Digital banking has come a long way in recent years, and it is likely to continue evolving and improving in the future. Artificial intelligence and machine learning: These technologies can be used to improve the accuracy of fraud detection, make personalized recommendations to customers, and streamline various processes such as loan approval and account opening. Biometric authentication: This technology, which uses unique physical characteristics such as fingerprints, facial recognition, and voice recognition, can improve security and make it easier for customers to access their accounts. Blockchain: This technology, which is the underlying technology behind cryptocurrencies, has the potential to revolutionize financial services by enabling secure, decentralized, and transparent transactions. Open banking: This refers to the practice of allowing third-party developers to build applications and services on top of a bank's infrastructure.

Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. Machine learning (ML) has undergone rapid transformation and adoption in recent years, driven by a number of factors. There is no shortage of opinions about why artificial intelligence (AI) and ML are growing. A recent report from McKinsey identified industrializing ML and applied AI as among its top trends for the year. In a session at the AWS re:Invent conference this week, Bratin Saha, VP and GM of AI and machine learning at Amazon, outlined the six key trends the cloud giant is seeing that are helping to drive innovation and adoption in 2022 and beyond.

From the NEJM Catalyst event AI and Machine Learning for Health Care Delivery, sponsored by Advisory Board, March 24, 2022. In the special artificial intelligence theme issue of NEJM Catalyst Innovations in Care Delivery, "AI Insurance: How Liability Insurance Can Drive the Responsible Adoption of Artificial Intelligence in Health Care" explores how AI liability insurance can mitigate predictable risks and uncertainties to health care AI adoption. The big challenge for health care delivery is overcoming institutional mismatch, according to Stern. "The technologies that have the greatest potential to transform health care delivery --this includes, but is not limited, to AI -- would be unrecognizable to the 20th-century architects of our regulatory and health care delivery institutions," says Stern. "And this problem is getting worse. The pace of innovation that we see today coupled with our rapidly transforming analytical and technological capabilities is increasingly mismatched to our existing institutions."