Many compliance teams in the financial services industry are struggling with limited human resources to oversee the fast-changing electronic communications compliance landscape.
Nearly half (48.5 percent) of C-suite and other executives at organizations that use artificial intelligence (AI) expect to increase AI use for risk management and compliance efforts in the year ahead
Thanks to advancements in Artificial Intelligence (AI) and Machine Learning (ML) in the area of cybersecurity, small businesses and enterprise-level companies can stay focused and maintain a high level of digital trust from their customers while keeping overhead costs in check.
As threats from the cyber and physical realms become increasingly prevalent and complex, enterprise security teams must arm themselves with an integrated approach to security operations—one that incorporates cybersecurity, physical security and advanced technologies such as artificial intelligence (AI) and machine learning.
The under-representation of women and people of color across the field of artificial intelligence is causing a “diversity crisis” that is contributing to the creation of flawed systems and technology, according to a New York University research center report.
Health and safety incidents have become the leading financial loss drivers for businesses around the globe, with cumulative losses now outstripping the costs of more high-profile disruptions such as cyber-attacks or IT outages.
Technology has advanced at an astonishing rate in the last decade, and the pace is only set to accelerate. Capabilities that seemed impossible only a short time ago will develop extremely quickly, aiding those who see them coming and hindering those who don’t. Developments in smart technology will create new possibilities for organizations of all kinds – but they will also create opportunities for attackers and adversaries by reducing the effectiveness of existing controls. Previously well-protected information will become vulnerable.
Red teaming, or the practice of detecting network and system vulnerabilities by taking an attacker-like approach to system, network or data access, has become a popular cybersecurity testing process across a wide swath of organizations.
