To the Admissions Committee: I taught the applicant Financial Economics and Statistics, and supervised their independent study. I recommend them for your MS in Finance.
The applicant's independent project backtested a momentum strategy on NSE mid-caps, and its value lay in how it failed. Rather than report a flattering paper return, they showed how transaction costs and survivorship bias erased the edge — and wrote more pages on why the strategy died than on its apparent success. A student who understands that a backtest's assumptions matter more than its Sharpe ratio is unusually well-prepared for graduate finance.
They cleared CFA Level I on their first attempt in their final year while carrying a full course load, and they use statistics as a working tool, not a memorized formula. In class they repeatedly probed the gap between paper price and executed price — the microstructure questions most undergraduates never think to ask.
I recommend them without reservation for graduate study in finance.
To the Admissions Committee: I head a credit desk at an NBFC and have supervised the applicant, a credit analyst, for three years. I support their MS in Finance application.
The applicant built our desk's first standardized template for underwriting small manufacturers that banks won't model — blending banked cash-flow analysis with unconventional verification like electricity-load records against claimed capacity. Loans underwritten on their template have run at roughly half the delinquency of our book average across two monsoon-affected cycles, and it is now mandatory desk practice.
They are applying for exactly the right reason. Their template is empirical craft; they cannot yet state its assumptions formally, stress it against rate shocks, or price the risk it measures beyond our house grid. When our treasury team discussed securitizing a slice of the book, they could describe every loan and nothing rigorous about the pool. The gap between those two abilities is the syllabus they're pursuing.
They are analytically rigorous and honest about the limits of their own tools. I recommend them strongly.
To the Admissions Committee: I supervised the applicant's research assistantship on credit-risk modeling for thin-file borrowers. I recommend them for your MS in Finance.
The applicant worked on modeling default risk for first-time borrowers with no bureau history — a genuinely hard problem where the standard models fail structurally. What impressed me was their refusal to over-claim: when their model performed well on a subgroup, they investigated whether it was signal or an artifact of an imbalanced sample, and honestly reported that part of it was the latter.
They handle data carefully, document their assumptions, and understand that in credit modeling a false sense of precision has a social cost — a family wrongly denied credit. That ethical seriousness about model error is rare and valuable.
They are methodical, skeptical, and ready for rigorous graduate work in finance. I recommend them highly.
To the Admissions Committee: I run treasury at a firm that worked with the applicant's credit desk on a securitization exercise, and I offer this recommendation for their MS in Finance from the counterparty's seat.
In diligence, the applicant was the analyst who actually understood the loans in the pool. When I pressed on a segment I suspected was riskier than rated, they didn't get defensive; they pulled the underlying files and confirmed I was partly right, then quantified exactly how much. An analyst who will validate the counterparty's doubt against their own book is someone you want on a deal.
They communicated the pool's characteristics without the usual sell-side gloss, stating clearly where the data was thin. That candor made the transaction faster, not slower, because I didn't have to independently verify everything they told me.
I recommend them enthusiastically. Their instinct for honest disclosure is exactly what graduate finance training should refine.