State of video in business report

whitePaper | September 12, 2022

A seamless customer experience has quickly emerged as a critical differentiator for businesses across all industries.1 And the bar is set high – using artificial intelligence (AI) to deliver touches like personalization, gamification and around-the-clock customer support has become an all but everyday expectation for a large number of consumers.

whitePaper | August 26, 2022

Started in 2013, Arya.ai is the first deep learning (DL) startup in India and has been one of the very early adopters to use DL in Financial Institutions. AryaXAI by Arya.ai, a full stack ML Observability platform, offers multiple components - AI explainability, ML monitoring, ML audit and Policy controls, which organisations require beyond simple ML monitoring tools.

whitePaper | July 20, 2022

In recent years, the use of AI in organisations has drastically increased. As a result, lawmakers around the world have been paying close attention to the developments in the field of AI too. While there is no comprehensive legal body in Switzerland and the EU that regulates the use of AI today, there are clear signs that Swiss and European organisations should prepare for stricter regulation.

whitePaper | August 26, 2022

Evolving data centers into intelligent hubs for digitized business processes poses numerous challenges for IT managers. Many organizations are already adopting hybrid IT concepts to make their data center operations more flexible. However, they also have to keep an eye on new requirements such as IoT, AI, blockchain, container technology as well as data security, legal regulations and climate change. How can all this be seamlessly integrated and managed? And, what will matter next for the data center of the future?

whitePaper | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.

whitePaper | August 10, 2020

Digital innovation is happening fast — and there’s no slowing it down. Financial institutions are shifting priorities as third-party apps and services become more prevalent among consumers. Now, staying connected is no longer just an option, it’s critical to achieving success and staying relevant. mx.com | 1 But moving fast isn’t as easy as it sounds. There’s a fine line that financial institutions have to balance when it comes to innovating quickly to give their customers the experiences they’ve come to expect and ensuring their data remains safe and secure. As data sharing and connected integration ecosystems become the new norm, here are three challenges many financial institutions are facing.