PT Lippo General Insurance Tbk (LPGI) Fair Value & Analysis
Financial Services · ID · Market cap 1.9T IDR
Fair value as of: Jun 26, 2026
Analysis
PT Lippo General Insurance Tbk (LPGI) currently trades at 685.00 IDR, while our model-based Fair Value estimate is 627.17 IDR — implying the stock looks roughly 8.4% overvalued today. We read business quality at 95/100 (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
PT Lippo General Insurance Tbk provides insurance products and services for individuals, families, and corporate clients in Indonesia. It operates through Property, Motor Vehicles, Marine Cargo, Marine Hull, Aviation Hull, Engineering, Health, Credit, and Others segments. The company offers health insurance products, including Medicare for company employees and their dependents; HealthPlus Family and Perlindungan Kesehatan Prima for individuals and families; HealthPlus Micro and HealthPlus Business for employees of small- to medium-sized companies; Elite Health Plan, which is a private medical insurance product; and Asuransi Jalan Prima for outpatient care. It also provides auto protection, motor protection, home care, marine cargo, domestic and international travel, business care, and aviation hull insurance; and contractor/erection all risk, engine damage, demolition, legal liability, money, heavy equipment, hole-in-one, and shipbuilder's risk insurance. In addition, the company o…
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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.