at a CAGR of 17.65% to reach US$7.8 billion in 2029.
Standardizing remittance information and automating data extraction and matching processes have become crucial for efficiency. Companies embracing digitization are already seeing internal improvements from investments in technology, as OCR and computer vision technology are becoming more widely used to extract data from scanned documents, while cloud-based platforms are providing centralized access to remittance data.
AI will increasingly streamline back-end operations such as processing, reconciliation, and settlements and has become crucial for payment firms to meet evolving business needs.
API integrations enable seamless data exchange between different systems, and automated matching algorithms employing rules-based systems efficiently match remittances with invoices or payments.
In 2022 Citibank reported more than an 82% increase in virtual account balance growth, due to a 33% virtual account management platform adoption. Beyond enhancing risk management and customer service, AI will increasingly streamline back-end operations such as processing, reconciliation, and settlements. With transaction volumes surging and security risks escalating, AI has become crucial for payment firms to address these challenges and meet evolving business and consumer needs.
Even though companies are increasing the use of technology in their cash flow process, there is still a great need for finance professionals to automate and streamline accounting processes.
According to Capgemini’s World Payments Report of 2023, more than 50% of corporate treasurers across multiple industries said that the rise in globalization and recent supply chain disruptions demand effective treasury management services, over 70% of corporate treasurers surveyed faced issues with collection and reconciliation processes, and more than 70% said subpar treasury management services result in higher operating costs, delayed cash pooling and high debt levels.
45% of CFO’s said invoicing errors and discrepancies caused payment disruptions.
By automating repetitive and time-consuming tasks, AI enables finance teams to focus on more strategic activities. According to PYMNTS “Working Capital Tracker® Series Report of 2023,” 45% of CFO’s said invoicing errors and discrepancies caused payment disruptions. The manual aspects of remittance processing hinder the ability to generate timely and accurate financial reports. Professionals spend hours reconciling discrepancies and ensuring payments are correctly recorded before reliable financial statements are produced. The integration of AI into the payment process will eliminate human error while increasing processing speed.
Accounts payable automation significantly reduces the time required for invoice receipt and data capture, on average saving up to 80% of the time required for manual processes.
In traditional accounts payable, data entry, invoice routing, and matching invoices with purchase orders are tasks that require extensive manual attention. Injecting AI will shorten the procure-to-pay cycle and minimize human intervention.
According to a study by BlueCreek Software accounts payable automation significantly reduces the time required for invoice receipt and data capture, on average saving up to 80% of the time required for manual processes.
Artificial intelligence facilitates intuitive financial processes by learning an organization’s invoice processing rules and applying them consistently. The integration of AI in AP processes not only reduces processing times but also improves vendor relations.
For payments both domestically and internationally, AI automatically captures and digitizes remittance advice, matches remittances with open invoices, and identifies unapplied payments, which streamlines the entire remittance capture process.
Moreover, AI-powered solutions enhance supplier onboarding and assessment by automating data entry and scoring vendors based on historical data, providing valuable insights into vendor performance and enabling better spend management.
Current AI for payments is linked to businesses’ ERP system’s general ledger transaction data, historical bank statements, and financial planning and analysis data to provide highly accurate cash flow forecasts. These types of AI solutions are built on multiple machine learning algorithms that continuously study and provide insights on possible AR and treasury scenarios. These predictive applications demonstrate how AI could significantly enhance the efficiency and effectiveness of financial operations, making it an indispensable tool for modern finance teams.
Automation saved a healthcare provider’s AR team 4.5 hours of daily work, reducing time spent on cash applications by 75%.
Automated workflows route payment requests through the necessary approval processes, facilitate payment reconciliation and support reporting efforts. This type of workflow automation not only increases efficiency but also reduces the likelihood of human error in the payment process. AI-enabled technology automates the extraction and classification of remittance data from various sources, such as emails and PDFs, significantly reducing manual data entry errors and speeding up the reconciliation process.
According to one vendor, the efficiency of payment processing for a healthcare provider was significantly improved once the software workflows were applied. Automation saved the healthcare provider’s AR team 4.5 hours of daily work, reducing time spent on cash applications by 75%. Now, the company has nearly 95% of its incoming payments automated. This application of AI allowed the healthcare provider to reduce errors, post payments quicker, and work with customers easily.
Invoice fraud and related billing schemes pose a significant threat to businesses, capable of quickly eroding profits and creating disruptions. To combat these fraudulent activities, detection tools powered by AI offer a substantial advantage in verifying the authenticity of incoming invoices. These tools identify duplicate, fake, and outright fraudulent payment requests that might have previously gone unnoticed by human-led teams.
AI detection software identifies duplicate, fake, and outright fraudulent payment requests that might have previously gone unnoticed by human-led teams.
Moreover, these detection efforts extend beyond individual invoices to detect recurring or novel patterns of unusual buying or spending behaviors. Given the machine learning capabilities provided by these platforms, taking AI-led anti-fraud measures effectively gives businesses a robust defense against financial fraud.
Remittance automation is poised to revolutionize accounts payable and accounts receivable teams by transforming remittance processes, minimizing manual errors, substantially boosting efficiency, and reducing costs. The integration of AI-powered solutions will automate critical tasks such as data extraction, invoice matching, and payment reconciliation, freeing finance professionals from manual time-consuming tasks and allowing them to concentrate on strategic initiatives and value-added activities.
As a result, businesses will be better equipped to make informed decisions, optimize working capital, and maintain a competitive edge in an increasingly digital marketplace.
AI-powered solutions transform businesses, equipping them to make informed decisions, optimize working capital, and maintain a competitive edge in an increasingly digital marketplace.
Looking ahead, the future of remittances is set to be defined by increased digitization and even further integration of advanced technologies. There is an anticipated surge in the adoption of AI and machine learning for predictive analytics and automated decision-making in remittance processing, as well as the emergence of enhanced cross-border payment solutions to ensure secure international transactions.
As these trends unfold, AP and AR teams will need to adapt to new technologies and processes to remain competitive and efficient in managing remittances, ultimately benefiting from the greater speed, accuracy, and transparency in financial transactions they will provide.