Arbuthnot Banking Group (ARBB) Fair Value & Analysis
Financial Services · GB · Market cap 131M GBX
Fair value as of: Jun 26, 2026
Analysis
Arbuthnot Banking Group (ARBB) currently trades at p8.30, while our model-based Fair Value estimate is p14.30 — implying the stock looks roughly 72.3% undervalued today. We read business quality at 95/100 (high quality), in the Financial Services sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Arbuthnot Banking Group PLC, together with its subsidiaries, provides private and commercial banking products and services in the United Kingdom. The company operates through Banking, Wealth Management, RAF, ACABL, AAG, All Other Divisions, and Group Center segments. It offers private and commercial banking services, including current and deposit accounts, loans, overdrafts, guarantees, charge cards, foreign exchange, mortgage portfolio service, bespoke commercial banking services, and tailored secured lending against property investments and other assets. In addition, the company provides financial planning; investment and asset management; asset finance funding; asset-based lending; deposits; and specialist finance. In addition, the company provides commercial vehicle finance and related services; secured finance on invoices, assets, and stock; and property investment, management, and development services. Arbuthnot Banking Group PLC was founded in 1833 and is headquartered in Lon…
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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.