OP_PRLNpeeranalysis.aceanalytics.dev

Read a bank against
a fair peer set.

Peer Lens runs an AI agent to identify a defensible peer group from FDIC regulatory data, compares it across 44 metrics, and an advisor-backed model writes CFO-grade takeaways - interpretation by AI, every figure grounded in the Call Report.

44
metrics compared
~11
defensible peers
0
fabricated figures
peeranalysis.ace / Arvest Bank vs 11 peers
PEER PERCENTILE · 12 BANKS · FDIC ARVEST
ROA
0.54%
0th
Efficiency
83.2%
100th
NIM
4.00%
73th
ROTCE
11.4%
18th
CET1
11.5%
18th
01

Agentic peer identification

An AI agent assembles candidates from FDIC data - asset band, business model, Fed region, proximity - then an advisor model pressure-tests whether the set is defensible. Sweep and trust banks are screened out; swap any member by hand.

02

44 regulatory metrics

Scale, profitability, funding, capital, and asset quality - FDIC Call Report-derived and bank-level. Computed in code, not guessed, for clean comparability.

03

Direction-aware

Efficiency, cost of funds, NIE/assets, and charge-offs read better-when-lower. Percentile is position, not virtue.

04

AI analysis, grounded

An AI analyst - an executor model with a stronger advisor - writes mechanism-level findings, watch items, and caveats. Every figure is cited from the computed stats; the model never invents one.

OP_PRLN_02·How the peer set is built

Regulatory-first, screened for outliers,
and defensible to a CFO.

Start from FDIC BankFind. An agent screens candidates to a 0.5x-2.0x asset band, gates on business model and Fed region, ranks by proximity, and an advisor model checks the set's defensibility - sweep and trust banks fall into a tray you can pull back in. The metrics are computed in code and grounded in the Call Report; the AI interprets them, it never invents a number.

OP_PRLN_03·Flow

Pick. Compare. Read.

01

Pick a target

Type a bank name or FDIC CERT. Ambiguous names disambiguate by certificate.

02

Agent builds the set

An AI agent proposes a defensible ~11-bank group and an advisor model pressure-tests it; remove, swap, or pull screened-out banks back in.

03

Read the AI analysis

Percentile strips, a performance-frontier scatter, and AI-written CFO-grade findings - every figure traced to FDIC.

Benchmark a bank in under a minute.

Peer Lens replaces the hand-built comp sheet with agentic peer identification and AI analysis, grounded in regulatory data.