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CRRR – Cygnet Regulatory Requirements Repository

Transforming regulatory requirements from documents into structured, reusable knowledge.


1. Introduction

The Cygnet Regulatory Requirements Repository (CRRR) is a knowledge management platform designed to capture, organize, maintain, and distribute regulatory reporting requirements in a structured and machine-readable format.

CRRR serves as the authoritative source of regulatory reporting knowledge within the Cygnet ecosystem.

Rather than treating regulations as static PDF documents, CRRR converts regulatory requirements into reusable metadata assets that can drive implementation, validation, testing, documentation, and reporting processes.


2. Why CRRR Exists

Financial institutions face a common challenge:

Regulators publish requirements as documents.

Systems require requirements as data.

Between those two worlds lies a significant amount of manual interpretation.

Teams must repeatedly answer questions such as:

  • What exactly does this field mean?
  • Which source systems provide the data?
  • How is this value calculated?
  • Which validation rules apply?
  • What changed from the previous version?
  • Which reports are impacted?

The same analysis is often repeated by:

  • Business Analysts
  • Data Architects
  • Developers
  • Testers
  • Data Governance teams
  • Regulators
  • External consultants

CRRR was created to eliminate this duplication of effort.


3. Vision

Our vision is:

Every regulatory requirement should exist as structured knowledge rather than unstructured documentation.

Once regulatory requirements become structured knowledge, they can be:

  • Queried
  • Validated
  • Compared
  • Versioned
  • Visualized
  • Automated
  • Reused

4. Core Philosophy

CRRR is built around five principles.

Regulatory Knowledge as an Asset

Regulatory interpretation is intellectual property.

The accumulated understanding of reporting requirements represents a valuable asset that should be preserved and continuously improved.


Single Source of Truth

Every regulatory requirement should have one authoritative definition.

This prevents conflicting interpretations across teams and projects.


Traceability

Every requirement should be traceable back to:

  • Regulatory publications
  • Circular letters
  • Guidelines
  • Business interpretations
  • Implementation decisions

Version Awareness

Regulations change constantly.

CRRR preserves historical versions and provides visibility into what changed and why.


Machine Readability

Regulatory requirements should be stored in a format that can be consumed by software.

This enables automation and integration with downstream systems.


5. What CRRR Contains

CRRR captures multiple layers of regulatory knowledge.


Regulatory Publications

Examples include:

  • PADG
  • PBI
  • SEOJK
  • POJK
  • Technical Guidelines
  • Reporting Manuals

Each publication is stored with:

  • Identifier
  • Publication date
  • Effective date
  • Superseded versions
  • Regulatory authority

Reporting Forms

Examples:

  • ADB01
  • KRP01
  • TAB01
  • GIR01
  • DEP01
  • F01
  • D01
  • D02

Each form contains:

  • Form metadata
  • Reporting frequency
  • Submission deadlines
  • Ownership information

Data Elements

Each reporting field is captured as an individual metadata object.

Examples:

  • Customer ID
  • Outstanding Balance
  • Credit Quality
  • Currency Code

Attributes include:

  • Business definition
  • Technical definition
  • Data type
  • Mandatory status
  • Reference codes
  • Source lineage

Business Definitions

CRRR records the business meaning of data elements.

This includes:

  • Regulatory interpretation
  • Industry interpretation
  • Institution-specific implementation notes

Reference Data

Examples:

  • Currency Codes
  • Sector Codes
  • Product Codes
  • Economic Activity Codes

Validation Requirements

Validation requirements define reporting expectations.

Examples:

  • Mandatory fields
  • Range checks
  • Domain checks
  • Cross-field validations
  • Cross-form validations

These requirements may later be transformed into executable assets by CDAP.


6. Relationship with RRDF

CRRR answers:

What information does the regulator require?

RRDF answers:

How should that information be represented in a canonical data model?

Example:

CRRR may define:

"Outstanding Financing Amount"

RRDF defines:

  • Entity
  • Attribute
  • Data type
  • Relationships

between the regulatory concept and enterprise data structures.


7. Relationship with CDAP

CRRR provides regulatory requirements.

CDAP transforms requirements into executable compliance assets.

Examples:

CRRR stores:

  • Rule description
  • Business intent
  • Regulatory source

CDAP generates:

  • Great Expectations rules
  • SQL validations
  • Test cases
  • Data quality checks

CRRR defines the requirement.

CDAP operationalizes the requirement.


8. Relationship with CRRS

CRRS is the operational reporting platform.

CRRR provides the knowledge used by CRRS.

Examples:

CRRR defines:

  • Form structure
  • Reporting fields
  • Submission rules

CRRS executes:

  • Data extraction
  • Transformation
  • Validation
  • Report generation
  • Submission

9. Current Scope

The initial implementation focuses on Indonesian regulatory reporting.

Priority areas include:

Bank Indonesia

Examples:

  • Antasena
  • Commercial Bank Reporting
  • Prudential Reporting

OJK

Examples:

  • SLIK
  • Risk Reporting
  • Governance Reporting

Internal Regulatory Metadata

Including:

  • Field definitions
  • Reporting mappings
  • Rule catalogues
  • Reference datasets

10. Target Information Model

id="b5u12z" Regulator | +-- Publication | +-- Reporting Framework | +-- Form | +-- Section | +-- Data Element | +-- Business Definition | +-- Validation Requirement | +-- Reference Data


11. Future Direction

Future enhancements may include:

Regulatory Change Management

Automatically identify differences between regulation versions.


Impact Analysis

Determine:

  • Affected forms
  • Affected systems
  • Affected validations
  • Affected data models

AI-Assisted Interpretation

Support analysts in understanding regulatory changes.


Regulatory Knowledge Graph

Connect:

  • Regulations
  • Reports
  • Fields
  • Rules
  • Data Models
  • Source Systems

through a navigable knowledge graph.


Multi-Jurisdiction Support

Expand beyond Indonesia to support regional and international reporting frameworks.


12. Long-Term Vision

The long-term vision of CRRR is to become the authoritative repository of regulatory reporting knowledge.

In this model:

  • CRRR manages knowledge.
  • RRDF manages data structures.
  • CDAP manages compliance assets.
  • CRRS manages execution.

Together they create a complete regulatory intelligence platform.


13. Project Motto

Capture Once. Reuse Forever.

CRRR transforms regulatory requirements from static documents into living knowledge assets that can be shared across teams, systems, and generations of technology.