How to Benchmark Technology Compensation in Financial Services, Properly

Mover data versus incumbent data

Surveys mostly measure incumbents, people sitting in seats. Search data measures movers, people changing organisations, who price 20 to 40 percent above incumbents depending on function scarcity. Neither number is wrong; they answer different questions. Use incumbent data to check internal equity, and mover data to set offers and to understand what retention is actually competing against. Confusing the two is the single most common benchmarking error we correct for clients.

Where surveys mislead

Three recurring gaps. Survey lag: bands published annually describe a market that has since moved, which in tight functions means materially. Segment blending: averaging banks, NBFCs, fintechs and GCCs into one number hides the premiums that decide real offers. And the counteroffer blind spot: no survey captures what institutions pay to keep people at resignation, which in the tightest functions is now the true top of market.

Our function-level benchmarks

Two related pages sit outside the function set:

• GCC compensation, financial services
• The wider India technology market, 2026 (compensation pillar, on a CTC basis)

When to commission benchmarking instead

Public ranges answer "roughly what does this cost." They do not answer "what will it take to hire a specific profile into this specific seat this quarter," which depends on scope, reporting line and the current state of two dozen competing teams. That question is a talent intelligence engagement, and for a single role it is usually a fast one.