The Compliance Ledgercomplianceledger.in
Proactive Indian AI Governance · complianceledger.in

Proactive AI gap analysis for Indian industry.

Global incident trackers document AI failures after harm occurs. India’s TEC incident reporting standard (TEC 57090:2025) deliberately leaves proactive compliance and enforcement outside its scope. Enterprise GRC startups sell private tools behind NDAs.

The Compliance Ledger fills the vacuum: we examine live automated decision systems in sensitive Indian domains (lending, hiring, healthcare, ed-tech) and publish evidence-qualified gap analysis against statutory law and the open SutraCheck rubric—before failures occur.

High-Risk Domains4 Sensitive Sectors
Dual EvaluationBinding vs Voluntary
Evidentiary Rule100% Public Records
Legal DefensibilityStrict Hedged Syntax
SUTRACHECK DETERMINISTIC RUNTIME

Deterministic classification. Zero LLM hallucination.

Audit outcomes are not prompted into an AI model. Public findings are fed into SutraCheck’s deterministic rule engine, verifying statutory compliance against coded Indian legal provisions.

sutracheck-engine/v0.4.2-preview
Target: Composite — Automated Underwriting & Alternative Credit ScoringOpen Engine
Domain RiskHigh Risk Tier
Binding Gaps2 flagged
Voluntary Gaps2 flagged
Disclosures2 verified
//SutraCheck Engine Standard Evaluation Matrix OutputRAW_DATA
[SUTRACHECK-CORE-CLASSIFIER v0.4.2]
TARGET_PROFILE: "FinTech Automated Lending / Retail Credit Scoring (Composite IN-01)"
JURISDICTION: "India (Union) · Sector: RBI Regulated Entities / LSP Intermediaries"

>>> DOMAIN_RISK_EVALUATION
- Domain: "Consumer Financial Credit Allocation"
- Severity Tier: HIGH (Statutory impact on fundamental livelihood and financial access)
- Sensitive Vectors: [Algorithmic Exclusion, Asymmetric Data Ingestion, Black-Box Denials]

>>> COLUMN_A: BINDING INDIAN LAW (STATUTORY)
- Mandate CPA-2019 / RBI-DLG-2022 (Grievance Redressal for Algorithmic Rejections): GAP_DETECTED
  Evidence: "No public evidence of algorithmic appeal or grievance escalation in public privacy policy."
- Mandate DPDPA-2023 Sec 5 (Notice & Profiling Transparency): GAP_DETECTED
  Evidence: "No public disclosure indicating automated ML risk profiling at consent capture."
- Mandate RBI-DLG-2022 (Regulated Entity & Lending Service Provider Disclosure): SATISFIED
  Evidence: "Partner NBFCs explicitly identified in application disclosures and footer."

>>> COLUMN_B: SUTRACHECK VOLUNTARY SUTRA RUBRIC (ACCOUNTABILITY)
- Pillar 1 (Demographic Bias & Fairness Audit Transparency): GAP_DETECTED
  Evidence: "No publicly verifiable demographic parity or fairness benchmark reports."
- Pillar 3 (Human-in-the-Loop Escalation for Borderline Rejections): GAP_DETECTED
  Evidence: "Zero-touch straight-through processing; no human review conduit disclosed."
- Pillar 4 (Adverse Action Explainability & Plain-Language Reasons): PARTIAL_DISCLOSURE
  Evidence: "High-level factor categories listed in FAQs without individualized actionable rationale."

MATRIX_RESULT: 2 BINDING GAPS | 2 VOLUNTARY GAPS | 1 PARTIAL | 1 SATISFIED
Feature 2: Real Engine Evaluation Verification
hash: sha256-verifiedstatus: 200 OK
// The Structural Gap

Why proactive, public evaluation is missing.

Every existing initiative in the ecosystem is either reactive or private. Nobody is publishing public, evidence-qualified gap analysis before disaster strikes.

Reactive Only

Incident Trackers & MIT

Databases like the AI Incident Database and MIT's classifier catalog harms post-catastrophe. None specialize in Indian jurisprudence, and none evaluate compliance before a breach.

Posture:Post-harm documentation
Excluded Scope

TEC Standard (TEC 57090:2025)

India's Telecommunications Engineering Centre issued standard TEC 57090:2025, but it explicitly confines itself to incident database schemas and taxonomy, leaving proactive compliance auditing and enforcement outside its scope.

Posture:Classification without enforcement
The Ledger's Role

The Compliance Ledger

Proactive, evidence-qualified, public evaluation. Applying the SutraCheck two-column rubric against publicly verifiable disclosures to identify statutory and voluntary gaps before harm occurs.

Posture:Pre-emptive gap analysis
// Benchmark Audit

Latest Published Analysis

View All Reports (1)
FinTech / Credit ScoringComposite Case StudyHigh Risk Tier · Lending & Underwritingpublished
Published: September 2026

Composite — Automated Underwriting & Alternative Credit Scoring

An evidence-qualified gap analysis of an archetypal Indian digital lending platform utilizing machine learning models to score creditworthiness and automate loan approvals. Evaluated against binding Indian statutes (DPDPA 2023, Consumer Protection Act 2019, RBI Digital Lending Guidelines) and voluntary SutraCheck governance pillars.

Sector Vectorlending
Binding Law Gaps2 Flagged
Voluntary Gaps2 Flagged
Public Disclosures2 Verified
// Institutional Safeguards

The 6 Non-Negotiable Features

How The Compliance Ledger maintains rigorous defensibility and objectivity across every published gap analysis.

01 // Public Methodology

Public Selection Methodology

Non-arbitrary criteria: sector risk classification (lending, hiring, healthcare, ed-tech), verifiable public documentation, and regulatory relevance.

02 // Engine Matrix

SutraCheck Engine Output

No freehand essays. Public facts are fed into the SutraCheck classifier engine, publishing the actual terminal matrix alongside analysis.

03 // Enforced Hedging

Enforced Hedged Syntax

No bare verdicts. Findings are structurally locked to: "no public evidence found of [X], as of [date], based on [source]."

04 // Right of Reply

7-Day Right of Reply

Pre-publication notification window for named subjects to submit factual corrections or disclosure updates, published verbatim.

05 // Voluntary Review

Opt-In Self-Review Track

Forward-looking AI platforms can voluntarily request a Ledger review as tangible proof of transparency and compliance readiness.

06 // Immutable Log

Permanent Version History

Company practices evolve. Re-evaluations are published as dated entries to the permanent record, mirroring our changelog discipline.

// Knowledge Base & Primer

Frequently Asked Questions

Key insights regarding our deterministic engine, Indian statutory scope, and the 7-day pre-publication Right of Reply.

Scope & Methodology

How does the Ledger differ from global AI trackers?

Global trackers catalog harms retrospectively after catastrophe and map to EU/US laws. The Compliance Ledger evaluates live Indian deployments proactively before harms occur.

Public Evidence

Do you inspect private code or proprietary weights?

No. We evaluate only publicly verifiable documentation: terms of service, privacy notices, engineering blogs, API disclosures, and regulatory filings under Indian transparency mandates.

Procedural Fairness

How does the 7-day Right of Reply operate?

Named subjects receive an advance copy 7 business days prior to release. Corrections and updated documentation are verified, and company statements are published verbatim alongside the report.

// Feature 5 · Voluntary Participation Track

Turn proactive transparency into a competitive advantage.

Does your company operate automated decision-making in India? Request an opt-in Ledger evaluation. Demonstrate proof of transparency to regulators, enterprise partners, and end users.