Data Management The foundation every other solution depends on.

Operating templates, the dictionary, the discipline.

Templates turn governance from concept into daily habit. They give every step a defined owner, a defined input, a defined output. The instruments below are what make Q-Lana data discipline operational every day, plus a preview of the Q-Lana Master Data Dictionary that anchors the whole framework.

These instruments are not theory. They are refined every quarter through client work. Banks, funds, impact investors. Emerging and developed markets. The previews below show structure and intent. The full versions are scoped and tailored to each institution as part of a Q-Lana engagement.

Operating templates

Six instruments that turn governance into daily practice.

Each template carries a clear purpose, named ownership, and a defined integration point with the rest of the data architecture. Below: the purpose of each, plus a small structural excerpt to show the format. The full templates are configured and shipped as part of a Q-Lana implementation.

Template 01

Data Inventory (per domain)

Captures every key data field for a domain: definition, ownership, system of record, allowed formats, validation rules, SLAs. The single reference for data accountability inside that domain.

Structural excerpt
Field · Definition · Owner · Source system · Allowed format · DQ rule · SLA · Sensitivity
Template 02

Business Glossary

Defines essential business and risk terms (RAF metrics, RAROC, portfolio limits, default events, IFRS 9 stages) so all teams speak the same language. Critical for aligning business and analytics output.

Structural excerpt
Term · Plain-English definition · Calculation formula · Source field(s) · Owner · Approval status
Template 03

Data Quality Rules Catalog

Lists rule identifiers, definitions, owners, and remediation steps. Powers automated DQ scorecards. The institutional record of what "clean" actually means for each domain.

Structural excerpt
Rule ID · Domain · Rule type · Tolerance · Severity · Owner · Remediation step
Template 04

RM Note Template

Standardizes how Relationship Managers record client interactions. Separates facts from opinions, highlights triggers, risks, and agreed actions. Builds the qualitative knowledge base over time.

Structural excerpt
Date · Client ID · Meeting type · Facts · Observations · Risks/triggers · Agreed actions · Owner
Template 05

Consent & Retention Log

Tracks client consent, purpose of data use, lawful basis, retention period, and anonymization plan. The audit-ready record of how the institution handles personal and sensitive data.

Structural excerpt
Client ID · Data category · Lawful basis · Purpose · Retention period · Anonymization date · Renewal trigger
Template 06

EWS Signal Catalog

Defines behavioral and contextual early-warning indicators (DPD streaks, covenant breaches, negative sentiment, sector stress). Links signals to escalation workflows.

Structural excerpt
Signal ID · Trigger condition · Severity tier · Source domain · Escalation path · Cooldown · Owner
The dictionary

The Q-Lana Master Data Dictionary.

The Master Data Dictionary is the canonical definition of every field that can appear in the lending lifecycle on the Q-Lana platform. It exists for three reasons: to give every Q-Lana customer a consistent, defensible data model from day one without forcing them to invent one; to give Q-Lana a single source of truth that downstream code, ETL pipelines, dashboards, and customer documentation are generated from; and to give institutional buyers (CIOs, Chief Data Officers, internal auditors, regulators) a verifiable artifact that demonstrates how the platform handles data. The dictionary is a product. It is built, versioned, and shipped with the same discipline as the platform itself.

Artifact metadata

Q-Lana Master Data Dictionary

Versionv0.1 (Draft)
StatusIn active review
Source formatYAML (canonical)
Generated viewsExcel · Markdown · SQL · API
OwnerQ-Lana Data Architecture
Mapped toBasel III · IFRS 9 · BCBS 239
Reference standardsISO · BIAN · FIBO

Seven design principles

01
Open by default. Published, readable, reviewable. Customers see what they are adopting before they adopt it.
02
Standards-anchored. Every field with a regulatory consumer is mapped to it. Basel III, IFRS 9, BCBS 239 are the primary anchors.
03
Modular adoption. No customer is forced to take the whole dictionary. Per-entity tiers, recommended bundles, extension modules.
04
Extensible without forking. Defined path for adding fields, entities, or domains. Forking the dictionary is never the right answer.
05
Auditable end-to-end. Every field carries lineage, ownership, sensitivity, lifecycle metadata. The dictionary is the BCBS 239 evidence file.
06
Generated, not hand-maintained. YAML is the source of truth. Excel, Markdown, schemas, validation libraries all generated from it.
07
English-stable, locale-aware. Field names are English and stable. Business labels and definitions are translatable.
Sample field excerpt · five rows of two-hundred-plus
Generated from the canonical YAML source
Field Definition Type Owner Regulatory anchor
individual.date_of_birth Date of birth of the natural person; used for age, KYC, and beneficiary checks. date Onboarding KYC / AML
company.legal_name Registered legal name of the entity as recorded in the relevant business registry. string(255) Counterparty mgmt ISO 20022
facility.principal_outstanding Drawn principal owed by the borrower at the reporting reference date, gross of provisions. decimal(18,2) Credit operations Basel III · IFRS 9
collateral.market_value Most recent market valuation of the pledged asset, in the currency of the collateral instrument. decimal(18,2) Collateral mgmt Basel III
covenant_breach.cure_period_days Number of days the borrower has to cure a covenant breach before formal escalation. integer Risk management Internal RAF
YAML excerpt · field record schema (illustrative)
# Sample field definition from the Q-Lana Master Data Dictionary
entity:          facility
field_name:      principal_outstanding
type:            decimal(18,2)
unit:            currency_amount
required:        true
owner:           credit_operations
steward:         facility_data_steward
sensitivity:     internal
regulatory_mapping:
  basel_iii:     "EAD component"
  ifrs_9:        "gross carrying amount"
  bcbs_239:      "P3.5 lineage required"
validation:
  - rule:        non_negative
  - rule:        less_than_or_equal_to.original_principal
# ... full record contains 17 additional metadata fields ...
What you see here is a preview. The full Q-Lana Master Data Dictionary contains over two hundred field records across nine subject areas, with full lineage, validation rule libraries, regulatory mappings, and modular adoption tiers. The complete artifact is shared during a Q-Lana engagement under a defined scoping agreement. Talk to us about a tailored review for your institution.
From the field

Practitioners on the toolkit.

Governance used to be a policy nobody read. Once the templates and the Master Data Dictionary became the single source of truth, every team spoke the same language and the audit trail wrote itself. Discipline finally lived in the tools, not in memos.

Head of Data, regional bank

Across Q-Lana

Related

Three places the Governance Toolkit shows up next.

Why this matters

Discipline lives in the templates.

Strategy decks describe data governance. Templates run it. The six instruments above and the Master Data Dictionary that anchors them turn principles into daily habits. What gets captured. Who owns it. Where it lives. When it expires. The institutions that win are not the ones with the best slides. They are the ones with the best templates.

For CIOs, CDOs, and Heads of Data

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