AvailLogic

Introduction

For major financial institutions, "legacy" is not a dirty word; it is a reality. Our client, a leading European financial group, faced a dilemma: their marketing operations were run by a powerful, but "blind", incumbent marketing execution platform. The bank’s valuable data was fragmented, and the marketing team was stuck in the past, sending generic offers based on simple demographic data.

The client's challenge was unique and highly complex: How could they leverage the power of real-time AI and machine learning *without* replacing the mission-critical legacy platform at the heart of their operations? They needed a "brain" to augment their existing "body."

The Challenge: The "Smart Brain, Dumb Body" Problem

Our initial discovery workshops pinpointed a clear and sophisticated set of challenges:

• The "Black Box" Execution Engine: The core marketing platform was a "black box" that could only execute pre-defined, static `IF-THEN` rules.
• No Real-Time Capability: Marketing was always "after the fact," with data processed in nightly batches, meaning insights were at least 24 hours old.
• Fragmented Data, Dual Requirements: The bank had to process both high-speed streaming data and massive, terabyte-scale historical batch data.
• A "Value-Proof" Mandate: The solution needed to be implemented in phases and prove its value via concrete A/B testing against the old rules.

Our Solution: An AI-Powered "Smart Core" Platform

We proposed and engineered a complete data and AI platform designed specifically to *integrate with* and *augment* the client's legacy engine. Our solution was to build an external "smart core" that would feed real-time intelligence back to the existing platform via an API.

1. The Foundation: The Dual-Channel Data Platform

First, we built a "Big Data Platform" to master the client's dual-velocity data problem, with a streaming channel for real-time data and a batch channel for large-scale historical datasets. This provided a complete analytics ecosystem for exploration, interactive queries, and graph analysis.

2. The "Brain": The Machine Learning (AI) Workbench

This dual-channel platform was built to feed the "brain." We used the massive historical data to train sophisticated AI models, which were then deployed to the real-time streaming engine to score new data in milliseconds. This brain automatically generated over 60 distinct business classifications for transactions and over 100 new predictive customer labels.

3. The "Bridge": The API & Legacy System Integration

The final, critical piece was the bridge back to the client's legacy world. We exposed all these insights via a single, secure, high-speed API. This allowed the marketing team to write powerful, intelligent rules, transforming their capabilities from basic to highly sophisticated, real-time targeting.

The Outcome: A Proven Model for "Augmented" Transformation

The phased project was an unqualified success, making the client's existing systems smarter, faster, and more effective.

• Immediate, Provable Value: The client could immediately run online A/B tests to pit new AI-driven strategies against their old static rules, providing data-backed proof of ROI.
• From Batch to Real-Time: The marketing team was, for the first time, able to identify and act on real-time "Trigger Events," capturing value that was previously lost.
• A New Paradigm: The Common Data Layer: The project served as a successful pilot for a much larger, organisation-wide transformation towards a unified "Common Data Layer."
• Innovation Without Disruption: We demonstrated that the client did not need to replace their core systems to become an AI-driven powerhouse, giving them the best of both worlds.