Tactics To Streamline Your Accounts Receivable Process in 2024

The accounts receivable (AR) process is a crucial cog in the financial operations of any business. An efficient AR process ensures timely collection of payments from customers, improved cash flow, and better relationships with customers. However, many businesses still struggle with manual and disjointed AR workflows, leading to disputes, write-offs, and revenue leakage.

With the pace of technological disruption, 2024 will usher in newer techniques and solutions to optimize the AR process. Businesses that can streamline their AR operations will gain a competitive edge with lower DSO, reduced costs, and improved working capital.

Here are some practical tactics that forward-thinking businesses can adopt to streamline their accounts receivable process in 2024.

1) Leverage Artificial Intelligence and Machine Learning
AI and ML have made substantial inroads into streamlining repetitive, rules-based processes like accounts receivable. Smart software solutions can automate tedious tasks like data capture, classification, reconciliations, and reporting.

By 2024, machine learning algorithms will be mature enough to enable the following AR capabilities:

  • Auto-reconciliation of invoices, payments, and account balances.
  • Instantaneous matching of invoices and remittances.
  • Accurate predictive coding of invoices based on historical patterns.
  • Anomaly detection in payment cycles and invoice flows.
  • Intelligent querying of invoices and customers for disputes and collections.

Adopting AI-enabled AR solutions will drive up to 80% improvement in efficiency and a 50% reduction in DSO.

2) Integrate Accounts Receivable with ERP and CRM Systems
Lack of integration between systems is a huge bottleneck in AR processes. Key data often resides in multiple systems like ERP, CRM, e-invoicing networks, and financial systems. Moving and reconciling data across systems eats up valuable time and leaves room for errors.

In 2024, the autonomous flow of information between disparate systems will become the norm. APIs and cloud integrations will enable real-time syncing of customer data, invoices, payments, and remittance details across platforms. This will pave the way for touchless, seamless AR workflows.

Integrated AR will deliver a multidimensional customer view to credit, sales, and support teams. This will foster superior customer experiences and fewer disputes arising from data mismatches.

3) Migrate to Touchless Payment Processing
Payment processing bottlenecks like data entry, payment matching, and cash application eat up a big chunk of the AR cycle. Manual payment processing can take up to 3-4 days of an 8-10 days DSO cycle.

Modernizing payment processing with digital and automated solutions will greatly boost AR efficiency. Some touchless techniques that will mature by 2024 include:

  • API-based electronic payments Customer payment details seamlessly flow into the AR system via payment gateways.
  • OCR and AI-enabled auto-cash application Remittances are scanned, extracted, and reconciled without human involvement.
  • Smart virtual assistants Chatbots and virtual agents use NLP to respond quickly to payment inquiries.
  • Digital wallets and payment gateways Platforms like PayPal, Stripe, and Apple Pay simplify direct-to-bank account payments.

Migrating 80-90% of transactions to touchless payment processing can collapse payment cycle times by over 50% and lower payment processing costs.

4) Automate Collections and Deductions Management
Collections and deductions resolution are crucial blocking points in AR workflows. The collections process will benefit tremendously from process automation and AI capabilities by 2024.

Intelligent collections software will be able to:

  • Continuously evaluate individual customer payment behavior using techniques like clustering and regression.
  • Predict potential payment delays and defaults early in the collections cycle.
  • Initiate context-aware communications like emails, calls, and texts at the optimal time and frequency.
  • Suggest the best next action for accounts using decision trees and predictive models.
  • Provide constant collections analytics and insights to AR analysts.

Automated deductions management will also become widespread by relying on ML techniques to:

  • Identify deduction patterns and root causes.
  • Classify deductions into categories using image recognition and text analytics.
  • Match customer claims with invoices and purchase orders.
  • Generate evidence to dispute invalid deductions.
  • Initiate automated deduction resolution actions based on reason codes.

Automating 50-60% of collections and deductions activities can potentially double the bandwidth of collections staff.

5) Adopt Agile and Data-Driven Workflows
Accounts receivable have traditionally followed rigid workflows that take a linear view of processes. This makes AR workflows non-adaptive to evolving customer needs and market dynamics.

Leading enterprises will start embracing agile principles to reshape AR operations by 2024.

Some ways this can be achieved are:

  • Realigning workflows around value AR workflows will be redesigned to maximize customer value and cash velocity. Non value-adding routines will be dropped.
  • Cross-functional AR teams AR analysts, credit managers, and sales/support staff will work closely in small focused teams with clear goals.
  • Data-driven decisions Real-time AR analytics dashboards will enable teams to gain insights and make rapid decisions.
  • Continuous improvement Regular reviews, failure analysis, and workflow enhancements will help sustain improvements.

Agile workflows can enable 30% faster processing and 10% greater workforce productivity.

6) Overhaul Credit Policies with Data Analytics
Outdated credit policies based on legacy parameters will prove detrimental in 2024’s dynamic economic environment. Businesses need a data-driven approach to calibrate credit policies.

Some ways data analytics will overhaul credit risk assessment include:

  • Using predictive models – Techniques like logistic regression can identify probabilities of delinquency or default.
  • Behavior based assessment – Analyzing trends in purchase patterns and payment behavior.
  • External data integration – Building holistic customer profiles using credit bureau data, web data, and market data.
  • Scenario modeling – Simulating credit decisions for different economic scenarios using Monte Carlo techniques.
  • Optimization methods – Balancing risk and returns to establish optimal credit limits and terms.

While these techniques require investment in skills and systems, the payoff can be significant. Analytics-driven credit policies can shrink bad debts by up to 30% while improving approvals.

Moving Forward

Streamlining accounts receivable requires foresight, innovation, and concrete execution. As we move closer to 2024, purposeful investments need to be channelled towards automation, analytics, integration, and digitization initiatives. Equally important is nurturing partnerships with customers, suppliers, and technology vendors.

Businesses that transform their AR operations in 2024 will gain profitability, resilience, and competitive edge for the future. Laggards will find themselves saddled with bloated costs and drained revenues. The time for action is now.