A Study on Financial Data Analytics and Its Need in Lear Corporation Pvt. Ltd.

This study applies a structured financial data analytics framework to evaluate the financial health, structural composition, and operational efficiency of Lear Corporation Pvt. Ltd.—a globally recognised Tier-1 automotive supplier—across FY2021–FY2025. Design/Methodology: Audited standalone financial statements are examined through leverage, liquidity, profitability, asset-utilisation, common-size, CAGR-based trend, and industry benchmarking analyses, anchored in Tutar et al (2025) FSA framework, agency theory (Brandenburg & Hahn, 2021), and the pecking-order hypothesis (Lim & Luo, 2025). Findings: Net margin recovered from −4.77% to 4.19%; ROCE surged from 0.31% to 30.10%; and Interest Coverage improved from 0.12× to 11.07×. The total assets grew at an average CAGR of 12.6%, funded by internal equity accretion, which is in line with pecking-order behavior. Peer benchmarking verifies that ROCE and D/E positioning are above Tier-1 automotive industry standards. Practical Implications: The combined framework will provide practical intelligence on corporate governance, creditor risk rating, and equity value, and can be generalized to capital-intensive manufacturing firms. Originality: The study addresses a gap in firm-specific, multi-metric, longitudinal financial analytics for an Indian Tier-1 automotive supplier, combining classical ratio analysis with structural decomposition and industry benchmarking.