If your enterprise is still relying on manual, legacy processes for managing accounts receivable (AR), it may be time to join the automation revolution. Modern technologies have made it possible to completely transform critical AR processes using automation.
In this comprehensive guide, we will explore the top 4 accounts receivable processes that forward-thinking enterprises should prioritize automating in 2023:
- Calculating and Monitoring DSO
- Checking Customer Credit
- Keeping Track of Customer Data
- Collecting Payments
Automating these crucial AR processes promises significant benefits from operational efficiency to cash flow optimization. Let‘s examine each one in detail.
Why Automate Accounts Receivable Processes?
Before we dive into the specifics, it‘s important to understand the pressing need for AR automation. Despite technological disruptions in nearly every other business function, AR processes at many organizations are still performed manually.
This is astonishing considering the transactions-heavy and time-sensitive nature of AR. Just looking at the numbers proves the urgent need for automation:
- 78% of AR professionals spend more than 20% of their time on manual duties that can be automated. (Source: Ardent Partners)
- 9/10 enterprises experience payment delays resulting in deficits in cash flow. Lack of AR automation is a top contributing factor. (Source: Bill.com)
- 60% of businesses report frequent customer queries and complaints due to inefficient AR processes. (Source: Oracle)
- AR costs can range from $5 to $12 per invoice for manual processing – an average of $8. (Source: TouchlessProcessing.com)
Clearly, manual AR processes are draining productivity, increasing costs, delaying payments and negatively impacting customer satisfaction.
Switching to automated AR solutions powered by technologies like artificial intelligence, machine learning and predictive analytics promises immense benefits:
1. Increased efficiency – Automation handles high-volume, repetitive AR tasks without human intervention
2. Lower operating costs – Reduces cost-per-invoice by 80% or more
3. High accuracy – Minimizes costly errors inherent in manual processes
4. Enhanced visibility – Provides real-time AR analytics and forecasting
5. Quicker payments – Accelerates invoice processing and collections
6. Scalability – Cloud-based solutions support business growth without proportional rise in AR costs
7. Improved customer satisfaction – Faster responses and no more payment delays
Given these compelling benefits, AR automation should be a top priority for enterprises in 2023. Now let‘s explore the top 4 processes ripe for automation.
1. Calculating and Monitoring DSO
DSO or Days Sales Outstanding is a crucial AR metric that measures the average number of days it takes to receive payment from customers after a sale occurs.
A high DSO indicates inefficient AR processes, while a low DSO signifies effective credit and collection policies. Tracking DSO allows businesses to monitor the payment patterns of customers and take corrective actions if needed.
However, manually calculating DSO can be extremely challenging. Here are some of the top limitations:
- Data accuracy – Collecting sales and payment data from multiple systems prone to human errors
- Time lag – Manual calculation cannot provide real-time DSO changes
- Inconsistent tracking – Methods may vary across locations or business units
- Limited insights – Hard to identify root causes behind DSO fluctuations
This makes it almost impossible to get an accurate and up-to-date view of DSO.
Automating DSO monitoring overcomes these challenges. Integrated AR management solutions can seamlessly pull sales and receivables data from source systems like billing, ERPs, CRM, accounting software etc.
Advanced analytics provide complete visibility into DSO fluctuations – both historical trends and real-time changes. Issues like payment delays or revenue recognition problems can be quickly identified.
For example, construction software provider HCSS automated its DSO tracking using HighRadius. This reduced DSO by 3.5 days resulting in the freeing up of $3 million in working capital.
By leveraging automation to transform DSO monitoring, enterprises can optimize cash flow, reduce bad debt expenses and improve forecasting.
2. Checking Customer Credit
Extending credit to customers involves financial risk. The best way to minimize bad debt is by thoroughly evaluating a customer‘s creditworthiness before approving credit terms or limits.
However, manual verification of credit information is incredibly tedious, inconsistent and prone to errors. Employees spend hours digging through paperwork and making phone calls to collect credit data on each customer.
Critical factors that indicate credit risk – like bankruptcy history or payment delays with other suppliers – can also be overlooked without systematic checks.
Automating the credit check process minimizes these issues through:
Comprehensive data collection – Automated solutions can seamlessly pull credit data from various sources like credit bureaus, public records, bank references etc. This provides complete visibility into creditworthiness.
Instant risk assessment – Sophisticated algorithms instantly analyze the compiled data to accurately evaluate credit risk.
Real-time monitoring – Any changes in customer credit profiles are immediately flagged to take appropriate actions.
Consistent decisions – Preconfigured credit policies standardize the approval process across the organization.
For instance, the accounts receivable team at Owens Corning automated credit checking and risk analysis by implementing HighRadius Software‘s integrated platform. This decreased time spent on manual credit verification by 90% allowing them to process twice the number of orders.
Credit decisions also became data-driven rather than intuition-based, minimizing potential losses. Automating credit checks is critical for prudent credit management and reduced bad debt.
3. Keeping Track of Customer Data
Maintaining comprehensive and updated customer data including contact information, outstanding invoices, payments, credit history, and account status is vital for efficient AR management.
Without a centralized repository of customer data, AR teams struggle to respond to customer inquiries or follow up on delinquent accounts. This results in payment delays, negative customer experiences and revenue leakage.
Manually compiling customer data from disparate systems like billing, accounting, CRM and collating it into reports is extremely cumbersome. Data often becomes outdated by the time reports are circulated leading to misinformed decisions.
AR automation solutions overcome these challenges by providing a single source of truth for customer data. Sophisticated integrations extract information from multiple systems into a centralized data lake in real time.
Advanced analytics generate actionable insights – like rising DSO for a particular customer – that can be instantly acted upon. Features like intelligent robotic process automation also automate mundane administrative tasks like report generation.
Global bank HSBC automated its customer data management using HighRadius. Centralized visibility of AR data improved collection efficiency by over 25% and reduced operating costs.
Withquality data readily available, enterprises can offer more personalized service, expedite issue resolution and make strategic decisions faster.
4. Collecting Payments
The end goal of efficient AR processes is accelerating the collection of payments from customers. Delayed payments directly impact short-term cash flows and long-term profitability.
Yet collection of receivables remains largely manual and reactive at most enterprises. AR teams send out payment reminders just days before due date and follow-up on delinquent accounts through basic techniques like emails or calls.
Valuable time and effort is spent on avoidable dunning and chasing customers for payments. Moreover, there is no centralized system for handling customer disputes and exceptions.
AR automation introduces structure, consistency and automation into the collections process through:
- Intelligent collections – Custom rules trigger automated payment reminders and follow-ups based on customer profiles. For example, customers with history of delayed payments can receive reminders 10-15 days before due date.
- Multi-channel outreach – Messages are delivered through preferred mediums like text, email, portals reducing need for manual calls.
- Prompt response – Automated rapid matching of invoices, payments and remittances speeds up dispute resolution.
- Self-service options – Customer portals allow access to statements and on-demand payments 24/7.
- Seamless experience – Tight integration between order, billing, payment and accounting systems.
Cisco Systems deployed automation to enhance collections using HighRadius, reducing past-due receivables by 54%. Both productivity and customer satisfaction improved significantly.
Boosting collection efficiency through automation has a direct positive impact on revenue and cash flow cycles.
Common Techniques for Accounts Receivable Automation
Now that we‘ve explored the top processes to automate, let‘s look at some of the technologies enabling AR automation:
Robotic Process Automation – Software bots that mimic human actions for automating repetitive, rules-based tasks. For example, RPA can help with data entry or report generation.
Artificial Intelligence – Enables software to sense, interpret, learn and act based on data patterns. AI powers intelligent capabilities like predictive analytics.
Machine Learning – Allows systems to learn from data without explicit programming and improve automated decision-making.
Natural Language Processing – Processing and analyzing text data like customer communications to automate responses.
OCR/ICR – Optical and intelligent character recognition extracts data from paper or electronic documents like invoices.
APIs – Application programming interfaces connect AR systems with other platforms like accounting, ERPs, payment gateways etc.
By combining these technologies, modern AR automation solutions can replicate almost every manual process – from credit checks to payment posting – digitally. This evolves AR management from an intuition-driven function to an insights-led strategic capability.
Success Stories: How Enterprises Automated Accounts Receivable
Many global enterprises have already embarked on the automation journey and are reaping the benefits:
- Unilever – The consumer goods giant automated AR with Esker, reducing DSO by 3 days and improving productivity by 20%.
- Emerson Electric – By partnering with VersaPay, Emerson sped up AR processing by 50%, while cutting costs by 75%.
- Murphy USA – The oil & gas company streamlined AR with Salesforce, doubling productivity and ensuring 99.7% invoice accuracy.
- Lowe‘s – The home improvement retail giant worked with HighRadius to reduce past-due AR by 20% through automation.
These examples demonstrate how enterprises both big and small across industries are automating AR processes to gain quantifiable results – from DSO reduction to ROI improvements.
Hypatos – AI-Powered Accounts Receivable Automation
While several vendors offer AR automation capabilities, one solution stands out for its easy integration, scalability and artificial intelligence – Hypatos.
Hypatos provides an end-to-end platform for automating accounts receivable processes by combining robotic process automation (RPA), natural language processing (NLP) and proprietary AI capabilities:
Image source: Hypatos.ai
Here are some of the key features that enable comprehensive AR automation:
Documents Processing with AI
Hypatos leverages advanced OCR, NLP and machine learning algorithms to instantly classify, extract and interpret data from both paper and electronic documents including:
- Sales orders
- Payment advises
This data can be automatically matched and reconciled without any manual processing.
Integrations & Workflows
Pre-built connectors allow integrating Hypatos with surrounding systems involved in AR processes like:
- Accounting software
- ERP platforms
- Contract databases
- Communication systems
End-to-end workflows can be configured through easy drag-and-drop to automate multi-step processes across these systems.
Continual Machine Learning
Hypatos utilizes a proprietary approach to machine learning called Continual Learning. Models continue learning actively in production through human-in-the-loop training.
This means the platform keeps getting smarter automatically without needing retraining of models. Accuracy of document processing and workflows improves consistently over time.
Hypatos is offered as a scalable cloud-native solution. This enables easy integration with on-premise and cloud systems through APIs. Usage-based pricing allows starting small and expanding automation as needed.
While supporting general accounting process automation, Hypatos offers pre-built capabilities tailored for accounts receivable management including:
- DSO forecasting
- Automated credit checking
- Intelligent collections
- Cash application
- Dispute and query resolution
- AR analytics and reporting
With minimal configuration, enterprises can achieve true lift-and-shift automation of manual AR processes using Hypatos. This delivers significant productivity improvements, cost savings and faster payment cycles.
The Future is Automated
The era of manual, reactive accounting processes is ending. Leading enterprises are embracing automation to completely transform time-consuming and inefficient accounts receivable management.
Intelligent solutions deliver accurate real-time AR analytics, consistent credit decisions, effortless customer tracking and accelerated collections. This leads to reduced costs, predictable cash flow and leaner AR teams.
As the examples in this guide demonstrate, automating the top accounts receivable processes provides immense competitive advantage. The technologies enabling AR automation like AI and ML are easily accessible today through cloud solutions.
Forward-thinking finance leaders should urgently prioritize AR automation to boost productivity, minimize risk, improve customer experiences and add strategic value. The future success of enterprises clearly lies in automated AR processes.