Quilter plc (QLT) Fair Value & Analysis
Financial Services · GB · Market cap 2.6B GBX
Analysis
Quilter plc (QLT) currently trades at p1.93, while our model-based Fair Value estimate is p1.49 — implying the stock looks roughly 22.7% 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
Quilter plc provides advice-led investment solutions in the United Kingdom and internationally. It operates through High Net Worth and Affluent segments. The High Net Worth segment provides discretionary investment management services to high-net worth clients, charities, companies, and institutions through a network of branches; and financial advice services for protection, mortgages, savings, investment, and pensions primarily to high-net-worth clients. Its Affluent segment comprises Quilter Investment Platform, an investment platform for advice-based wealth management products and services; Quilter Investor, which offers investment solutions in the form of funds for the group and third-party clients; and Quilter Financial planning, a restricted and independent financial adviser network that provides mortgage and financial planning advice, and solution for individuals and business through a network of intermediaries. The company was incorporated in 2007 and is based in London, the…
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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.