₹80 LPA Offer Includes ₹40 Lakh ‘Kidnapping Insurance’

A recent placement anecdote from the Indian Institute of Management Calcutta has gone viral, reigniting conversations around the gap between advertised salary packages and actual take-home pay. The story, shared by podcaster Kushal Lodha during a discussion with Aman Dhattarwal, revealed how a company offered an ₹80 lakh per annum package, but with a surprising breakdown.

According to Lodha, only ₹40 lakh of the offer was fixed salary, while the remaining ₹40 lakh was allocated as “kidnapping insurance.” The company, reportedly operating in certain high-risk geographies, structured this component as a contingency to cover ransom in case of employee abduction.

While the rationale may be linked to safety concerns in specific regions, the structure has sparked widespread debate on the transparency of compensation packages. Critics argue that including such conditional or unlikely-to-be-used benefits in Cost to Company (CTC) inflates headline figures and creates a misleading perception for candidates.

The viral clip has triggered strong reactions on social media, ranging from humour to serious criticism. Some users joked about the unusual perk, while others questioned the ethics of presenting such components as part of total compensation. The discussion has also brought renewed attention to how companies design salary structures, especially during campus placements where headline numbers often influence candidate decisions.

The incident underscores a broader trend in hiring practices, where companies package compensation in ways that may not fully reflect actual earnings. As competition for top talent intensifies, transparency in salary communication is increasingly becoming a critical factor in building trust with candidates.

Although the identity of the company involved has not been officially confirmed, the episode serves as a reminder for job seekers to carefully evaluate offer structures beyond the headline CTC figure, paying close attention to fixed pay, variable components, and conditional benefits before making career decisions.