India is a breeding ground for many industries. The increase in educated population and the run towards growth has unraveled technology into the country. Today, technology is a core element of growth in the Indian ecosystem. While well-established companies are embracing artificial intelligence for further improvement, Indian start-ups are ballooning like never before. Fortunately, technology-based Indian start-ups landscape has evolved to become the 3rd largest in the world.
Organizations hoping to deploy artificial intelligence have to know what problems they're solving -- no vague questions allowed. Artificial intelligence (AI) and machine learning have come a long way, both in terms of adoption across the broader technology landscape and in the insurance industry specifically. That said, there is still much more territory to cover, helping integral employees like claims adjusters do their jobs better, faster and easier. Data science is currently being used to uncover insights that claims representatives wouldn't have found otherwise, which can be extremely valuable. Data science steps in to identify patterns within massive amounts of data that are too large for humans to comprehend on their own; machines can alert users to relevant, actionable insights that improve claim outcomes and facilitate operational efficiency.
McNee is the president of Ultimate Collision Repair, an auto repair shop in Edison, New Jersey. From his perspective, appraisers and claims adjusters, paid by insurance companies, generally want to pay less for repairs than he thinks his shop deserves. Since Covid-19 swept the globe last year, McNee sees far fewer appraisers. Instead, insurers are deploying technology, including photo-based estimates and artificial intelligence. McNee kind of misses his old adversaries.
A startup is employing machine learning to process aerial imagery and remotely analyze insurance risks to properties around the country. Why it matters: The combination of AI and aerial imagery from satellites and even stratospheric balloons can help insurers quickly judge property risks without an in-person visit, saving money and time. How it works: Arturo's AI model can identify potentially risky characteristics of a property -- like roof tiles in need of repair or a pool that lacks a fence -- and estimate the likelihood of an insurable accident in the future. Background: Arturo's business model is a combination of two major technological trends: the ever-increasing growth of aerial imagery that can capture detailed pictures of the ground and the power of machine learning. The big picture: Insurance might seem like the blandest of businesses, but since its origins hundreds of years ago, the field has focused on using available data to try to predict the future -- which happens to be precisely what machine learning is good at.
In Season 4 of the show Silicon Valley, Jian-Yang creates an app called SeeFood that uses an AI algorithm to identify any food it sees--but since the algorithm has only been trained on images of hot dogs, every food winds up being labeled "hot dog" or "not hot dog." While Jian-Yang's creation may seem absurd, in fact his app displays an intelligence that most AI models in use today do not: it only gives an answer that it knows is 100% accurate. In real life, when you ask most machine learning algorithms a question, they are programmed to give you an answer, even when they are somewhat or entirely unqualified to do so. The data on which these models are trained may have nothing to do with the specific question being asked, but the model delivers an answer anyway -- and as a result, that answer is often wrong. It's as if SeeFood tried to identify every food based only on a knowledge of hot dogs. This issue, known as "model overconfidence," is a key reason why many AI deployments fail to meet their business objectives.
Technology is increasingly becoming centerstage for all businesses across the world. In the last decade, we saw increased adoption of digital operating models and digital transformation of businesses featuring in board conversations. The next decade will surely belong to data and its effective use through AI and ML. AI & ML are by no means new buzzwords in the tech lexicon and we will continue to witness their increasing deployment at scale and becoming far more ubiquitous across organizations and industries. A report by PwC India indicates that the largest rise in the use of AI during COVID-19 has been observed in India.
The insurance industry is being disrupted like it hasn't in decades. Unlike other events like Hurricane Sandy or even the 2008 financial crisis, the coronavirus is impacting essentially every corner of the world and more or less every industry. Smaller insurance companies may not survive the onslaught of new requests, and many larger firms may need to downsize in order to make it through these painful economic times. But innovation investments including artificial intelligence are not going to stop and, in fact, innovation will be one of the key factors in what helps the winners survive. However, those investment priorities will change.
The graph represents a network of 2,735 Twitter users whose tweets in the requested range contained "#FinServ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 04 April 2021 at 01:32 UTC. The requested start date was Sunday, 04 April 2021 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 11-day, 1-hour, 34-minute period from Monday, 22 March 2021 at 09:56 UTC to Friday, 02 April 2021 at 11:30 UTC.
More than ever, companies are able to tailor prices across people, places, and time. They do this to maximize profit, and sometimes simply to survive. We're in a new era of supercharged price discrimination, made possible by two major scientific and technological trends. First, AI algorithms -- often trained on highly detailed behavioral data -- enable organizations to infer what people are willing to pay with unprecedented precision. Second, recent developments in behavioral science -- often invoked with the tagline "nudge" -- provide organizations greater ability to influence their customers' behaviors.
One of the key factors in determining whether companies will thrive or fail in the next five years is how well they use the data they have available. This is a problem for many that may not even know what data they have, let alone how to use it or what insights it may contain. Business processes often involve creating or capturing data in a way that is siloed and difficult to access, analyze or act on outside of the process for which it was created. Even today, many business processes are reliant on physical record-keeping – note-taking, filling out paper forms, or ticking checkboxes on hard copy documents that are then filed away and forgotten about. Even if all a business's procedural documents and record-keeping is digital, the information is of little value unless careful thought is given to the data structure, format, and storage media that will be used.