IAP-FIN: Building AI Audit Trails That Actually Satisfy Financial Regulators

The $35 Million Question: Can You Prove What Your AI Did?

The EU AI Act penalty for prohibited AI practices: €35 million or 7% of global turnover.

MiFID II RTS 25 requires 100 microsecond UTC accuracy for high-frequency trading timestamps.

SEC Rule 17a-4 demands 6-year retention in WORM-compliant storage.

DORA requires incident reports within 4 hours containing 101 data points.

If your trading algorithm makes a bad decision tomorrow, can your audit system satisfy all of these requirements simultaneously?

For most financial institutions, the honest answer is: probably not.

---

The Regulatory Patchwork Problem

Financial services AI faces a unique compliance challenge: there's no single standard for AI audit trails. Instead, there's a patchwork of overlapping requirements across jurisdictions and subsectors.

The Global Regulatory Matrix

Requirement	EU	US	UK	Singapore	Australia
Timestamp precision	100μs (HFT)	50ms (CAT)	100μs (MiFID equivalent)	Not specified	Not specified
Retention period	5-7 years	6 years	6 years	5 years	7 years
AI-specific logging	EU AI Act Art.12	SR 11-7 (Fed)	FCA guidance	MAS AI guidelines	APRA CPS 234
Incident reporting	4 hours (DORA)	"Prompt"	"Promptly"	24 hours (material)	24 hours
Storage format	Not specified	WORM required	WORM recommended	Not specified	Not specified

Every institution operating globally must satisfy the union of all applicable requirements—effectively implementing to the strictest standard in each category.

The Missing Standard

Here's what doesn't exist: a comprehensive, open standard for AI audit trails in financial services.

• ISO/IEC 42001 (AI Management System): General framework, no financial specifics
• IEEE 2894 (Explainable AI): Architecture guidance, no compliance documentation
• NIST AI RMF: Risk management, no prescriptive audit specifications

The result? Every institution builds proprietary solutions. Auditors face inconsistent formats. Regulators can't efficiently verify compliance. The industry spends $9.8 billion annually on RegTech without a common audit trail format.

---

IAP-FIN: Industry Application Profile for Financial Services

VAP-IAP-FIN-001 fills this gap. It's an industry application profile that maps the generic VAP (Verifiable AI Provenance) framework to the specific requirements of financial services.

The Architecture: Layered Conformance

┌─────────────────────────────────────────────────────────────────┐
│  VAP Framework (Cross-Domain)                                   │
│  ───────────────────────────────────────────────────────────    │
│  Core cryptographic requirements, hash chains, Merkle trees     │
└─────────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────────┐
│  IAP-FIN Base Conformance                                       │
│  ───────────────────────────────────────────────────────────    │
│  Mandatory fields for ALL financial AI systems                  │
│  • Decision identifier (UUID v7)                                │
│  • UTC timestamp (precision configurable)                       │
│  • Model identifier + version + hash                            │
│  • Input data hash                                              │
│  • Output/decision value                                        │
│  • Confidence score                                             │
│  • Operator LEI                                                 │
│  • Cryptographic signature                                      │
└─────────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────────┐
│  Subsector Profiles                                             │
│  ───────────────────────────────────────────────────────────    │
│  ┌─────────────┐ ┌─────────────┐ ┌─────────────┐               │
│  │  Capital    │ │   Banking   │ │  Insurance  │               │
│  │  Markets    │ │             │ │             │               │
│  └─────────────┘ └─────────────┘ └─────────────┘               │
│  ┌─────────────┐ ┌─────────────┐                               │
│  │  Payments   │ │    Asset    │                               │
│  │             │ │  Management │                               │
│  └─────────────┘ └─────────────┘                               │
└─────────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────────┐
│  Jurisdictional Extensions                                      │
│  ───────────────────────────────────────────────────────────    │
│  ┌────┐ ┌────┐ ┌────┐ ┌──────┐ ┌─────┐                        │
│  │ EU │ │ US │ │ UK │ │ APAC │ │ GCC │                        │
│  └────┘ └────┘ └────┘ └──────┘ └─────┘                        │
└─────────────────────────────────────────────────────────────────┘

This layered approach means:

1. Base conformance is universal—every financial AI system implements it
2. Subsector profiles add domain-specific requirements
3. Jurisdictional extensions handle regulatory variations

---

Timestamp Precision: The Hidden Complexity

One of IAP-FIN's key contributions is configurable timestamp precision. Different use cases have radically different requirements:

Precision Tiers

Use Case	Minimum Precision	Clock Sync	Standard
HFT algorithmic trading	1 microsecond	PTP to BIPM UTC	MiFID II RTS 25
Non-HFT algo trading	1 millisecond	NTP to UTC	MiFID II
Credit decisioning	1 second	NTP to UTC	Reg B
Insurance/actuarial	1 day	System clock	Solvency II
Fraud detection	1 millisecond	NTP to UTC	PSD2/PSD3

Why This Matters

HFT systems generate millions of events per second. Requiring 1-microsecond precision for an insurance actuarial model would be absurd—and expensive. Requiring only 1-day precision for HFT would violate MiFID II.

IAP-FIN lets implementations declare their precision tier and validates accordingly.

Implementation: Precision Time Protocol

For Tier 1 (microsecond) precision, NTP isn't sufficient. You need PTP (IEEE 1588-2019):

from dataclasses import dataclass
from enum import Enum
from typing import Optional
import time

class PrecisionTier(Enum):
    TIER_1_MICROSECOND = "T1"  # HFT: PTP required
    TIER_2_MILLISECOND = "T2"  # Standard algo: NTP sufficient
    TIER_3_SECOND = "T3"       # Credit/banking
    TIER_4_DAY = "T4"          # Insurance/actuarial


@dataclass
class IAPTimestamp:
    """IAP-FIN compliant timestamp with precision metadata"""

    utc_nanoseconds: int
    precision_tier: PrecisionTier
    clock_source: str  # "PTP", "NTP", "GPS", "SYSTEM"
    uncertainty_ns: int  # Clock uncertainty in nanoseconds
    sync_status: str  # "LOCKED", "HOLDOVER", "FREERUN"

    @classmethod
    def now(cls, tier: PrecisionTier) -> "IAPTimestamp":
        """Generate timestamp for specified precision tier"""

        if tier == PrecisionTier.TIER_1_MICROSECOND:
            # In production: read from PTP hardware clock
            # This is a placeholder
            return cls(
                utc_nanoseconds=time.time_ns(),
                precision_tier=tier,
                clock_source="PTP",
                uncertainty_ns=50,  # 50ns typical for good PTP
                sync_status="LOCKED"
            )
        elif tier == PrecisionTier.TIER_2_MILLISECOND:
            return cls(
                utc_nanoseconds=time.time_ns(),
                precision_tier=tier,
                clock_source="NTP",
                uncertainty_ns=1_000_000,  # 1ms typical for NTP
                sync_status="LOCKED"
            )
        else:
            return cls(
                utc_nanoseconds=time.time_ns(),
                precision_tier=tier,
                clock_source="SYSTEM",
                uncertainty_ns=10_000_000,  # 10ms for system clock
                sync_status="FREERUN"
            )

    def to_dict(self) -> dict:
        return {
            "utc_ns": self.utc_nanoseconds,
            "precision_tier": self.precision_tier.value,
            "clock_source": self.clock_source,
            "uncertainty_ns": self.uncertainty_ns,
            "sync_status": self.sync_status
        }

    def validate_for_tier(self) -> bool:
        """Validate timestamp meets precision tier requirements"""

        max_uncertainty = {
            PrecisionTier.TIER_1_MICROSECOND: 1_000,       # 1μs
            PrecisionTier.TIER_2_MILLISECOND: 1_000_000,   # 1ms
            PrecisionTier.TIER_3_SECOND: 1_000_000_000,    # 1s
            PrecisionTier.TIER_4_DAY: 86_400_000_000_000   # 1 day
        }

        return self.uncertainty_ns <= max_uncertainty[self.precision_tier]

---

Entity Identification: LEI Integration

IAP-FIN mandates LEI (Legal Entity Identifier) for operator identification. Over 200 regulations globally require LEI—it's the universal entity identifier for financial services.

Why LEI?

• Global uniqueness: 20-character alphanumeric code
• Verified identity: Certified by GLEIF-accredited LOUs
• Cross-reference capability: Maps to BIC, ISIN, MIC, OpenCorporates
• Verifiable LEI (vLEI): Digital certificates for cryptographic authentication

Implementation

import re
from dataclasses import dataclass
from typing import Optional

@dataclass
class OperatorIdentity:
    """IAP-FIN operator identification using LEI"""

    lei: str  # Legal Entity Identifier (ISO 17442)
    vlei_credential: Optional[str] = None  # vLEI digital credential
    registration_authority: Optional[str] = None  # MIC for venues

    def __post_init__(self):
        if not self._validate_lei(self.lei):
            raise ValueError(f"Invalid LEI format: {self.lei}")

    @staticmethod
    def _validate_lei(lei: str) -> bool:
        """Validate LEI format (ISO 17442)"""

        # LEI: 20 characters, alphanumeric
        # Format: LLLLLLLLLLLLLLLLLLCC
        # First 4: LOU prefix
        # Next 14: Entity-specific
        # Last 2: Check digits

        if not re.match(r'^[A-Z0-9]{20}$', lei):
            return False

        # ISO 7064 Mod 97-10 check digit validation
        lei_numeric = ''
        for char in lei:
            if char.isdigit():
                lei_numeric += char
            else:
                lei_numeric += str(ord(char) - 55)  # A=10, B=11, etc.

        return int(lei_numeric) % 97 == 1

    def to_dict(self) -> dict:
        return {
            "lei": self.lei,
            "vlei_credential": self.vlei_credential,
            "registration_authority": self.registration_authority
        }


# Example usage
operator = OperatorIdentity(
    lei="5493001KJTIIGC8Y1R12",  # Example LEI
    registration_authority="XNAS"  # NASDAQ MIC
)

---

Subsector Profiles: One Size Doesn't Fit All

Capital Markets Profile

The most demanding profile—HFT algorithmic trading requires:

from dataclasses import dataclass
from typing import List, Optional
from enum import Enum

class OrderSide(Enum):
    BUY = "BUY"
    SELL = "SELL"


class OrderType(Enum):
    MARKET = "MARKET"
    LIMIT = "LIMIT"
    STOP = "STOP"
    ICEBERG = "ICEBERG"


@dataclass
class CapitalMarketsEvent:
    """IAP-FIN Capital Markets subsector event"""

    # Base IAP-FIN fields
    event_id: str
    timestamp: IAPTimestamp  # Tier 1 or 2 required
    model_id: str
    model_version: str
    model_hash: str
    operator_lei: str

    # Capital Markets specific
    event_type: str  # SIG, ORD, ACK, EXE, REJ, CXL, MOD
    instrument_isin: str
    venue_mic: str

    # Order details (when applicable)
    order_id: Optional[str] = None
    client_order_id: Optional[str] = None
    side: Optional[OrderSide] = None
    order_type: Optional[OrderType] = None
    quantity: Optional[float] = None
    price: Optional[float] = None

    # Execution details (when applicable)
    execution_id: Optional[str] = None
    executed_quantity: Optional[float] = None
    executed_price: Optional[float] = None

    # Decision provenance
    signal_factors: Optional[List[str]] = None
    confidence_score: Optional[float] = None
    risk_check_results: Optional[dict] = None

    # Best execution (MiFID II)
    best_execution_factors: Optional[dict] = None

    def validate_mifid_compliance(self) -> List[str]:
        """Validate MiFID II RTS 25 compliance"""

        issues = []

        # Timestamp precision
        if self.timestamp.precision_tier not in [
            PrecisionTier.TIER_1_MICROSECOND,
            PrecisionTier.TIER_2_MILLISECOND
        ]:
            issues.append("Timestamp precision insufficient for MiFID II")

        # Required fields for order events
        if self.event_type in ["ORD", "ACK", "EXE", "MOD", "CXL"]:
            if not self.order_id:
                issues.append("Order ID required for order lifecycle events")
            if not self.instrument_isin:
                issues.append("ISIN required for all orders")
            if not self.venue_mic:
                issues.append("MIC required for venue identification")

        return issues

Banking Profile: Credit Decisioning

Credit models have different requirements—lower timestamp precision, but stricter explainability:

@dataclass
class CreditDecisionEvent:
    """IAP-FIN Banking subsector - Credit Decision"""

    # Base IAP-FIN fields
    event_id: str
    timestamp: IAPTimestamp  # Tier 3 sufficient
    model_id: str
    model_version: str
    operator_lei: str

    # Credit decision specific
    application_id: str
    decision: str  # APPROVE, DECLINE, REFER

    # CFPB-required explainability
    adverse_action_reasons: Optional[List[str]] = None
    principal_factors: List[dict] = None  # Must be human-readable

    # Fair lending analysis
    protected_class_impact_assessed: bool = False
    less_discriminatory_alternatives_documented: bool = False

    # Model governance
    model_validation_date: str = None
    model_owner: str = None

    def validate_cfpb_compliance(self) -> List[str]:
        """Validate CFPB adverse action requirements"""

        issues = []

        if self.decision == "DECLINE":
            if not self.adverse_action_reasons:
                issues.append(
                    "CFPB requires adverse action reasons for declines"
                )
            if not self.principal_factors:
                issues.append(
                    "Principal factors must be documented (no black-box exception)"
                )

        if not self.less_discriminatory_alternatives_documented:
            issues.append(
                "LDA analysis must be documented per CFPB guidance"
            )

        return issues

Insurance Profile: Actuarial Models

Insurance operates on longer cycles with different provenance needs:

@dataclass  
class ActuarialModelEvent:
    """IAP-FIN Insurance subsector - Actuarial Model"""

    # Base IAP-FIN fields
    event_id: str
    timestamp: IAPTimestamp  # Tier 4 (daily) sufficient
    model_id: str
    model_version: str
    operator_lei: str

    # Insurance specific
    model_type: str  # PRICING, RESERVING, CAPITAL, CLAIMS
    line_of_business: str

    # Solvency II requirements
    use_test_documented: bool = False  # Model "widely used" in governance
    model_limitation_adjustments: List[dict] = None
    validation_date: str = None

    # IFRS 17 lineage
    source_systems: List[str] = None
    transformations_applied: List[str] = None
    contract_boundary_applied: bool = False

    # UK Solvency II divergence
    cro_attestation_date: Optional[str] = None

---

Extension Mechanism: FIX Protocol Pattern

IAP-FIN adopts the FIX Protocol reserved field range pattern for extensibility:

Range	Purpose	Governance
1000-4999	Base specification fields	VSO Technical Committee
5000-7999	Industry-wide extensions	Public RFC process
8000-8999	Jurisdictional regulatory extensions	Regulatory working groups
9000-9999	Proprietary extensions	No governance required

Example: Adding a Jurisdiction-Specific Field

# EU AI Act requires logging of "human verification actions"
# This is a jurisdictional extension (8000-8999 range)

EU_AI_ACT_HUMAN_VERIFICATION = 8001

@dataclass
class JurisdictionalExtension:
    """Jurisdictional extension for EU AI Act compliance"""

    field_id: int = EU_AI_ACT_HUMAN_VERIFICATION
    jurisdiction: str = "EU"
    regulation: str = "EU_AI_ACT_ART_12"

    # Extension data
    human_verification_performed: bool = False
    verifier_id: Optional[str] = None
    verification_timestamp: Optional[int] = None
    verification_outcome: Optional[str] = None  # APPROVED, REJECTED, MODIFIED

---

Cryptographic Requirements: FIPS 140-3 Compliant

IAP-FIN specifies cryptographic requirements aligned with FIPS 140-3 and PCI DSS 4.0.1:

Algorithm Requirements

Purpose	Algorithm	Minimum Strength	Standard
Hashing	SHA-256+	256-bit	FIPS 180-4
Signing	Ed25519 or RSA-2048	128-bit equivalent	FIPS 186-5
Encryption (at rest)	AES-256	256-bit	FIPS 197
Transport	TLS 1.2+	112-bit	PCI DSS 4.0.1

Key Management

from dataclasses import dataclass
from typing import Optional
from enum import Enum

class KeyStorage(Enum):
    HSM = "HSM"  # Hardware Security Module (recommended)
    SOFTWARE = "SOFTWARE"  # Software keystore
    CLOUD_KMS = "CLOUD_KMS"  # Cloud key management


@dataclass
class CryptoConfig:
    """IAP-FIN cryptographic configuration"""

    hash_algorithm: str = "SHA3-256"
    signature_algorithm: str = "Ed25519"
    key_storage: KeyStorage = KeyStorage.HSM

    # FIPS 140-3 compliance
    fips_module_validated: bool = True
    fips_security_level: int = 3  # Level 3 for most financial services

    # Key rotation
    signature_key_rotation_days: int = 365
    encryption_key_rotation_days: int = 90

    def validate_fips_compliance(self) -> bool:
        """Validate FIPS 140-3 compliance"""

        approved_hash = self.hash_algorithm in [
            "SHA-256", "SHA-384", "SHA-512",
            "SHA3-256", "SHA3-384", "SHA3-512"
        ]

        approved_signature = self.signature_algorithm in [
            "Ed25519", "RSA-2048", "RSA-3072", "RSA-4096",
            "ECDSA-P256", "ECDSA-P384"
        ]

        return (
            approved_hash and 
            approved_signature and 
            self.fips_module_validated
        )

---

Retention Policies: WORM Compliance

SEC Rule 17a-4 requires WORM (Write Once Read Many) storage. IAP-FIN supports configurable retention with jurisdiction-specific defaults:

from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import Optional
from enum import Enum

class RetentionJurisdiction(Enum):
    EU_MIFID = "EU_MIFID"  # 5 years, extendable to 7
    US_SEC = "US_SEC"      # 6 years, first 2 easily accessible
    UK_FCA = "UK_FCA"      # 6 years
    SG_MAS = "SG_MAS"      # 5 years
    AU_ASIC = "AU_ASIC"    # 7 years


class StorageType(Enum):
    WORM = "WORM"          # Write Once Read Many (SEC 17a-4)
    IMMUTABLE = "IMMUTABLE"  # Cloud immutable storage
    STANDARD = "STANDARD"   # Standard storage (non-US)


@dataclass
class RetentionPolicy:
    """IAP-FIN data retention policy"""

    jurisdiction: RetentionJurisdiction
    retention_years: int
    storage_type: StorageType

    # Accessibility requirements
    immediate_access_years: int = 2  # SEC requires 2 years readily accessible

    # Extension handling
    regulatory_extension_possible: bool = True
    max_extension_years: int = 2

    @classmethod
    def for_jurisdiction(cls, jurisdiction: RetentionJurisdiction) -> "RetentionPolicy":
        """Create policy for specific jurisdiction"""

        configs = {
            RetentionJurisdiction.EU_MIFID: {
                "retention_years": 5,
                "storage_type": StorageType.IMMUTABLE,
                "max_extension_years": 2
            },
            RetentionJurisdiction.US_SEC: {
                "retention_years": 6,
                "storage_type": StorageType.WORM,
                "immediate_access_years": 2
            },
            RetentionJurisdiction.UK_FCA: {
                "retention_years": 6,
                "storage_type": StorageType.IMMUTABLE
            },
            RetentionJurisdiction.SG_MAS: {
                "retention_years": 5,
                "storage_type": StorageType.STANDARD
            },
            RetentionJurisdiction.AU_ASIC: {
                "retention_years": 7,
                "storage_type": StorageType.STANDARD
            }
        }

        config = configs[jurisdiction]
        return cls(jurisdiction=jurisdiction, **config)

    def calculate_deletion_date(self, event_date: datetime) -> datetime:
        """Calculate when data can be deleted"""
        return event_date + timedelta(days=self.retention_years * 365)

    def is_in_immediate_access_period(self, event_date: datetime) -> bool:
        """Check if data must be immediately accessible"""
        cutoff = datetime.utcnow() - timedelta(days=self.immediate_access_years * 365)
        return event_date > cutoff


# Multi-jurisdictional: use the strictest requirements
def combined_retention_policy(
    jurisdictions: list[RetentionJurisdiction]
) -> RetentionPolicy:
    """Combine policies to satisfy all jurisdictions"""

    policies = [RetentionPolicy.for_jurisdiction(j) for j in jurisdictions]

    return RetentionPolicy(
        jurisdiction=jurisdictions[0],  # Primary
        retention_years=max(p.retention_years for p in policies),
        storage_type=StorageType.WORM if any(
            p.storage_type == StorageType.WORM for p in policies
        ) else StorageType.IMMUTABLE,
        immediate_access_years=max(p.immediate_access_years for p in policies)
    )


# Example: US broker-dealer with EU operations
policy = combined_retention_policy([
    RetentionJurisdiction.US_SEC,
    RetentionJurisdiction.EU_MIFID
])
# Result: 6 years, WORM storage, 2 years immediate access

---

Complete Event Schema

Here's a complete IAP-FIN event combining all components:

{
  "iap_fin_version": "1.0",
  "conformance_level": "CAPITAL_MARKETS",

  "event": {
    "event_id": "019400a2-7e5c-7000-8000-1a2b3c4d5e6f",
    "event_type": "SIGNAL_GENERATED",

    "timestamp": {
      "utc_ns": 1734432600123456789,
      "precision_tier": "T1",
      "clock_source": "PTP",
      "uncertainty_ns": 50,
      "sync_status": "LOCKED"
    },

    "operator": {
      "lei": "5493001KJTIIGC8Y1R12",
      "vlei_credential": "base64...",
      "registration_authority": "XNAS"
    },

    "model": {
      "model_id": "alpha_momentum_v3",
      "model_version": "3.2.1",
      "model_hash": "sha3-256:8f14e45f...",
      "model_owner": "quant_desk_ny",
      "last_validation_date": "2025-06-15"
    },

    "provenance": {
      "input_hash": "sha3-256:2c26b46b...",
      "input_sources": [
        "market_data:XNAS:2025-12-17T10:30:00Z",
        "risk_params:v4.1"
      ],
      "decision": {
        "action": "GENERATE_BUY_SIGNAL",
        "instrument_isin": "US0378331005",
        "target_quantity": 1000,
        "confidence": 0.87
      },
      "factors": [
        {"name": "momentum_20d", "contribution": 0.45},
        {"name": "volume_breakout", "contribution": 0.32},
        {"name": "sector_correlation", "contribution": 0.23}
      ]
    },

    "risk_checks": {
      "pre_trade_risk_passed": true,
      "position_limit_check": "PASS",
      "concentration_check": "PASS",
      "kill_switch_active": false
    },

    "integrity": {
      "prev_hash": "sha3-256:genesis...",
      "signature": "ed25519:base64...",
      "signer_key_id": "key_2025_001"
    }
  },

  "jurisdictional_extensions": {
    "8001_eu_ai_act_human_oversight": {
      "human_verification_required": false,
      "automated_decision": true
    }
  },

  "retention": {
    "policy_id": "MULTI_US_EU",
    "retention_years": 6,
    "storage_type": "WORM",
    "deletion_eligible_date": "2031-12-17"
  }
}

---

Regulatory Compliance Mapping

IAP-FIN includes non-normative annexes mapping fields to specific regulatory requirements:

EU AI Act Article 12 Mapping

Requirement	IAP-FIN Field
Period of use logging	timestamp.utc_ns
Reference database used	provenance.input_sources
Input data	provenance.input_hash
Human verification	jurisdictional_extensions.8001_*

MiFID II RTS 25 Mapping

Requirement	IAP-FIN Field
Timestamp (100μs accuracy)	timestamp (Tier 1)
Algorithm identifier	model.model_id
Instrument identification	provenance.decision.instrument_isin
Trading venue	operator.registration_authority

SEC Rule 17a-4 Mapping

Requirement	IAP-FIN Field
6-year retention	retention.retention_years
WORM storage	retention.storage_type
2-year accessibility	retention.immediate_access_years

Federal Reserve SR 11-7 Mapping

Requirement	IAP-FIN Field
Model documentation	model.*
Validation dates	model.last_validation_date
Inputs and outputs	provenance.*
Responsible individuals	model.model_owner

---

Why IAP-FIN Matters

For Financial Institutions

• One implementation satisfies multiple regulators
• Auditor-friendly format reduces examination friction
• Future-proof architecture handles regulatory evolution

For Regulators

• Standardized format enables efficient review
• Cryptographic verification provides confidence in data integrity
• Cross-border consistency simplifies international coordination

For Auditors

• Common schema across clients
• Machine-processable validation rules
• Clear compliance mapping to authoritative requirements

For the Industry

• Reduced duplication of compliance effort
• Vendor interoperability for RegTech solutions
• Open standard prevents lock-in

---

Get Involved

IAP-FIN is under development. We're seeking input from:

• Compliance officers at banks, asset managers, and broker-dealers
• Quantitative developers building algorithmic trading systems
• RegTech vendors building compliance solutions
• Regulators interested in standardization

Resources

• 🌐 Website: veritaschain.org
• 📦 GitHub: github.com/veritaschain
• 📧 Standards: [e-mail]
• 📧 Enterprise: [e-mail]

---

Final Thought

The financial industry spends nearly $10 billion annually on regulatory technology. Much of that goes toward solving the same problem in slightly different ways at thousands of institutions.

IAP-FIN doesn't replace existing systems—it provides a common output format that any system can generate. One format that satisfies MiFID II, EU AI Act, SEC, CFTC, FCA, MAS, and APRA. One format that auditors can verify. One format that regulators can trust.

The alternative is what we have today: proprietary formats, inconsistent logs, and a €35 million question that nobody can confidently answer.

---

"Encoding Trust in Financial Services AI"

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About IAP-FIN: VAP-IAP-FIN-001 (Industry Application Profile for Financial Services) is part of the VAP (Verifiable AI Provenance) framework, maintained by the VeritasChain Standards Organization (VSO). VCP (VeritasChain Protocol), the algorithmic trading specification, is already in production. IAP-FIN extends VCP with comprehensive subsector and jurisdictional support. The specification is open source under CC BY 4.0.