Role-Based Programme
RB1406

AI-Powered Accounts Receivable

Smarter Billing, Receivables Analysis & Cash Collection Management

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Accounts Receivable activities including billing, receivables monitoring, cash application, reconciliations, customer follow-up, and reporting.
  • Use AI-assisted techniques to analyse invoices, customer balances, payment records, ageing data, deductions, disputes, and collection activity more efficiently.
  • Develop structured workflows for invoice review, payment matching, account reconciliation, overdue follow-up, dispute handling, and period-end reporting.
  • Improve receivables visibility through AI-assisted ageing analysis, exception identification, cash collection insights, and management reporting.
  • Apply responsible AI practices covering customer confidentiality, financial-data accuracy, payment information, communication quality, access control, and human approval.

Tools covered

Generative AI AssistantsAccounts Receivable AnalyticsInvoice & Billing AnalysisAgeing AnalysisCash Application SupportReconciliation SupportCustomer CommunicationSpreadsheet AnalysisReceivables ReportingWorkflow Automation

Who should attend

  • Accounts Receivable Managers
  • Accounts Receivable Executives
  • Accounts Receivable Analysts
  • Receivables Accountants
  • Billing Professionals
  • Cash Application Professionals
  • Collections Professionals
  • Order-to-Cash Professionals
  • Finance Operations Professionals
  • Credit Controllers
  • Customer Finance Professionals
  • Financial Accountants
  • Finance Managers
  • Finance & Accounting Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of Accounts Receivable, finance operations, billing, collections, or accounting
  • Familiarity with invoices, customer accounts, payments, ageing reports, reconciliations, or disputes is helpful
  • Basic spreadsheet and numerical-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, document intelligence, and automation in Accounts Receivable
  • Identifying AI applications across billing, cash application, collections, reconciliation, and reporting
  • Understanding AI assistance versus authorised Finance and Accounts Receivable decision-making
  • Recognising risks related to incorrect balances, confidential customer information, and unsupported conclusions
Practical activities
  • Mapping the Accounts Receivable lifecycle to AI-assisted opportunities
  • Identifying repetitive AR activities suitable for AI support
  • Comparing traditional and AI-assisted receivables workflows

Scenarios

Customer Invoice to Cash Application & Reconciliation

Customer Invoice → Payment Receipt → AI-Assisted Matching → Exception Review → Cash Application → Account Reconciliation → Customer Update → Closure

Participants process a simulated customer account from invoicing through payment application, identify matching exceptions, reconcile the account, and prepare clear follow-up documentation.

Receivables Data to Cash Collection Improvement Plan

Ageing Data + Customer Balances + Payment History + Disputes + Unapplied Cash → AI Analysis → Collection Bottlenecks → Priority Accounts → Process Improvements → Management Report

Participants consolidate Accounts Receivable data, identify recurring billing, collection, and payment-application issues, and prepare a management-ready improvement plan with actions, owners, and priorities.

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