Artificial Intelligence has revolutionized the finance industry. Not only does it improve the precision level in the industry, but it also enhances the customer engagement level and speed up the query resolution period. In this blog, we will be finding out answers about the importance of AI in financial sectors or FinTech firms. By the year 2030, traditional financial institutions can shave 22% in costs, as per the latest 84-page report of the Autonomous in an AI in the financial industry. Fintech companies and financial firms were the early adopters of relational databases, mainframe computers, and have eagerly awaited the next generation of computational and analysis power.
During peak business periods for group carriers, such as open enrollment in the United States, artificial intelligence can be leveraged to increase group insurance sales by streamlining quoting, optimizing resources, automating manual tasks and eliminating duplication of effort before and during enrollment. Peak enrollment period is here once again as group and voluntary benefits providers put their remote work arrangements to the test in what will be an unusually demanding season. This year has been the year of digital transformation in the insurance industry, and 2020's challenges will inspire new approaches and digitization within carrier ecosystems. Fortunately, insurers can use AI and predictive analytics to increase group insurance sales. AI can help carriers streamline quoting and enrollment, optimize resources, and automate manual tasks.
In 2009, the future founders of Kinetica came up empty when trying to find an existing database that could give the United States Army Intelligence and Security Command (INSCOM) at Fort Belvoir (Virginia) the ability to track millions of different signals in real time to evaluate national security threats. So they built a new database from the ground up, centered on massive parallelization combining the power of the GPU and CPU to explore and visualize data in space and time. By 2014 they were attracting other customers, and in 2016 they incorporated as Kinetica. The current version of this database is the heart of Kinetica 7, now expanded in scope to be the Kinetica Active Analytics Platform. The platform combines historical and streaming data analytics, location intelligence, and machine learning in a high-performance, cloud-ready package.
Researchers have used machine learning, a type of artificial intelligence, to develop a prediction model for the early diagnosis of opioid use disorder. The advance is described in Pharmacology Research & Perspectives. The model was generated from information in a commercial claim database from 2006 through 2018 of 10 million medical insurance claims from 550,000 patient records. It relied on data such as demographics, chronic conditions, diagnoses and procedures, and medication prescriptions. The tool led to a diagnosis of opioid use disorder that was on average 14.4 months earlier than it was diagnosed clinically.
No conference on artificial intelligence (AI), machine learning or robotics would be complete without its fair share of technologists, programmers and engineers. But scan the list of attendees at the 2020 Rise of AI Summit, a hybrid (digital and physical) event this week in Berlin (November 17-18, 2020) and the number of people from health insurance companies, banks and venture capitalists is astonishing. As one of the founders of the event, CEO of Asgard Capital, Fabian Westerheide, said in his opening remarks on "The Next Decade of AI, we are in a'renaissance' of the technology." Westerheide says we're seeing a "refurbishment of ideas from the 1960s, 70s and 80s," combined with the amount of data we have now and today's processing power. He calls it "old ideas, new execution, and new capital."
As artificial intelligence (AI) ascends in the marketplace, the burning question remains as to how far it can be trusted when it comes to the "last mile," the final decision that follows the analytics and recommendations that AI yields. In medicine, AI and analytics crunch through reams of data and scientific research to come up with a series of recommendations for a difficult diagnosis, but it is the expert medical practitioner who makes the final decision. In a loan-approval process, automated decision-making software reviews an application and third-party data to determine a lending decision, but the loan underwriter or supervisor makes the final decision. "Not all decisions in organizations can be fully automated, and some of these will require human intervention," said Arash Aghlara, CEO of Flexrule, which produces decision automation software. "Decision automation should allow scenarios in which fully automated decisions are not possible because of ambiguities, uncertainty, and so on regarding the decisions.
Peak enrollment period is here once again as group and voluntary benefits providers put their remote work arrangements to the test in what will be an unusually demanding season. This year has been the year of digital transformation in the insurance industry, and 2020's challenges will inspire new approaches and digitization for enrollment. Fortunately, insurers can use AI and predictive analytics to streamline quoting and enrollment, optimize resources, and automate manual tasks. Traditional renewal processes raise several speedbumps. Disconnects between quoting and underwriting as well as unreliable information on past successful plan designs unnecessarily increase quote turnaround time, resulting in missed opportunities and a poorer customer experience.
I've been featured on many reputed publications and online magazines! AI has made headlines for the last few years and it's here to make an impact. But what does exactly that mean for HR professionals and recruiters? While adopting artificial intelligence has benefits of its own, the organizations that are the real head-turners are those that have integrated artificial intelligence in the very cores of their business. HR professionals said talent acquisition is one of the most important areas where AI will play a role over the next few years.
This December, CWO: DIGITAL and IBM are bringing 15 insurance fraud leaders together in an exclusive virtual networking event to discuss how technology can be used to enhance their anti-fraud efforts. You'll be joined by IBM fraud specialists who will share their expertise on how to deliver a structured anti-fraud solution for better alert accuracy and efficiency across your organization. In true CWO style, you'll mix business with pleasure as we send guests a selection of the finest wines to be enjoyed over the course of the interactive experience. The estimated cost of property and casualty insurance claims fraud is $32 billion in the US alone. To protect against these losses, fraud detection techniques are evolving to uncover more fraud, avoid false positives and streamline investigations.
Accern is proud to announce its recognition in FinTech Global's InsurTech100, a list of the world's most innovative InsurTech companies that every leader in the insurance industry needs to know about in 2020. Accern Corporation, a leading no-code, Artificial Intelligence (AI) company announced its recognition by FinTech Global as one of the most innovative companies solving significant insurance industry challenges. The InsurTech100 list includes the top 100 of the world's most innovative companies in insurance and is carefully selected by a panel of industry experts and analysts. Accern received recognition for its no-code, AI platform, which allows insurance teams to easily implement artificial intelligence into their workflows, without writing a single line of code. According to FinTech Global, selection is extremely competitive as over 1,000 companies from around the world are evaluated.