Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory concerns. This project seeks to determine a reasonable path forward in technology design and adoption to accommodate current and anticipated infrastructure changes. Moreover, bridging the service layer across multiple, distinct distributed systems of varying complexity will pose new […]

Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory concerns. This project seeks to determine a reasonable path forward in technology design and adoption to accommodate current and anticipated data privacy and data residency concerns, making it possible to keep data within borders while still facilitating collaboration […]

Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory and business concerns. This project seeks to define a technology infrastructure design that supports current and anticipated data privacy and data residency concerns, making it possible to keep data within borders while still facilitating collaboration across those borders. […]

The objective of the project is to investigate how machine learning techniques can be used to detect anomalies in volumes of transactions. This requires the student to conduct a literature review about the topic as well as experimenting with a subset of selected machine learning techniques. The results from the research could help the partner […]

Within a tiered or zoned architecture, new business constraints for regional data residency, imply a need for new architectural patterns. These constraints are not arbitrary: they arise directly from customers demand to ensure their confidential data stays within their defined borders unless required otherwise (e.g. data originating in the U.S. is intended for an E.U. […]