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How a US Credit Card Servicer Turned Its Data Into New Product Lines

The client wanted one complete view of its cardholders across every company and card program. Parkar built an enterprise data platform on Azure and Databricks, and the insights from it led to two new product lines.

  • Data strategy
  • Enterprise data platform
  • Cardholder profile
  • Data governance
A person holding a credit card next to an open laptop

The business

Our client is a West Coast-based servicer with more than 1,000 people, running credit card programs for banks and lenders across the US. It handles every step from new accounts to payments and collections. Its mission is to give every cardholder a better experience, and to help its partners grow their programs.

The challenge

Bringing a growing business together

Several companies, several warehouses

Each acquired company brought its own on-premises data warehouse, built around its own card programs and processes.

Many partners

Call center, collections and servicing partners each held part of every cardholder’s history.

A full cardholder profile

Leadership wanted to see each cardholder’s accounts, transactions, payments and service history in one place, and use that view to grow the business.

Ready for AI

The client wanted its data ready for AI when the first use cases came up.

The solution

What we delivered

  1. Strategy and roadmapMonths 1 to 2
  2. Platform and migrationMonths 3 to 9
  3. Cardholder profilesMonths 10 to 12
Data strategy and roadmap
Agreed with leadership, with data sources ranked by business value.
One enterprise platform
Azure and Databricks replaced 5 on-premises data warehouses, moved one at a time while the business kept running.
Every source connected
25 sources, including the acquired companies, every card program, and partner systems for call center, collections and servicing.
Controls built in
Access controls, data quality checks and lineage, so every team knows where each number comes from.
One profile per cardholder
Accounts, transactions, payments and service history together, refreshed daily. Parkar and the client’s teams used the profiles to spot where new products could grow the business.

Results

The outcomes

2

New product lines

Launched, with new offers for existing cardholders, based on what the profiles showed.

40%

Faster reporting

Teams report from one platform with one set of numbers.

6 weeks

To add an acquisition

A newly acquired company’s data joins the platform in about 6 weeks.

Parkar helped us bring every part of our business onto one platform. Two new product lines came out of what we learned from it.

Chief Technology OfficerUS credit card servicing company

What’s next

With the foundation in place, the client plans to add AI in collections and cardholder servicing, built on the same governed data.

Keep reading

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Industry Financial Services Data and AI for banks, lenders and loan servicers. Service Data Engineering Data foundations your business can trust. Case study · Financial services How a US Loan Servicer Is Modernizing Its Platform and Its Data More than 100 older applications moving to a modern loan servicing platform.

Get started

Start with where your data stands.

A two- to three-week Data Readiness Assessment scores your platform, data quality and governance against your analytics and AI priorities, and ends with a ranked plan.

Download a sample report ›
Data Readiness Assessment2 to 3 weeks

Ends with a ranked list of work and clear next steps.

In the first phase
  • One business area on a modern data platform
  • One trusted data set in daily use
  • Governance in place on your first data set

From there we build in stages, starting where the payback is fastest.