Tag: AI

The role of AI has ballooned in recent years, and the recent introduction of GenAI platform ChatGPT has seen the sector soar further.

Despite threats posed by the emergence of new technologies such as AI, global business leaders' focus on cyber risk seems to be waning.

Key European AI investment stats in Q2 2023: • European AI FinTech deal activity increased 6% to 38 deals in Q2 2023 from the previous...

With the meteoric rise of SaaS (Software as a Service) applications utilisation by large enterprises, Santa Clara and Bangalore-based Zluri, a robust SaaSOps (SaaS Operations) platform, is stepping up to the plate. They aim to assist companies in managing their expansive SaaS estates and mitigating potential risks.

Emerging from stealth, Vendict, an Israeli technology startup, has broken into the scene, intent on harnessing generative artificial intelligence (AI) to bolster security compliance teams.

Dive into the intricate world of smurfing, a subtle form of money laundering, and learn about the transformative role Flagright's AI-powered tools are playing in combating this malpractice.

House Numbers, an AI-empowered home wealth management platform, has announced its successful pre-seed funding round.

Shinkansen, a burgeoning FinTech start-up hailing from Chile, has recently celebrated the successful closure of a seed investment round.

The FinTech landscape is increasingly gravitating towards perpetual know your customer (KYC) protocols. As part of this evolution, the operational pillars are rapidly transforming. Graham Bailey, COO of Quantifind, and Brian Kindle, VP of product development at ACFCS, shed light on this shifting terrain in a new podcast on the foundational elements of perpetual KYC.

As we move deeper into 2023, AI breakthroughs are dominating the global business landscape. The capabilities of generative systems and large language models have gripped the public's attention, with companies across various sectors investing heavily in these AI-centric technologies. However, the success of these investments heavily relies on the quality of data used to train these systems and the in-house expertise of the organisations implementing them.