OPFI vs QFIN

OppFi Inc. vs Qfin Holdings, Inc. — Valuation Comparison 2026

OPFI

Credit Services
OppFi Inc.
Quality
8.9
out of 10
Value Trap
12
SAFE
Price
$8.34
Last close
Models
12/13
Active
VS

QFIN

Credit Services
Qfin Holdings, Inc.
Quality
10.0
out of 10
Value Trap
12
SAFE
Price
$15.37
Last close
Models
5/13
Active

Model-by-Model Comparison

ModelType OPFI Fair ValueOPFI Upside QFIN Fair ValueQFIN Upside
Bayesian DCF Intrinsic $34.15 +309.5%
Earnings Power Value Intrinsic $4.62 -44.6% $74.07 +381.9%
EROIC Spread Intrinsic $2.13 -74.4% $46.84 +204.8%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
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 OPFI vs QFIN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

OPFI vs QFIN — Which Stock Is More Undervalued?

QFIN scores higher with a 10.0/10 quality rating vs OPFI's 8.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing OppFi Inc. (OPFI) and Qfin Holdings, Inc. (QFIN) 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.

OPFI currently trades at $8.34 with a QOC of 8.9/10, while QFIN trades at $15.37 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).