Faster, Smarter Underwriting for a Multifamily Investor in Mumbai

Client profile

The client is a Mumbai-based investment firm that acquires and operates multifamily and mixed-use assets across Maharashtra and one other state. The team evaluates 15–25 deals per year and holds a portfolio of roughly 800 units. Decisions are made by a small investment committee that relies on consistent, comparable analysis and clear hurdle rates.

Challenges before Proforma Studio

Deal analysis lived in spreadsheets—one file per deal, with formulas copied and tweaked by hand. There was no standard way to include India-specific costs: stamp duty, registration, and TDS had to be added manually and often differed between analysts. Comparing two deals meant opening two workbooks and reconciling assumptions. Running 'what if' scenarios (e.g. higher vacancy, different rent growth) required duplicating sheets and risked formula errors. After acquisition, actual performance was tracked in separate reports, so linking back to the original proforma was difficult. The result was longer underwriting cycles, inconsistent hurdle-rate application, and occasional surprises when deals closed because upfront costs had been understated.

Why they chose Proforma Studio

The team wanted a single platform where every deal could be modeled the same way, with Indian stamp duty, registration, and TDS built in so that total cost of acquisition was always visible. They needed to compare Base, Downside, and Upside scenarios side by side and to track actual rents and expenses against the proforma after closing. Proforma Studio's country context (India, with currency and date format) and the ability to model purchase price, financing, rent schedule, vacancy, and operating expenses—with country-specific taxes and fees automatically included—matched their workflow. The fact that the same tool could later support portfolio-level views and document automation was a plus for future rollout.

Implementation

The team implemented Proforma Studio's Proforma module as the standard for all new deal underwriting. For each opportunity they now: (1) Create a deal in the India context so that currency (INR), date format, and tax rules default correctly. (2) Enter purchase price and financing assumptions, then build the rent schedule (by unit type or property) and apply vacancy and operating expense assumptions. (3) Rely on the platform to add stamp duty, registration fees, and TDS into the total cost of acquisition and multi-year cash flows. (4) Run Base, Downside, and Upside scenarios (e.g. different vacancy or rent growth) and compare NOI, cash-on-cash, and IRR in one view. (5) After acquisition, update the same deal with actual rents and expenses and use the platform to monitor actual vs proforma, so that underperforming assets are visible quickly. The investment committee now reviews a standardized output for every deal, with hurdle rates applied consistently.

Outcomes

Within four months of rollout, the team reported a 40% reduction in the time from receiving a deal pack to presenting a recommendation—from an average of five days to three. Fewer last-minute corrections were needed at closing because upfront costs were consistently modeled. The committee declined two deals that had looked attractive in ad-hoc spreadsheets but failed the hurdle once country-specific costs and downside scenarios were applied. Post-acquisition, actual-vs-proforma tracking helped identify one underperforming asset earlier, leading to faster operational intervention. Qualitatively, the team described better alignment between analysts, more confidence in cross-deal comparison, and a clearer audit trail for why deals were approved or rejected.

Client quote

“We used to spend days making sure our spreadsheets were comparable and that we hadn't missed stamp duty or registration in one of the states. Now we model every deal the same way, run scenarios in minutes, and we can see how assets are performing against our underwriting. It's made our process more disciplined and our decisions easier to explain.”