Monday, 17 December 2018
The right technology choices can accelerate success for a cloud born business. This is true for the fintech start-up clearTREND Research. Their solution architecture team knew one of the most important decisions would be the database decision between SQL or NoSQL.
Monday, 10 December 2018
Although it’s not a typical use case for Azure Functions, a single Azure function is all it took to fully implement an end-to-end, real-time, mission-critical data pipeline for a fraud detection scenario. And it was done with a serverless architecture.
Monday, 26 November 2018
We recently published a blog on a fraud detection solution delivered to a banking customer. The solution required complete processing of a streaming pipeline for telemetry data in real-time using a serverless architecture. This blog describes the evaluation process and the decision to use Microsoft Azure Functions.
Monday, 8 October 2018
A single Azure function is all it took to fully implement an end-to-end, real-time, mission critical data pipeline. And it was done with a serverless architecture. Serverless architectures simplify the building, deployment, and management of cloud scale applications.
Thursday, 20 September 2018
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms.
Thursday, 30 August 2018
The future of mobile banking is clear. People love their mobile devices and banks are making big investments to enhance their apps with digital features and capabilities. As mobile banking grows, so does the one aspect about it that can be wrenching for customers and banks, mobile device fraud.
Thursday, 2 August 2018
When you buy an item on a favored website, does the site show you pictures of what others have bought? That’s the result of a recommendation system. Retailers have been building such systems for years, many built using the programming language R.