SSM-Audit – Case Studies: Strategy & Generic Guidance (4.0)

Purpose. Executive-level, copy-ready guidance to present real and illustrative case studies without bundling third-party data on this blog. Methods, schemas, and tiny synthetic snippets appear here; complete artifacts (scripts, longer vectors, stamped logs) are available via the repository link below. Classical values remain unchanged: phi((m,a)) = m. Clamp everywhere: a := clamp(a, -1+eps_a, +1-eps_a).

Two-track evidence model (why both).

  • Track A — Public, stampable reproductions. Uses open indicators and finance tables with fixed knobs and one-screen math. Blog stays dataset-neutral; full, step-by-step materials are provided at the link below.
  • Track B — Real companies (anonymized until clearance). Shows how a bounded lane beside classical KPIs surfaces stability debt early (bands and S(m,a) := m*a), while the reported numbers stay identical.

What appears here (safe to copy).

  • Schemas & formulas. CSV headers, band policy, identities (atanh/tanh, {U,W} fuse).
  • Tiny synthetic snippets. Minimal rows that demonstrate the pipeline.
  • Stamp line format. One per day to anchor runs (optional).
  • Executive summaries. Narrative of what changed (bands, early warnings).

What does not appear here.

  • No third-party CSVs or license text.
  • No screenshots of proprietary dashboards.
  • No PII or sensitive logs.

Finance lane mappers (library recap, ASCII).

coverage:  a := 2*q - 1
agreement: a := tanh( 1 - |m1 - m2| / b )
residual:  a := tanh( k*( 1 - |actual - forecast| / s ) )
sdi:       a_sdi := tanh( (SUM atanh(a_i)) / n )
fuse:      a_out := tanh( (SUM w*atanh(a)) / max(SUM w, eps_w) )
clamp:     a := clamp(a, -1+eps_a, +1-eps_a)
collapse:  phi((m,a)) = m
defaults:  eps_a=1e-6, eps_w=1e-12
bands:     A++: a>=0.75; A+: a>=0.50; A0: a>=0.25; A-: a>=0.10; else A--
hysteresis: promote if delta_a >= +0.05; demote if delta_a <= -0.05

CSV schema (pilot-ready).

time,kpi,m,a,band,knobs_hash,build_id,stamp

Synthetic generator (drop-in; demonstrates lanes, bands, SDI).

from math import atanh, tanh
from datetime import date, timedelta

EPS_A, EPS_W = 1e-6, 1e-12

def clamp_a(a): 
    return max(-1+EPS_A, min(1-EPS_A, a))

def band_of(a):
    return "A++" if a>=0.75 else "A+" if a>=0.50 else "A0" if a>=0.25 else "A-" if a>=0.10 else "A--"

def fuse_tanh_mean(as_, ws_=None):
    if not as_:
        return 0.0
    if ws_ is None: 
        ws_ = [1.0]*len(as_)
    U=W=0.0
    for a,w in zip(as_, ws_):
        a = clamp_a(a)
        U += w*atanh(a); W += w
    return tanh(U / max(W, EPS_W))

def demo_rows():
    print("time,kpi,m,a,band,knobs_hash,build_id,stamp")
    t0 = date(2025,10,1)
    rows=[]
    # AR coverage
    for d in range(5):
        m = 0.96                      # classical ratio (unchanged)
        q = 0.92 - 0.02*d             # within-window coverage trending down
        a = clamp_a(2*q - 1)
        rows.append((t0+timedelta(days=d),"AR_collected_issued",m,a))
    # Refunds agreement
    for d in range(5):
        m_platform = 0.021 + 0.0005*d
        m_bank     = 0.020
        b = 0.005
        dlt = abs(m_platform - m_bank)
        m = m_platform                # classical choice (unchanged)
        a = clamp_a(tanh(1 - dlt/b))
        rows.append((t0+timedelta(days=d),"Refunds_agreement",m,a))
    # Forecast residual
    for d in range(5):
        forecast = 1_000_000
        actual   = 1_000_000 - 10_000*d
        r = actual - forecast
        s, k = 50_000, 1.2
        m = actual                    # classical actual (unchanged)
        a = clamp_a(tanh(k*(1 - abs(r)/s)))
        rows.append((t0+timedelta(days=d),"Revenue_actual",m,a))

    # Emit rows with bands and dummy hashes
    for t,kpi,m,a in rows:
        band = band_of(a)
        print(f"{t.isoformat()},{kpi},{m:.6f},{a:.6f},{band},knobshash_demo,build_demo,")
    # SDI sketch (same days, subset lanes)
    print("# SDI (daily tanh-mean over {AR, Refunds, Revenue})")
    by_day={}
    for t,kpi,m,a in rows:
        by_day.setdefault(t,[]).append(a)
    for t in sorted(by_day):
        a_sdi = fuse_tanh_mean(by_day[t], None)
        print(f"# {t.isoformat()}, SDI={a_sdi:.6f}")

demo_rows()

Daily stamp line (optional; one per file/day).

SSMCLOCK1|iso_utc|rasi_idx|theta_deg|sha256(file)|chain
# chain_0 := "0"*64
# chain_k := sha256( ascii(chain_{k-1} + "|" + stamp_core_k) )

Reproduction checklist (pass/fail).

  1. Clamp discipline before any atanh; re-clamp after any tanh.
  2. Order-invariance: a_out := tanh(U/max(W,eps_w)) equals any permutation.
  3. M2 identities for products/ratios when applicable.
  4. Collapse parity everywhere: phi((m,a)) = m.
  5. Bands + hysteresis match declared thresholds and gates.
  6. Stamps (optional): single ASCII anchor per day.
  7. Determinism: fixed knobs yield byte-stable CSV for a and band; knobs_hash flips on any knob change.

Where to find full materials.
For extended scripts, optional conformance vectors, and sample logs, use the repository link below. Keep blog pages generic; keep concrete files in the repository.


Navigation
Previous: SSM-Audit – Deeper Finance Modules (3.6–3.7)
Next: SSM-Audit – Case Study A: Stability Debt in a Collapsing Firm (4.1A)


Directory of Pages
SSM-Audit – Table of Contents


Frequently asked questions
SSM-Audit Q & A


Explore Further
https://github.com/OMPSHUNYAYA/Symbolic-Mathematical-Audit

Disclaimer
Research/observation only. Not for operational, safety-critical, or legal decision-making.