A financial services firm uses SAP Business AI to predict cash flow and optimize account reconciliation processes. What actions should the firm take to maximize SAP Business AI capabilities? There…

Question

Options

• AUse predictive analytics for cash flow projections
• BAutomate reconciliation workflows
• CDeploy AI-based fraud detection models
• DIntegrate results with SAP Analytics Cloud
• EDevelop custom models for risk assessment

• A
  73% (30)
• C
  17% (7)
• E
  10% (4)

Explanation

A, B, and D are correct because they align directly with SAP Business AI's built-in capabilities within the SAP ecosystem: predictive analytics for cash flow projections (A) is a core SAP Business AI feature in financial planning, automating reconciliation workflows (B) directly addresses the scenario's stated goal of optimizing account reconciliation, and integrating with SAP Analytics Cloud (D) is the natural extension point for surfacing AI-generated insights - these three work together as a cohesive, native SAP solution.

C (AI-based fraud detection) is a distractor because while fraud detection is a valid AI use case, it is not scoped to the cash flow and reconciliation focus stated in the question - it solves a different problem domain.

E (custom models for risk assessment) is wrong because SAP Business AI promotes using its pre-built, embedded AI rather than developing custom models from scratch; custom model development also falls outside the scope of the firm's stated objectives (cash flow prediction and reconciliation).

Memory tip: Think of the acronym PAI - Predict (A), Automate (B), Integrate (D). These three verbs represent the standard SAP Business AI adoption pattern: predict with built-in models, automate workflows, then integrate outputs into SAP Analytics Cloud for visibility.

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