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Banking verified Verified Outcome TRL 9

Trading Investment Data Fabric

domain Client: A Danish investment bank handshake Provider: Snowflake / Confluent schedule Deploy: Q2 2021 (Scale)
90 Impact
Enterprise Ready
Evidence Score: 4/10
Strength: Medium

Executive Summary

ANALYST: COI RESEARCH

The bank implemented a Data Mesh to support its 'Banking-as-a-Service' (BaaS) model. By treating trading data as a product, they enable white-label partners to consume real-time trade/position data via governed APIs. This turned internal data infrastructure into an external revenue driver.

rate_review Analyst Verdict

"Monetization of the Data Mesh. Most meshes are internal; this one supports external partners. It demonstrates how clean, governed data products can be directly exposed to clients (B2B2C) to create sticky ecosystem value."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

The bank supports hundreds of white-label partners (other banks, brokers). Providing them with timely data on their end-users' trading activity was difficult via batch files. The central data team was a bottleneck for onboarding new partners.

psychology The Solution

Adopted a Data Mesh with Snowflake and Kafka. Trading domains publish real-time events. A governance layer creates 'Partner Data Products' that securely filter data for each white-label client. Partners consume this via APIs or direct data sharing.

settings_suggest Technical & Deployment Specs

Integrations
Trading Engine, Snowflake Data Sharing
Deployment Model
Public Cloud
Data Classification
Financial Trading
Estimated TCO / ROI
High
POC Summary (2019-01-01 to 2020-01-01)

"N/A"

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Data Leakage Critical Strict row-level security policies in Snowflake.
Latency Low Streaming-first architecture.

trending_up Impact Trajectory

Audited value realization curve

Real-time data sharing with >100 partners Verified Outcome
Primary KPIReduction in partner support tickets
Audit CycleIncrease in BaaS revenue

policy Compliance & Gov

  • Standards: MiFID II, GDPR
  • Maturity (TRL): 9
  • Evidence Score: 4/10
  • Data Class: Financial Trading

folder_shared Verified Assets

description
Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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The "Blind Verification" Protocol

How we verified these outcomes for A Danish investment bank without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-906
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-906

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