The Challenge

The organization relied on multi-layered approval workflows for high-impact business decisions, including credit exceptions, contractual deviations, and policy overrides. While formal risk policies existed, how those policies were interpreted varied widely.

Different managers assessed similar risk scenarios differently. Some approvals moved quickly, while others stalled due to repeated clarifications or escalations. Decision timelines were inconsistent, and outcomes lacked predictability.

This variability created operational friction and increased perceived risk. Business teams viewed approvals as opaque, while risk teams faced growing review loads and audit pressure.

Leadership identified that the issue was not insufficient policy coverage. It was the absence of a shared, consistently applied risk assessment structure.

Key challenges identified:

• High variance in risk interpretation across approvers

• Inconsistent approval timelines for similar cases

• Limited visibility into decision rationale

• Over-reliance on escalations to manage uncertainty

The Solution

The engagement focused on applying Intelligent Process Automation to standardize risk assessment while retaining human decision authority.

Approval workflows were first mapped to identify where judgment diverged despite common policy. Risk criteria were analyzed to distinguish between objective thresholds and subjective interpretation.

Automation was introduced to structure risk evaluation. Relevant data points, historical precedents, and policy thresholds were assembled automatically for each approval request. Risk indicators were scored consistently, providing a baseline assessment for reviewers.

Approvers retained full decision authority. The system did not approve or reject cases independently. Instead, it provided a standardized view of risk, enabling managers to make decisions with shared context and rationale.

Decision reasoning was captured in a structured format, improving traceability and audit readiness.

Core actions implemented:

• Standardized risk criteria across approval workflows

• Automated aggregation of risk-relevant context

• Consistent baseline risk scoring for approvers

• Structured capture of approval rationale

• Preservation of human oversight and accountability

Automation aligned judgment without centralizing control.

The Outcome

Approval workflows became more predictable and consistent.

Approval cycle time reduced by 39%, driven by fewer clarification loops and escalations. Decision variance across similar cases reduced by 44%, improving confidence in risk outcomes.

No policy breaches were recorded, and audit reviews showed improved traceability of decision rationale. Business teams experienced clearer expectations, while risk teams operated with reduced friction.

No changes were made to risk thresholds or governance structures. The improvement resulted from embedding consistent judgment into existing approval processes.