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Every bank wants AI. Few can trust the data beneath it.

Regulators demand you prove where every number comes from. AI demands clean, governed, real-time data. Both are blocked by the same thing - fragmented legacy cores and data scattered across products. KPI Partners builds the governed, real-time foundation that satisfies the regulator and powers the model.

Regulatory Reporting GenAI Copilots Core Modernization Model Governance Data Lineage Risk Data Aggregation Real-Time Fraud Customer 360 AML / KYC Credit Risk
Banks hold more data than almost anyone,
 and trust less of it than they should.
 
Regulators demand accurate, traceable risk data on demand. AI demands clean, governed, real-time data.
Most banks can do neither at speed - because the data sits fragmented across legacy cores and products.
 
 
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Five things standing between you and trusted, AI-ready data

 

None of these are new. Each one becomes more expensive the moment AI moves from the roadmap to the budget — and the moment a regulator asks you to prove a number.

 

  1. Legacy Core & EDW Lock-In

    Critical data trapped in mainframe cores, Oracle and Teradata estates, and on-prem warehouses, costly to maintain, batch by design, and impossible to scale to real time.

    | No model runs on infrastructure your own teams can't change.

  2. No Single View of Customer or Risk

    Retail, cards, lending, wealth, and payments data sit in separate systems owned by separate teams. There is no enterprise customer 360, and no single, defensible view of risk.

    | AI trained on inconsistent data inherits, and scales, the inconsistency.

  3. Regulatory & Risk-Data Pressure

    BCBS 239, CCAR and stress testing, AML/KYC, fair lending, and model risk (SR 11-7) all demand accurate, traceable data delivered fast. AI raises the bar again — regulators now expect lineage and explainability for model-driven decisions.

    | Ungoverned data turns every AI use case into a compliance liability.

  4. Real-Time Demands, Batch Reality

    Fraud, real-time payments, and customer experience need decisions in the moment. Cores and reporting that run overnight simply cannot keep pace with the way money now moves.

    | A decision made tomorrow on today's fraud is no decision at all.

  5. The Distance From Pilot to Production

    Leadership wants GenAI copilots, real-time fraud models, and smarter credit decisions. Without a clean, unified, governed foundation, these stay perpetual pilots that never reach the customer.

    | The gap between a demo and an operating capability is the data layer.

A path to trusted, AI-ready data-built in the right order 
 
KPI Partners is a data, analytics, and AI consultancy with deep cloud alliances. For banking, we sequence the work so each layer compounds: modernize the foundation, make data self-service, put AI into production, and govern it all to the standard regulators demand. 
 
 

Move critical data off mainframe cores, Oracle, Teradata, and on-prem warehouses onto modern, cloud-native foundations - unifying customer, risk, and finance data along the way.

  • Mainframe and legacy core data offload

  • Oracle, Teradata & on-prem EDW migration

  • Cloud Lakehouse on Azure, AWS, Snowflake, Databricks

  • Real-time ingestion and streaming pipelines

  • Customer & risk data unification

What a trusted foundation unlocks

Each of these depends on the same thing: clean, unified, governed, real-time data.

Build the foundation once, and the use cases stop being pilots.

 

 

From fragmented systems to data you can defend.

The following are illustrative scenarios that reflect common banking engagements.

They are masked and do not depict specific named clients.

 

 

From any legacy estate to a governed, AI-ready platform

A suite of migration and analytics accelerators for all your modernization needs - moving core, risk, and customer data off legacy

systems onto the cloud platforms that AI runs on, and pre-building the risk, fraud, and customer analytics on top.

 

 

Core systems, data warehouses, and ETL - migrated and unified, with logic and lineage preserved.

Source - migrate from

Core Banking / Mainframe Oracle (EBS / Exadata) Teradata Netezza IBM Db2 Hadoop / On-Prem EDW SQL Server SAP Informatica IBM DataStage SSIS Azure Data Factory

Target - migrate to

Google BigQuery Vertex AI Databricks Snowflake Microsoft Fabric dbt AWS Data Platform

Legacy risk, finance, and regulatory reporting modernized - automated conversion at scale.

Source - migrate from

OBIEE / OAC IBM Cognos MicroStrategy SSRS SAP Crystal Reports Tableau SAP BusinessObjects

Target - migrate to

Power BI Looker Azure OpenAI / Copilots Tableau (modern)

Can you prove your numbers - and power your AI?

 

Two fast ways to find out where you stand.

 

Whether you're modernizing a legacy core or trying to put AI into production, KPI Partners offers focused, low-risk engagements built for the regulatory complexity of banking.

 

 

Data & AI Readiness Assessment (2 Weeks)
A clear-eyed look at how your customer, risk, and finance data connect today, where the trust gap sits, and a roadmap to a governed, real-time
 
 
Risk Data Aggregation & BCBS 239 Review
Assess your risk-data lineage, aggregation, and reporting against regulatory expectations, with a remediation roadmap.
 
 
Core & EDW Modernization Assessment 
Evaluate your legacy core and warehouse estate, rationalize the report inventory, and receive a migration plan with accelerator recommendations.
 
 
GenAI & Real-Time Readiness 
Determine whether your data foundation can safely support real-time fraud models and GenAI copilots - before you build on it.
 

Standard Enterprise

AI Engagement Model

 

AI Engagement Model

 

Data Platform Migration for Modern Analytics

 

KPI DataBridge Suite is designed to help enterprises modernize their data and analytics infrastructure across:
 
BI Modernization 🔗
Data Platform Migration 🔗
Data Products 🔗

 

Group 3

 

Explore Real-World
Data Platform Migration Case Studies

 


 

BI Platform Migration

GenAI Accelerators

Databricks Accelerators

4 Infrastructure Optimizer
5 Databricks Unity Catalog Enablement
Description Text is Optional
6 Data Quality Validator for Databricks
Description Text is Optional

Snowflake Accelerators

2 Oracle / SQL Server to Snowflake Migration
3 Snowflake Cost Optimization App
4 Snowflake Security Automation App
5 Snowflake Data Governance App
Description Text is Optional
6 Data Quality Validator for Snowflake
Description Text is Optional
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