BUILDING A SECURE FOUNDATION TO REDUCE CYBER RISK

whitePaper | November 23, 2022

Over the last four decades, the information technology industry has grown from about $50 billion globally in 1980 to more than $4 trillion. During this time, the IT industry has experienced the transition from mainframe computing to minicomputers, to personal computing, to internet computing, and to handheld computing.

whitePaper | March 22, 2023

Artificial intelligence is increasingly becoming a part of our everyday lives, whether at home, in industry or in the public sector. The technology poses risks, but also opens up new opportunities. This presents the institutions in Brussels with the challenge of finding a balance between innovation and regulation for AI in the EU.

whitePaper | June 4, 2021

In this fast-paced and competitive world, the need for speed is vital. This is especially true when it comes to IT and customer service desks. There has been a recent surge of interest in conversational AI platforms that build on all the strengths of AI to help make IT service desks and customer service more efficient.

whitePaper | October 18, 2022

If you have worked in lending for even just the past year, you have already experienced its cyclical nature. Take mortgage lending, for example. Less than a year ago, the main problem facing mortgage originators was how to process high volumes of applications while still observing regulatory compliance and conformance to underwriting policies.

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 | September 12, 2022

Artificial intelligence is currently attracting considerable interest and attention from industry, researchers, governments as well as investors, who are pouring record amounts of money into the development of new machine learning technologies and applications.