Role-Based Programme
RB1418

AI-Powered Credit & Collections

Smarter Credit Analysis, Receivables Management & Cash Recovery

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

Programme Objectives

  • Apply AI across Credit and Collections activities including credit review support, receivables monitoring, ageing analysis, collection follow-up, dispute tracking, and reporting.
  • Use AI-assisted techniques to analyse customer balances, payment history, overdue invoices, ageing patterns, collection activity, and supporting documents more efficiently.
  • Develop structured workflows for credit review, collections prioritisation, customer follow-up, dispute resolution, escalation, and cash-recovery tracking.
  • Improve working-capital visibility through AI-assisted trend analysis, exception identification, collection forecasting, and management reporting.
  • Apply responsible AI practices covering customer confidentiality, fair treatment, data quality, explainability, financial judgement, and human approval.

Tools covered

Generative AI AssistantsCredit Data AnalysisAccounts Receivable AnalyticsAgeing AnalysisCollections Prioritisation SupportDocument IntelligenceCustomer Communication SupportSpreadsheet AnalysisCash Collection ReportingWorkflow Automation

Who should attend

  • Credit Managers
  • Collections Managers
  • Credit Analysts
  • Collections Analysts
  • Accounts Receivable Professionals
  • Credit Controllers
  • Finance Managers
  • Finance Operations Professionals
  • Order-to-Cash Professionals
  • Receivables Managers
  • Billing & Collections Professionals
  • Working Capital Professionals
  • Financial Controllers
  • Finance & Accounting Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of credit management, collections, accounts receivable, finance, or order-to-cash processes
  • Familiarity with customer balances, invoices, ageing reports, credit limits, disputes, or collection follow-up 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, automation, and their role in Credit and Collections
  • Identifying AI applications across credit review, receivables monitoring, collections, disputes, and reporting
  • Understanding AI assistance versus authorised credit and finance decision-making
  • Recognising risks related to inaccurate data, unfair treatment, unsupported assumptions, and confidential customer information
Practical activities
  • Mapping the Credit-to-Cash lifecycle to AI-assisted opportunities
  • Identifying repetitive analysis and follow-up activities suitable for AI support
  • Comparing traditional and AI-assisted Credit and Collections workflows

Scenarios

Overdue Receivables to Collection Action Plan

Ageing Report + Customer Exposure + Payment History + Dispute Status → AI-Assisted Analysis → Priority Accounts → Collection Actions → Customer Follow-Up → Payment Commitments → Recovery Tracking

Participants analyse a simulated receivables portfolio, identify priority accounts using approved criteria, create structured collection actions, and track follow-up while keeping credit and escalation decisions with authorised finance professionals.

Credit Portfolio Data to Working Capital Improvement Plan

Customer Balances + DSO + Overdue Trends + Disputes + Collection Performance → AI Analysis → Portfolio Risks → Collection Bottlenecks → Improvement Opportunities → Management Report

Participants consolidate Credit and Collections data, identify recurring receivables and recovery issues, and prepare a management-ready working-capital improvement plan with actions, owners, and priorities.

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