DECONSTRUCTING DOMAIN-DRIVEN ARCHITECTURE FOR CO-BRANDED CLOUD BANKING PLATFORMS

Ved Bhat

doi:10.5281/zenodo.22908768

Abstract

Bringing a household consumer brand into a retail bank’s card portfolio requires infrastructure that most legacy
banking estates were never designed to support. This paper examines how Barclays addressed that challenge in
delivering the Next Generation Consumer Banking (NGCB) platform for its Amazon co-branded credit card, using
an in-depth case study grounded in the author’s direct delivery experience as the Senior Technical Business
Analyst responsible for the underlying data-mapping work. The central argument is that a domain-driven approach
to data architecture, built on cloud-native infrastructure, is what makes rapid, ecosystem-scale product launches
possible inside a bank still running on legacy rails. The paper traces how disparate legacy source systems — the
Customer System, Debt Manager and PPE — were mapped into four reusable domains (customer, debt/default,
transaction and bureau reporting); how outbound and inbound data exchange with Experian and TransUnion was
standardised; and how the resulting affordability and creditworthiness data was made fit for use in Probability of
Default (PD), Exposure at Default (EAD) and Loss Given Default (LGD) credit-risk models. These findings are
then generalised into a six-step framework that other institutions can adapt, together with the governance and datalineage disciplines needed to scale it safely. The architecture gave Barclays a reusable route into Amazon’s
customer base and left the bank better placed to onboard further ecosystem partnerships without repeating the
heaviest integration work each time. The paper closes with practical recommendations for institutions planning
similar partnerships and an assessment of the approach’s future relevance as regulatory scrutiny of data lineage
and governance continues to increase.

Keywords

domain-driven design, cloud-native architecture, retail banking, co-branded credit cards, credit risk modelling

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