In a statement, CLDC says that it will work with Rui Xin to develop a consumer financial platform. CLDC expects to provide value-added consumer financial services to insurance consumers of Rui Xin and its partners. In addition, CLDC and Rui Xin will explore opportunities for collaboration in areas such as insurance consumer acquisition, development of insurance products, expansion of insurance business, and customisation of consumer financial solutions. Moreover, CLDC will benefit from Rui Xin and its partners' advanced technological capabilities in big data and artificial intelligence to improve its risk management and enhance its customer experience. In its turn, Rui Xin will be able to explore new business opportunities and increase its competency to eventually expand its customer base in the insurance industry by benefiting from CLDC's financial service expertise, bank credit facility resources, and client base in certain regional markets.
Along with the hardware and software sectors, the drone services market is the largest segment in the commercial drone industry with the strongest expansion. According to the market research report "Global Drone Service Market Analysis & Trends – Industry Forecast to 2025", the drone services market is estimated at USD 4.4 billion in 2019 and is projected to reach USD 63.6 billion by 2025, at a CAGR of 55.9% from 2019 to 2025. This is a huge opportunity for drone service providers. The key for capturing a share of this growing market is to offer turnkey business solutions beyond data capture, such as mapping, surveying and specialized geospatial analytics. With more and more business relying on location data to optimize their day-to-day operations and planning or gain first-hand market insights.
What a company chooses, determines the pace of its growth. Processes such as underwriting, claims to process, and policy servicing, bring along with them a plethora of important but mundane and repetitive work, affecting the overall organization's efficiency. This is where the need to automate systems and manual processes arise. Robotic process automation (RPA), with the use of software bots to handle routine processes and time-consuming data entry work, is an objective solution for any organization to drive customer-centric strategies and scale up operations. Why is RPA a Good Fit For the Insurance Sector?
One of the biggest problems health plans face is dirty data, says Jordan Bazinsky, executive vice president and administrative officer at Atlanta-based Cotiviti. The healthcare solutions and analytics company reports having "several hundred" health insurance companies among its clientele, including 24 of the top 25 plans, he says. "Dirty data is one of the key problems that blocks health plans from finding insights from data," Bazinsky says. "You might be able to push data real-time, but if you can't trust the underlying kernel of data--all the other things can't be trusted." According to Bazinsky, Cotiviti uses data analytics to help payers achieve financial health through payment accuracy that is appropriate to the care delivered.
Clearsurance, the insurance industry's first unbiased peer review marketplace for insurance consumers, today announced its Recommendation Engine, a new solution driven by consumer data to help consumers view personalized, conflict-free insurance recommendations for the first time. By filtering and sorting based on their unique risk profile, consumers shopping for homeowners, rental or auto insurance can now view the top insurance policies for them without having to worry about financial conflicts of interest or their data surreptitiously being sold to third parties. "Many insurance consumers are eligible for discounts as a result of an affinity to specific groups and unique personal attributes that qualify them to save money on their personal insurance policies," said Michael Crowe, CEO and founder at Clearsurance. "Clearsurance's recommendation engine enables the consumer to identify discount attributes and get recommendations from insurance companies that offer such discounts." In addition to providing an easy-to-use interface designed to simplify an ordinarily complex process, the recommendation engine addresses critical data privacy concerns.
What began as an assignment to the research and development team at American Family Insurance Co. now stands alone as an independent company and today announced its first major customer. Arturu, a Chicago-based insurtech startup launched by American Family three years ago, said in a press release that it has penned a deal with Hippo Insurance to provide "real-time" analytics on property characteristics. "Hippo's partnership with Arturo has allowed us to pre-fill very valuable property data and information directly into the customer's application including roof material, pool presence, and more," stated Michael Gulla, senior director of underwriting at Hippo. "These insights streamline the client's onboarding process, while helping us define a highly accurate initial rating and top-quality underwriting requirements." Hippo, based in Mountain View, California, began working with Arturo from its very start as an insurance provider, and even before Arturo became a company.
The AI in Finance Summit is returning to New York due to popular demand, this time accompanied by the AI in Insurance Summit. Across 2 days, 400 attendees will come together to learn from over 60 speakers about the most cutting edge advancements in the application of AI in the financial and insurance industries. Topics covered will include investment, fintech, financial compliance, financial forecasting, fraud detection, responsibility, deep learning and more. As the discussions around regulation, cybersecurity and ethics increase, these topics will take centre stage across both tracks at the summit. Sessions will focus on the explainability of algorithms used within the financial industry, and there will be presentations for business leaders and decision makers specifically as well to compliment the technical sessions.
Sooner or later, everyone working in applied forms of machine learning goes after a use case that is going to yield tons of data, examples off of which to train a neural network. It's the data, many believe, that very often is the biggest deciding factor in making a network useful. That's the premise of Owlcam, a Palo Alto-based startup that sells a $349 camera for your car dashboard. It has been able to gather millions of videos from its users to refine its ability to detect crashes, to know when to capture video that can be used to handle insurance claims, or to detect an intruder to potentially solve car theft. The product, in other words, is the young company's entrée into a big problem where there's lots to learn.
Technological innovation is a crucial driver of transformation in the financial sector, which has led to efficiency benefits, even though these changes can initially be accompanied, by uncertainty. With opportunities for new methods of service provision, and more significant options for data collection and fraud detection, the insurance industry is no exception to such innovations, which are called "InsurTech." Artificial Intelligence and Robotic Process Automation are occupying the center stage in insurance, driven by data channels, data processing abilities, and advancements in AI algorithms. Insurance companies deploy AI and behavioral economics as its core elements as it eliminates brokers and paperwork. Behavioral economic capabilities minimize fraud, which helps reduce time, efforts, and costs.