BSBR vs BSVN

Banco Santander Brasil SA vs Bank7 Corp. — Valuation Comparison 2026

BSBR

Banks - Regional
Banco Santander Brasil SA
Quality
6.1
out of 10
Value Trap
20
SAFE
Price
$5.45
Last close
Models
10/13
Active
VS

BSVN

Banks - Regional
Bank7 Corp.
Quality
10.0
out of 10
Value Trap
12
SAFE
Price
$44.39
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BSBR Fair ValueBSBR Upside BSVN Fair ValueBSVN Upside
Bayesian DCF Intrinsic $2.26 -58.5% $51.38 +15.8%
Earnings Power Value Intrinsic $4.78 -12.3% $76.95 +73.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for BSBR vs BSVN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BSBR vs BSVN — Which Stock Is More Undervalued?

BSVN scores higher with a 10.0/10 quality rating vs BSBR's 6.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Banco Santander Brasil SA (BSBR) and Bank7 Corp. (BSVN) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

BSBR currently trades at $5.45 with a QOC of 6.1/10, while BSVN trades at $44.39 with a QOC of 10.0/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).