Success Story Financial Services

Modern Data Analytics Platform Supports Credit Loss & Customer Acquisition Use Cases

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This tech-forward financial services company provides simple, personalized payment, lending, savings, and loyalty solutions to consumers and businesses. These include market-leading private label, co-branded, general purpose and business credit card programs, as well as digital payments.

Apexon began its strategic partnership with the company in 2019. At the time, the company was having difficulty delivering the necessary speed and agility to process and deliver high volumes of data on time for analytical models via its on-prem applications. Apexon’s scope included data strategy, data migration, and data engineering services to help create a simple, efficient platform that would reduce costs and increase revenues for the company. Apexon analyzed multiple use cases and designed and implemented a cloud-based analytical platform to meet the organization’s needs.

  • Tech-forward payment and lending solutions

    Tech-forward payment and lending solutions

  • 8,000+ global associates

    8,000+ global associates

  • $3.38+ annual revenues

    $3.38+ annual revenues in FY 2021

  • Owns and operates loyalty/reward programs for global brands

    Owns and operates loyalty/reward programs for global brands

the Results

Key Outcomes

Scalable & Serverless Architecture
Scalable & Serverless
Architecture

Higher Service Levels
Higher
Service Levels

Reduced Onboarding Time - from 14 days to 3 days
Reduced Onboarding Time
– from 14 days to 3 days

Reusable Data Ingestion Components
Reusable Data
Ingestion Components

Faster Cycle Time
Faster
Cycle Time

Reduced Costs
Reduced
Costs

Our methodology

how
we did it

Infostretch works with companies across the digital lifecycle.

Go Digital
Go Digital

Accelerating the delivery of new digital initiatives with confidence

Be digital
Be digital

Creating the infrastructure and foundation to scale digital initiatives

Evolve Digital
Evolve Digital

Leveraging data and analytics to continuously improve digital delivery processes

Launch & Experiment

Automate & Accelerate

Be Intelligent & Autonomous

Launch & Experiment

Enable digital adoption in a quick, and agile mannertransform the patient experience

Legacy data migration

Apexon defined the data strategy and roadmap:

  • Understanding expectations of different users and stakeholders
  • Defining business and data requirements
  • Evaluating proprietary frameworks for faster data ingestion and processing

Automate & Accelerate

Build digital infrastructure and foundation for enterprises to scaledigitization on patient Experience

New data infrastructure

Apexon helped formalize new delivery processes across the business:

  • 12 weeks to working pilot
  • Detailed source analysis
  • Data ingestion pipeline w/ consumption patterns
  • Data catalog design and roles
  • Conceptual data model mapped to use cases
  • Re-usable POC components
  • Data roadmap informing next 2 – 3 years of development

Be Intelligent & Autonomous

Leverage data engineering to make strategic decisions and get digital right every time

Data analytics to help predict fraud and streamline customer acquisition experiences

Apexon enabled automation to deliver trusted data and faster insights:

  • Self-serve analytics for 200 brand partners to access critical data about their sales and credit card applications
  • Serverless architecture to scale data with core capabilities

The challenge

FASTER DATA ANALYTICS TO SUPPORT CREDIT LOSS & CUSTOMER ACQUISITION

The company had been an early innovator and leader in providing loyalty and marketing services support. They have since repositioned and made acquisitions to add payment and lending solutions to brand marketing and SMB segment. This meant migrating data from legacy platforms to modern data platforms and enabling analytics for quicker insights and improved customer acquisition experience.

The end goal was to minimize fraud and provide trusted data and faster insights. But they faced several obstacles including:

Linear & Siloed Development Efforts

Linear & Siloed
Development Efforts Which hampered the build process and created the need for rework in the later stages

Disparate Tools & Methodologies

Disparate Tools &
Methodologies Used across the organization, creating huge inefficiencies and redundancies

Lack of A Source-Code Management System

Lack of A Source-Code
Management System Resulting in multiple code bases, further slowing development and testing

The Solution

Modern Self-service Data Analytics Platform Delivering Faster Insights

Apexon’s engagement focused on two primary initiatives:

  • Building ML Models

    Enabling a Quick Pilot

  • Building ML Models

    Setting Up an Enterprise Data Platform

The goal was to transform the data analytics landscape to support the business transition organization-wide. At the core of the solution was a faster data curation platform that could deliver high quality data on demand and predict fraud while also providing a seamless customer experience through a self-service portal. Over 14 months, Apexon defined and executed on multiple requirements and use cases including pipeline automations, scalable architecture to transform data based on AI/ML, and a building a semantic layer for ML models.

Some of the other key deliverables included:

Building ML Models

Building ML Models 60% of data ingested (including ~160 3rd party Brand Partner files) with history onto Azure and a semantic layer for building ML models

Analytical Platform

Analytical Platform Self-service “one-stop-shop” analytical platform for over 200 brand partners to access critical data about their sales and credit card application

Serverless Architecture

Serverless Architecture A serverless architecture – compute and storage on demand, data availability at scale with core capabilities

Compliant Data Platform

Compliant Data Platform Enterprise grade compliant data platform delivering trusted data

Onsite-offshore Development Center

Onsite-offshore Development Center Onsite-offshore development center – (USA-India/Hyderabad)

iC4 Proprietary Accelerator

iC4 Proprietary Accelerator Leverage of Apexon’s iC4 proprietary accelerator for faster data curation

KEY AREAS OF PROJECT SCOPE INCLUDE:
Data engineering services

Data Engineering

Apexon re-imagined the underlying data architecture of the company’s platform. This included a scalable, cloud-based data repository and data analytics solution built on Azure and Databricks. Apexon also designed and developed a data ingestion framework with re-usable micro-services and pre-defined ingestion pipelines. In addition, Apexon designed and developed a UI-based portal for configuring and managing metadata of source, target and operational data along with the ingestion pipeline setup thus reducing the ingestion development timeline and eliminating expensive manual efforts and errors.

Data strategy

Data Strategy

Apexon was involved in developing a secure, cloud-based modern data platform for the company including blueprinting, implementation, and agile design and delivery to minimize risk. Apexon also worked with the company to quickly launch new initiatives and validate them through a Minimum Viable Product (MVP) approach in advance of production implementation.

Cloud migration services

Cloud Migration

Apexon proposed the migration of the company’s data assets to Azure cloud from its on-prem databases and Hadoop big-data platform. This included project definition, tool selection, execution, mitigation strategy, execution, testing, and verification. This effort enabled the company to lower infrastructure management costs while increasing database performance and resilience.

KEY results:
Reduced onboarding time for new data sources

Higher Service Levels

Reduced onboarding time for new data sources from 14 days to 3 days enable clients to access data and consume the data for advanced data analytics

Increased Customer Satisfaction

Increased Customer Satisfaction

The enterprise-grade, best-in-class, compliant data platform is set up with automated data management processes to deliver trusted data and faster insights to users

Increased Operational Efficiency

Increased Operational Efficiency

As data is ingested and curated from source systems, individual reusable components can be leveraged independent of one another based on the selected data ingestion design patterns

Scalable & Serverless Architecture

Scalable & Serverless Architecture

To support exponential growth of compute and storage