How to use these numbers
Benchmarking technology compensation, properly
Level mapping, mover versus incumbent data, and where surveys mislead. Read this before quoting any range internally.
Read moreCompensation data in Indian financial services mostly arrives a year late and a level too vague. These pages are our attempt at the opposite: narrow, current, and honest about method. Every range is our read of the current market, cross-checked against our search work, every page states when it was last touched, and where we do not have enough data to publish, we say "in calibration" instead of guessing. Pick a function below.
How to use these numbers
Level mapping, mover versus incumbent data, and where surveys mislead. Read this before quoting any range internally.
Read moreOne page
Every verified function and level in one table, with the three differentials that decide whether an offer lands, and the method in one paragraph.
See the tableThe full reference
The pillar guide: headline numbers, pay by experience and role family, the city caveat, the expectation gap, and where financial services sits in the wider India technology market in 2026, by role, city and employer type.
Read moreEleven functions, grouped by discipline. Each card shows the three level bands on the same axis so you can compare a function against its neighbours before opening the page. Fixed pay in INR lakhs, for people changing organisations.
Updated 2 Sep 2026
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These ranges are our read of the current market for movers, people changing organisations, which typically prices above incumbent pay for the same seat. They are compiled from current public compensation data across Indian financial services and fintech (NASSCOM, LinkedIn Salary Insights, Glassdoor, AmbitionBox and published 2026 market guides) and cross-checked against our own search work. Figures are annual fixed compensation in INR lakhs. Bonus and long-term incentives vary too much across institutions to compress into a range, and we would rather show you less data than false precision. Ranges update as the market moves, not on a publishing calendar; the date at the top of each page is real. For the wider India technology market on a CTC basis, by role, city and employer type, see the wider-market sections of our compensation pillar guide.
Every range is our read of the current market for movers and is cross-checked against our live search work. Ranges update as the market moves, not on a publishing calendar, and each function page shows the date it was last touched. Where we do not have enough current data to publish a defensible range, we mark the function in calibration rather than guess.
Current public compensation data across Indian financial services and fintech (NASSCOM, LinkedIn Salary Insights, Glassdoor, AmbitionBox and published 2026 market guides), cross-checked against the offer and joining data we see running specialist search across the sector. Figures are annual fixed compensation in INR lakhs; bonus and long-term incentive vary too widely across institutions to compress into a single range. The wider India technology market, on a CTC basis by role, city and employer type, is in the wider-market sections of our compensation pillar guide.
Yes. The free pages here cover the common functions. For a specific role, comparator set and city, a custom benchmark built from live mapping is a paid talent-intelligence engagement, with scope and fee agreed up front. See compensation intelligence.
Surveys are strong on breadth but weak on recency and specificity, which is the right trade for an annual reward cycle and the wrong one for a live hiring decision. These benchmarks are the opposite: narrow, current, and specific to financial services. The full comparison is on compensation benchmark vs salary survey.
For hiring leaders
PeopleCap is a specialist recruitment partner for banks, NBFCs, fintechs and financial services GCCs in India. Calibrated shortlists in two to three weeks, success-fee, paid only on joining.