Tech advances coupled with AI can help insurers manage risk, improve underwriting and boost customer experience. In the wake of the pandemic, people have dramatically changed how they live, communicate, work and shop. COVID-19 has also changed how they interact with critical services such as healthcare and insurance. In a time of change and uncertainty, customers are seeking reassurance and easy transitions to the "new normal." Insurers that take advantage of the new data and customer insights this global digital shift has provided can better assess customer claims and applications, and deliver a better experience.
Artificial intelligence (AI) and financial services have only formed a coherent whole for a handful of years. Yet, the role of machine learning and AI-based recommendation has become central to how the finance industry approaches revenue, sales, marketing, security and customer satisfaction. The main reason for this shift in perspective is the emergence of well-adapted tools that allow banks and other actors to harness the full potential of this technology. One such tool is Explainable AI, which bridges the gap between AI and financial services by providing a completely transparent and compliant solution to assist in decision-making processes. Machine learning and algorithm-based technologies are just as promising.
Machine learning can assess the effectiveness of mathematical tools used to predict the movements of financial markets, according to new Cornell research based on the largest dataset ever used in this area. The researchers' model could also predict future market movements, an extraordinarily difficult task because of markets' massive amounts of information and high volatility. "What we were trying to do is bring the power of machine learning techniques to not only evaluate how well our current methods and models work, but also to help us extend these in a way that we never could do without machine learning," said Maureen O'Hara, the Robert W. Purcell Professor of Management at the SC Johnson College of Business. O'Hara is co-author of "Microstructure in the Machine Age," published July 7 in The Review of Financial Studies. Other Cornell co-authors are: David Easley, the Henry Scarborough Professor of Social Science in the College of Arts and Sciences and professor of information science in Computing and Information Science; and Marcos Lopez de Prado, professor of practice in Operations Research and Information Engineering in the College of Engineering and chief information officer of True Positive Technologies.
As the popularity of artificial intelligence waxes and wanes, it feels like we are at a peak. Hardly a day goes by without an organization announcing "a pivot toward AI" or an aspiration to "become AI-driven." Banks and fintechs are using facial recognition to support know-your-customer guidelines; marketing companies are deploying unsupervised learning to capture new consumer insights; and retailers are experimenting with AI-fueled sentiment analysis, natural language processing, and gamification. A close examination of the activities undertaken by these organizations reveals that AI is mainly being used for tactical rather than strategic purposes -- in fact, finding a cohesive long-term AI strategic vision is rare. Even in well-funded companies, AI capabilities are mostly siloed or unevenly distributed.
The pandemic is a severe stress test for the business continuity plans of global corporations. The operators of call centres are playing an important role in meeting that challenge, and it has not been easy. In normal times, if an earthquake hits Bangalore, you can switch capacity to your call centre in Manila. But what do you do when all the call centres around the world that serve your customers are hit – all at the same time? The big outsourcing call centre companies which serve corporate giants have hundreds of thousands of employees, and many of these people are working from home now.
As robots take on an increasingly diverse portfolio of roles, their charging regimen is going wireless. The same tech that enables charging pads to juice up your mobile device is also coming to robots, enabling them to return to base and get more juice without the complex docking procedures required of contact-based charging stations. WiBotic, one of the companies leading the way in industrial wireless charging, which has a special focus on automation technologies like robots and drones, just got a big vote of confidence from the FCC, which granted equipment authorization for WiBotics's high power transmitters and receivers, which provide up to 300 watts of wireless power. It's the first time the FCC has granted approval of this sort of technology for use in mobile robots, drones, and other devices with larger batteries. The coup for the company comes after a successful summer when WiBotic, based in Seattle, raised $5.7 million in Series A funding.
San Diego Supercomputer Center makes high performance computing resources available to researchers via a "condo cluster" model. Many homebuyers have found that the most affordable path to homeownership leads to a condominium, in which the purchaser buys a piece of a much larger building. This same model is in play today in the high performance computing centers at many universities. Under this "condo cluster" model, faculty researchers buy a piece of a much larger HPC system. In a common scenario, researchers use equipment purchase funds from grants or other funding sources to buy compute nodes that are added to the cluster.
Consumers have come to expect personalization in their shopping experiences, whether using online marketplaces such as Amazon and Etsy or mobile apps such as Gilt or Poshmark. Product recommendations, informed by purchase histories and preferred payment methods, are becoming a standard aspect of digital checkout experiences. Online content subscription purchasing experiences are far different from that ideal in practice, however. Magazines, newspapers, television networks and other content providers typically offer more uniform interfaces that may not consider their customers' geographies, content or payment preferences. The standard approach to conversion that has been representative of the digital content ecosystem -- the paywall -- could be on its way to becoming a thing of the past, according to Trevor Kaufman, CEO of New York City-headquartered Software-as-a-Service firm Piano.io,
Managing Partner and Co-Founder of Scale-Up VC, a Silicon Valley venture capital firm based in Palo Alto, California. Experts have warned against its potential misuse. It's now affecting aspects of our lives that many of us never anticipated: healthcare, education, employment and even national security. What could I be talking about? Artificial intelligence, or the "big AI," as I call it.
Modernization of technology can make a significant impact across many parts of the insurance industry, including underwriting, policy administration, and claims. McKinsey research shows that the potential benefits of modernization include a 40 percent reduction in IT cost, a 40 percent increase in operations productivity, more accurate claims handling, and, in some cases, increased gross written premiums and reduced churn. 1 1. Technology modernization is vital, but--given the significant value at stake and the size of the investment--it should be approached with a healthy dose of caution. Indeed, many insurers miss out on the full benefits of the program for several reasons. First, they don't have a clear view of what sort of actions are needed or the impact such actions could have, which may lead them to undersell both the business value at stake and what is needed to capture it. This approach can enhance the customer experience somewhat, but it doesn't address core challenges such as the ability to reconfigure products quickly or scale users rapidly. is all that is needed, only to find that some capabilities (such as rapid product configurations) require modernization of core systems.