Senior Executive

Role Overview

Financial Spreading Analyst

automated financial statement spreading systems

Key Responsibilities

• Automated Spread Review: Validate and reconcile financial data extracted by automated spreading systems (e.g., Moody’s Risk Analyst, CreditLens or equivalent) against source financial statements.
• Ratio Analysis: Calculate and interpret key financial ratios, trends, and performance indicators to highlight strengths, weaknesses, and potential risks.
• Exception Handling: Identify and correct system misclassifications, OCR errors, and misaligned mappings; escalate recurring issues to technical teams for model retraining.
• Complex Data Interpretation: Apply judgment in handling unstructured or jurisdiction-specific financial formats, adjusting for reclassifications, non-recurring items, and sector-specific reporting nuances.
• Quality Control: Perform periodic audits of system-generated spreads to ensure compliance with internal credit policies, IFRS/GAAP standards, and regulatory requirements.
• Stakeholder Collaboration: Liaise with credit analysts, relationship managers, and system administrators to ensure timely and accurate delivery of spread data for credit decisions.
• Process & System Improvement: Provide feedback to automation teams on template refinements, data mapping logic, and AI model performance; contribute to user acceptance testing (UAT) for system upgrades.
• Training & Knowledge Sharing: Support team members in understanding automated spread outputs, exception patterns, and best practices for validation.
  

Qualifications & Skills

• Bachelor’s degree in Finance, Accounting, Commerce or related field; CA, CPA, CFA preferred.
• 3+ years of financial spreading experience in a banking or credit rating environment, with at least 2 years working on automated spreading platforms (e.g., Moody’s Risk Analyst, CreditLens or similar) .
• Strong grasp of IFRS, GAAP, industry-specific accounting nuances and cross-border accounting variations.
• Hands-on experience with OCR-based data capture, AI/ML-powered financial extraction tools, and exception handling workflows.
• Advanced Excel and data validation skills; comfort with structured/unstructured data.
• High attention to detail, with ability to work to tight SLAs.
• Effective communication skills for both business and technical audiences.