Insurance is now ready for an AI-based analytics platform that can help minimize claim costs and improve customers' claims experience. Insurtech and artificial intelligence (AI) have become the new buzz words and mantra in the insurance industry. Creativity and innovation are thriving in Silicon Valley with more than 1,600 technology companies in the insurtech space for underwriting and claims. If you remember, back in the 1990s, experts predicted that if your company was not an internet company, you would not be around for long. That prediction came true, but what about the current prediction that artificial intelligence for claims will change the insurance industry?
Today, we're pleased to announce the private preview of a new AI-powered project from Microsoft's Healthcare NExT initiative which is designed to enable our healthcare partners to easily create intelligent and compliant healthcare virtual assistants and chatbots. These bots are powered by cognitive services and enriched with authoritative medical content, allowing our partners to empower their customers with self-service access to health information, with the goal of improving outcomes and reducing costs. So, if you're using a health bot built by one of our partners as part of our project, you can interact in a personal way, typing or talking in natural language and receiving information to help answer your health-related questions. Our partners, including Aurora Health Care, with 15 hospitals, over 150 clinics and 70 pharmacies throughout eastern Wisconsin and northern Illinois, Premera Blue Cross, the largest health plan in the Pacific Northwest, and UPMC, one of the largest integrated health care delivery networks in the United States, are working with us to build out bots that address a wide range of healthcare-specific questions and use cases. For instance, insurers can build bots that give their customers an easy way to look up the status of a claim and ask questions about benefits and services.
The tech is increasingly becoming ubiquitous across all industries from the automotive industry, fintech, social media, ecommerce to even entertainment. We are living in the age of big data, as increasingly more enterprises invest in AI and machine learning -- a branch of AI which is in its simplest definition is a form of data analysis -- startups are taking notice and disrupting whole industries by employing that tech. With that in mind, here's everything you need to know about the artificial intelligence (AI) and machine learning tech ecosystem in South Africa. There are a large number of South African startups using AI-related technologies in their software solutions. Here below is a list of some of the more well-known startups -- some of which have developed cutting AI solutions, or potentially disruptive technologies using AI.
This year, whiz kid Ke Jie, the world champion of Chinese national pastime GO, was soundly defeated by a computer powered by Artificial Intelligence. Jie described it as a "horrible experience," but it highlighted the tremendous potential AI has in fields such as gaming – and far beyond. One such field is medicine and healthcare, where we are beginning to reap the benefits of technology that has the potential to impact billions of lives around the world. Here are five health-related industries poised to be revolutionized by Artificial Intelligence in 2018. For doctors, analyzing a patient's records – many of which are still handwritten – often involves the time-consuming task of going through a lifetime's history of notes, lab results and prescriptions.
Can two companies merge their way to digital transformation, become a health care and analytics juggernaut and improve outcomes with one $69 billion deal? CVS and Aetna merged in a deal valued at $69 billion. CVS valued Aetna at $207 a share and combines a large pharmacy and retail footprint with pharmacy benefits and insurance. The deal also creates a massive data pool that could lead to more personalized medicine and follow-up and efficiencies. The rough plan is to use CVS' physical and digital footprint to provide more last mile services in healthcare.
The short answer is No. Machine learning is where the traditional Statistical modeling of data meets the algorithmic and computational field of data science. Such statistical modeling has been used for a long time probably since mid 60's or even before to model some real world process. Actuarial modeling in the insurance industry is a good example, where a lot of data about general health, longevity, personal habits are used to model and determine insurance premiums. Statisticians and Actuaries have been doing this unsexy work for modeling for decades with none of the pomp and attention that Machine learning has been getting the last few years. So if Machine learning is mostly about model building then why is there all the recent hoopla?
So, how do companies find ways to address the ever-increasing customer needs? While the adoption of new technologies might have been slower than desired initially, the Indian insurance sector is certainly awakening to its benefits now. Several insurers are now deploying these processes to understand their customers better and for product innovation. Of all these news processes, perhaps artificial intelligence and machine learning are proving to be the most potent! Information overload New data sources like third-party databases, social media activity, internet of things, and more are providing a steady stream of information.
A second wave of automation in banking will increase capacity and free employees to focus on higher-value projects. To capture the opportunity, banks must take a strategic, rather than tactical, approach. Automation is the focus of intense interest in the global banking industry. Many banks are rushing to deploy the latest automation technologies in the hope of delivering the next wave of productivity, cost savings, and improvement in customer experiences. While the results have been mixed thus far, McKinsey expects that early growing pains will ultimately give way to a transformation of banking, with outsized gains for the institutions that master the new capabilities.
But with that promise comes risk – perhaps greater than the risks inherent with all new technologies – that the insurance industry needs to consider. The Financial Stability Board released a detailed report this month on the potential upsides and downsides of AI, most of which align with Novarica's research of the technology. Many of the risks highlighted in the report stem from the increasing reliance financial services companies will have on outside technology companies for key business components. Another source of risk is that the results of AI and machine learning may be too complex for humans to fully understand. As the FSB report puts it, "New trading algorithms based on machine learning may be less predictable than current rule-based applications and may interact in unexpected ways."
Start-up-developed technology is offering'touchless' claims handling to the motor insurance industry through the use of AI-powered photo recognition. Tractable, which already provides the first-wave of its technology to UK insurer Ageas, has today announced the roll out of a new development to its AI system, which will see it able to provide a full estimate repair cost using photos in minutes. The company, which was founded in 2015 and has attracted more than $10 million (£7.5 million) in funding, says that its new'AI Estimating' technology will save time, cut costs, and transform the claims experience on more than 60% of motor claims. The system will streamline the claims process, from First Notification of Loss (FNOL) to an insurer-approved estimate, without the need for human intervention. "Today when you have an accident and you call your insurance company, the process to manage your claim is extremely slow, its expensive and its very manual," Adrien Cohen, chief commercial officer at Tractable, told Insurance Business.