Aditya Birla Money Limited (BIRLAMONEY) Fair Value & Analysis
Financial Services · IN · Market cap ₹7.9B
Fair value as of: Jun 29, 2026
Analysis
Aditya Birla Money Limited (BIRLAMONEY) currently trades at ₹140.87, while our model-based Fair Value estimate is ₹74.39 — implying the stock looks roughly 47.2% overvalued today. We read business quality at 97/100 (high quality), in the Financial Services sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Aditya Birla Money Limited provides financial services in India. It operates through Broking, Whole Debt Market, and Others segment. The company offers stock and commodity broking, portfolio management, depository, and e-insurance repository solutions; distributes other financial products; and invests in stocks, mutual funds, and initial public offerings (IPOs). It is also involved in equity and derivative trading through NSE and BSE; currency derivative through MCX-SX; and commodities trading through MCX and NCDEX, as well as margin funding activities. In addition, the company provides Elevate app, a trading platform and investing app; Elevate web, a web trading platform for trading and updates; Open Store API for various financial products; Mutual Funds Platform, a mutual fund interface; and Express Trade, a desktop trading application. Further, it distributes life and health insurance, mutual funds, and loan products; and offers home, business, and personal loans, as well as inve…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.