Fundamental Credit Analysis, Strengthened by Code & Valuation.
I am a 3rd-year Data Science student at IIT Madras, learning to look at finance through both numbers and first principles. I am building my foundation in valuation, private credit, and due diligence through Prof. Aswath Damodaran's work, while using code, AI, and automation to make financial analysis sharper, faster, and more useful. My aim is simple: combine quantitative thinking with sound finance to turn complex information into decisions that hold up.
Learn the Fundamentals. Build the Advantage.
I start with the fundamentals: understanding what the numbers say, what the documents allow, and where the real risks are. Then I use code and AI to make that work more efficient, repeatable, and useful.
Understanding Value from the Ground Up
I am working through corporate finance and valuation with Aswath Damodaran's material, building DCFs, connecting credit metrics to default risk, and testing how businesses hold up when conditions change.
- Credit Metrics & Default Risk
- Cash Flow & Debt Capacity
- Recovery & Downside Analysis
Making Analysis More Useful with Tech
I use Python, NLP, and AI to work through the repetitive parts of diligence: finding important clauses in long credit agreements, structuring messy data, and creating tools that leave more room for actual judgment.
- Credit Agreement & Covenant Search
- Financial Data Analysis in Python
- Repeatable Diligence Workflows
Learning in Public
I write about the ideas I am learning in private credit, from liability management and lender protections to direct lending and the forces shaping debt markets. Writing helps me test what I think I understand.
- Deal Breakdowns & Finance Primers
- Lender Protections & Covenants
- Sharing Models & Lessons Learned
Where the Analysis Gets Practical.
I am building the habit of looking at a business from the lender's side: how it earns, how much debt it can carry, and what protects capital when the plan changes.
How Businesses Carry Debt
Learning how direct-lending structures work in practice: debt capacity, cash generation, covenant headroom, and the details that shape risk for middle-market borrowers.
Finding the Real Earnings
Looking past reported numbers to understand recurring performance, working capital needs, and the obligations that may not be obvious at first glance.
Protecting the Downside
Studying what happens when a borrower is under pressure: recovery values, creditor priorities, covenant protections, and the decisions that shape a restructuring.
Private Credit Studies in Progress.
These three case studies are currently being developed. I will publish the supporting memos, analysis, and deal breakdowns as each study is completed.
Whether Interest Earned Adequately Compensates Private Credit Firms for Risk Taken
An ongoing study of whether coupon income, fees, and downside protection compensate private credit firms for default, liquidity, concentration, and recovery risk.
INR 1,000 Cr Healthcare Rescue Financing
A study of second-lien rescue capital, working-capital pressure, subordinated debt, liquidity gaps, and recovery allocation for an Indian healthcare borrower.
INR 700 Cr SaaS ARR Facility
A study of debt capacity against recurring revenue, retention quality, cash-sweep mechanics, minimum liquidity, and lender protection in an Indian SaaS business.