Data, service quality and analytics should be tailored to use cases, and API models manage use cases independently. This should be more efficient and cost effective than full service, flat file based models.

Data as a Service (DaaS) providers use smart and efficient APIs for delivery, quality assurance and support. Analysing each use case by itself avoids the “one stop shop” problem of one bottleneck delaying multiple deliverables.

Smart APIs include messaging, which prioritises and lets some tasks proceed without holding up everything. In contrast, flat files cannot handle this sort of complexity.

DaaS providers flexibly use APIs to provide bespoke stage 2 transformation and quality assurance. Clients not only retain domain experience and expertise – but also build up this knowledge over time to become versatile enough to handle new products, mergers, and operating models.

Exogenous shocks to the TOM are more easily, efficiently and cost- effectively absorbed using APIs. DaaS provider’s use of APIs creates a happy medium of an initial efficiency, whilst allowing a reasonable level of expertise to grow inside a fund.