Sharp rise in electronic payment incidents in Australia resulted in substantial customer disruption in 2018.
Sharp rise in electronic payment incidents in Australia resulted in substantial customer disruption in 2018.
The discussion on cybersecurity is being given increased importance in the boardroom as cybercrime goes global and data protection comes to the forefront
Cyber-threats have become increasingly complex, inflicting high monetary and reputational damages to institutions that, despite various measures, are forced to plan “catch up” to the advanced technology of criminals. As regulators expand advisories, the institutions now need stronger multi-layered cyber-resilient initiatives.
Competition is forcing banks to improve the digital experience of their customers. Banks are focused on investing in mobile technologies, data analytics, security and cloud computing.
The Asian Banker’s survey across financial institutions (FIs) in seven countries in Asia reveals emerging trends in cybersecurity risks and fraud, pressing challenges and technology areas prioritised.
Despite economic headwinds, banks leveraged advanced technologies and a customer-centric approaches to drive balanced growth, with customer engagement, financial inclusion, and ecosystem development emerging as key strategies
The popularity of Bank Central Asia reflects a trend of traditional banks embracing digital innovation to meet customer preferences
Financial institutions are swiftly adopting blockchain and cryptocurrencies, catalysing regulatory discussions and heralding a significant shift in the global financial system.
Bank boards globally lack enough technology experts to influence strategy decisions, though North American banks are better at integrating such experts into their boards
The global outage led by the CrowdStrike-Microsoft faulty software update underscores the emerging gaps in resilience, interdependence of systems, vendor concentration, and single points of failure in networks
While leading financial institutions are rapidly integrating GenAI into operations to enhance efficiency, challenges in model reliability, data integrity, and compliance hinder implementation and scalability.