{"id":16025,"date":"2021-11-16T12:56:30","date_gmt":"2021-11-16T12:56:30","guid":{"rendered":"https:\/\/icgnet.it\/the-point-on-artificial-intelligence\/"},"modified":"2021-11-16T12:57:58","modified_gmt":"2021-11-16T12:57:58","slug":"the-point-on-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/icgnet.it\/en\/the-point-on-artificial-intelligence\/","title":{"rendered":"The point on Artificial Intelligence"},"content":{"rendered":"\n
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Insurtech and surroundings<\/p>

LET’S MAKE A POINT ON ARTIFICIAL INTELLIGENCE<\/p>\n

What are the applications in the insurance sector?<\/a><\/p><\/div>\n\n

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Welcome to a new era<\/h2>\n
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At the end of April 2018, the European Commission finally unveiled its plans to promote research and development in the field of Artificial Intelligence (AI), proposing a three-pronged approach aimed at increasing public and private investments, preparing for change. socio-economic and to ensure an adequate ethical and legal framework.<\/p>\n\n

As steam, electricity and the internet did in the past, AI is transforming our world in a definitive way, giving life to what experts already consider the Fourth Industrial Revolution.<\/p>\n\n

A recent report published by Forbes identifies a timid start to the use of solutions developed on AI during 2017 (we are talking about 38% of companies), but the percentage seems destined to rise to 62% in 2018. Other studies and analyzes predict 300% increases in investments in Artificial Intelligence.<\/p>\n\n

Apart from the numbers involved that may vary from research to research, the interesting data is certainly the strong acceleration that this technology will have in the coming months.<\/p>\n<\/div>\n<\/div>\n\n

But what is Artificial Intelligence?<\/h2>\n
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In a simplistic way we could define artificial intelligence as the ability of a technological system to solve problems or perform tasks and activities typical of the human mind and ability.<\/p>\n\n

Looking at the IT sector, we could identify AI – Artificial Intelligence as the discipline that deals with creating machines (hardware and software) capable of “acting” autonomously, carrying out tasks and actions typical of human intelligence (planning, understanding of language , image and sound recognition, problem solving, pattern recognition, etc.).<\/p>\n\n

The interest of the scientific community in Artificial Intelligence dates back to the 40s of the twentieth century, but the current ferment around this discipline is explained by the technological maturity achieved both in computational computing (today there are very powerful hardware systems, of small size and with low energy consumption), both in the ability to analyze in real-time and in a short time of huge amounts of data and of any form (Analytics).<\/p> \n\n

Today, technological maturity has meant that Artificial Intelligence leaves the riverbed of research to actually enter everyday life. \n<\/p><\/div>\n<\/div>\n\n

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How Artificial Intelligence works.<\/h2>\n
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Talking about AI actually means talking about different technologies and tools.\nThere are four key points that help us define the activity of Artificial Intelligence.\n<\/p>

\"\"<\/p>\n

understanding<\/h5>\n

Through the simulation of cognitive abilities of data and event correlation, AI (Artificial Intelligence) is able to recognize texts, images, tables, videos, voice and extract information from them.\n<\/p>

\"\"<\/p>\n

reasoning<\/h5>

\nThrough logic, the systems are able to connect the multiple information collected (through precise mathematical algorithms and in an automated way).\n<\/p>

\"\"<\/p>\n

learning<\/h5>

\nIn this case we are talking about systems with specific functions for the analysis of data inputs and for their “correct” return in output (it is the classic example of Machine Learning systems that with machine learning techniques lead AI to learn and perform various functions).\n<\/p>

\"\"<\/p>\n

interaction<\/h5>

\nHuman Machine Interactions, that is, the methods of functioning of AI in relation to its interaction with humans. This is where Nlp – Natural Language Processing systems are strongly advancing, technologies that allow humans to interact with machines (and vice versa) by exploiting natural language.\n<\/p>\n<\/div>\n<\/div>\n\n

ICG offers customized Artificial Intelligence and Machine Learning solutions for Insurance Players<\/p><\/div>\n\n

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ICG supports companies in exploiting the potential of Artificial Intelligence to implement sector-specific solutions. Thanks to the skills consolidated during the implementation of numerous PoCs with latest generation technologies, it can be considered at the forefront of these issues that will inevitably mark the near future of the insurance world.\n<\/p>\n<\/div>\n<\/div>\n\n[grid_plus name=”AI_products”]\n\n

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Why are we talking about Artificial Intelligence in Insurance?<\/h2>\n
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Automation through artificial intelligence is destined to permeate all processes in the insurance world, giving a significant opportunity to streamline and optimize processes and reduce management costs.\n<\/p>

\nCarrying out repetitive and low added value activities through these technologies leads to an improvement in process efficiency and more easily ensures compliance with increasingly stringent regulatory requirements for verifiability, security, data quality and operational resilience.\n<\/p>

\nTechnology will drastically change the insurance workforce in the years to come: there will be less demand for resources to handle routine processing tasks, and at the same time the workforce will begin to favor creative thinkers and market strategy connoisseurs. The resources able to collaborate effectively with the technology and train it, as if it were an apprentice, will become fundamental.\n<\/p>

\nIn fact, these new technologies cannot ignore interaction with man: they are at his service and work in an integrated way with human intelligence. In fact, Artificial Intelligence can analyze large amounts of data very quickly and, with self-learning processes, progressively improve the performance of the systems. \nHowever, it always needs a guide and a teacher who asks the correct questions and objectives:\nthe algorithm provides results and modifies its behavior based on human user feedback.\n<\/p>\n<\/div>\n<\/div>\n\n

Find out more<\/p>\n

Contact us to find out how we can help your business.<\/p>Learn more<\/a><\/div>\n\n

Introducing Artificial Intelligence in Insurance<\/h2>\n
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The applications through which AI can translate into reality in the insurance sector are basically:\n<\/p>\n

  • Natural language and bots<\/li>\n
  • Analysis of images and documents<\/li>\n
  • Semantic analysis and target market<\/li>\n
  • Process observation<\/li>\n
  • RPA robotic process automation<\/li>\n
  • Predictive models<\/li>\n<\/ul>

    We think of the voice \/ virtual assistants who use Artificial Intelligence both for the recognition of natural language and for the learning and analysis of the habits and behaviors of users; real-time analysis of large amounts of data for understanding the “sentiment” and needs of people to improve customer care, user experience, assistance and support services but also to create and refine sophisticated engagement mechanisms with activities that push up to the forecast of purchasing behaviors from which to derive communication strategies and \/ or service proposals.\n<\/p>\n

    Fraud prevention is one of the most mature applications where Artificial Intelligence materializes with what are technically called “advanced analytics”, very sophisticated analyzes that correlate data, events, behaviors and habits to understand any fraudulent activity in advance; these systems can actually also find application within other business contexts, for example for the mitigation of risks, the protection of information and data, the fight against cybercrime.\n<\/p>\n

    The ability to analyze huge amounts of data in real time and to “deduce” through correlations of events, habits, behaviors, attitudes, systems, geo-localization and monitoring of the movement of things and people offers enormous potential for improving efficiency and the effectiveness of public security, for example for crisis prevention and management in cases of natural disasters such as earthquakes and tsunamis.\n<\/p>\nImplementing predictive models and robotic process automation (RPA), can help every actor to work better thanks to intelligent processes that suggest the right passage at the right time and eliminate manual processing prone to errors.\n\n

    To these examples we can add further advantages for insurance players:<\/p>\n

    • Replace ex-post checks, statistics and extractions with active process analysis<\/li>\n
    • Apply the best action to every single event, based on previous experiences<\/li>\n
    • Anti-fraud verification of the images of the claim<\/li>\n
    • Damage quantification based on the images<\/li>\n
    • Decoding of paper documents and intelligent use of the information contained<\/li>\n
    • Real-time complaints 24 \/ 24h<\/li>\n
    • Virtual assistant 24 \/ 24h<\/li>\n
    • Geo-localized marketing<\/li>\n
    • Weather alerts, hail, earthquakes<\/li>\n<\/ul><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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