As fintech transforms, cybercrime will also be another priority for providers (for example, 20,000 customers of Tesco Bank lost money in their accounts in one weekend alone). As new regulations take effect and the promise of open APIs, security will become even more important -- some predict that 30 percent of banking work will be automated in the next few years. 2. Medical Technology The biggest question for medtech is how augmented reality and machine learning can bring real meaningful improvements to healthcare, not just the average user experience in mobile health apps (in 2015 alone, 32% of mobile phone users have downloaded a healthcare or fitness app). AI tools are used in more or less all areas of healthcare as it promises to ease the workload of medical professionals.
Algorithms for better diagnosis – algorithms that can spot DNA mutations in tumors, predict heart attacks, and diagnose skin telemarketing list cancer and other diseases; Advanced patient care – developing artificial intelligence systems to detect depressive-prone behaviors early and help reduce the occurrence of serious mental illness; Disease Prediction – An echocardiogram produces sound waves to map the heart, helping cardiologists identify whether a patient has heart disease. In the coming years, consumers will be encouraged to interact more with their devices and take more measurements, such as blood sugar monitoring, heart rate monitoring or remote blood pressure monitoring. Putting big data into action could turn healthcare into health predictions — saving us potentially 50% of the global healthcare budget compared to current inefficient processes.
Educational Technology Over the years, the number of educational technology tools has grown significantly due to educators' willingness to embrace new teaching and research methods. Let's take a look at what new technologies are being applied to education: Artificial Intelligence – With the help of artificial intelligence, students become more inspired and motivated in the learning process. Machine learning can personalize teaching by assessing students’ abilities, making teaching content effective and useful for everyone; Augmented reality and virtual reality – immersed in real situations to learn, students can understand and remember knowledge points faster; Learning Analytics – Students leave data on the web about their learning. Educational institutions will conduct user analysis on this to optimize teaching by analyzing their learning behaviors and habits.