{"id":1549,"date":"2022-08-31T12:12:11","date_gmt":"2022-08-31T12:12:11","guid":{"rendered":"https:\/\/pickl.ai\/blog\/?p=1549"},"modified":"2024-08-13T10:43:13","modified_gmt":"2024-08-13T10:43:13","slug":"radicl-ml","status":"publish","type":"post","link":"https:\/\/www.pickl.ai\/blog\/radicl-ml\/","title":{"rendered":"Leveraging Machine Learning to Predict Insurance Premiums"},"content":{"rendered":"<p><b>Summary: <\/b><span style=\"font-weight: 400;\">This article explores how Machine Learning (ML) can predict insurance premiums based on customer data. It also discusses Natural Language Processing (NLP) advancements and how AI is becoming better at understanding spoken language and facial recognition<\/span><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Background\" >Background<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Key_Factors_Driving_this_Change\" >Key Factors Driving this Change<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Open_Source\" >Open Source<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Harnessing_the_Internet_of_Things_IoT_Data\" >Harnessing the Internet of Things (IoT) Data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#NLP_Algorithms_on_the_Rise\" >NLP Algorithms on the Rise<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Case_Study\" >Case Study<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Modelling\" >Modelling<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Scope_for_Improvement\" >Scope for Improvement<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Challenges_Insurers_Typically_Encounter_When_Adopting_Machine_Learning\" >Challenges Insurers Typically Encounter When Adopting Machine Learning\u00a0<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Training_requirements\" >Training requirements<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Right_Data_Source\" >Right Data Source<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Difficulty_in_Predicting_Returns\" >Difficulty in Predicting Returns<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Data_security\" >Data security<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Can_Machine_Learning_Really_Predict_my_Insurance_Cost\" >Can Machine Learning Really Predict my Insurance Cost?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Is_My_Data_Safe_When_Using_AI-powered_Insurance\" >Is My Data Safe When Using AI-powered Insurance?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#What_Are_The_Benefits_of_NLP_in_Insurance\" >What Are The Benefits of NLP in Insurance?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.pickl.ai\/blog\/radicl-ml\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"background\"><span class=\"ez-toc-section\" id=\"Background\"><\/span><b>Background<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Data has always played a central role in the insurance industry; today, insurance carriers have access to more than ever. We have created more data in the past five years than the human race has ever created.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Insurers\u2014like organisations in most industries\u2014are overwhelmed by the explosion in data from various sources, including telematics, online and social media activity, voice analytics, connected sensors and wearable devices.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">They need machines to process this information and unearth analytical insights. However, most insurers are struggling to maximise the benefits of Machine Learning.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This situation is seeing a gradual but steady change, driven by an environment characterised by increased competition, elastic marketplaces, complex claims and fraud behaviour, higher customer expectations and tighter regulation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Insurers are being forced to explore ways to use <\/span><a href=\"https:\/\/pickl.ai\/blog\/anticipating-tomorrow-the-power-of-predictive-modeling\/\"><span style=\"font-weight: 400;\">predictive modelling<\/span><\/a><span style=\"font-weight: 400;\"> and <\/span><a href=\"https:\/\/pickl.ai\/blog\/feature-engineering-in-machine-learning\/\"><span style=\"font-weight: 400;\">Machine Learning<\/span><\/a><span style=\"font-weight: 400;\"> to maintain their competitive edge, boost business operations and enhance customer satisfaction.\u00a0<\/span><\/p>\n<h2 id=\"key-factors-driving-this-change\"><span class=\"ez-toc-section\" id=\"Key_Factors_Driving_this_Change\"><\/span><b>Key Factors Driving this Change<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Enterprises want to use advanced Machine Learning to drive smart, automated applications in healthcare diagnosis, predictive maintenance, customer service, and automated data centres.\u00a0<\/span><\/p>\n<h3 id=\"open-source\"><span class=\"ez-toc-section\" id=\"Open_Source\"><\/span><b>Open Source<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">As data becomes omnipresent, open-source protocols will emerge to ensure data is shared and used. Different public and private entities will create ecosystems for sharing data on multiple use cases under a common regulatory and cybersecurity framework.\u00a0<\/span><\/p>\n<h3 id=\"harnessing-the-internet-of-things-iot-data\"><span class=\"ez-toc-section\" id=\"Harnessing_the_Internet_of_Things_IoT_Data\"><\/span><b>Harnessing the Internet of Things (IoT) Data<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The volume and velocity of data from IoT will drive the need to automate the generation of actionable insight using advanced Machine Learning tools.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to Gartner, by 2025, 55 <\/span><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2023-08-01-gartner-identifies-top-trends-shaping-future-of-data-science-and-machine-learning\"><span style=\"font-weight: 400;\">per cent of enterprises <\/span><\/a><span style=\"font-weight: 400;\">will employ dedicated people to monitor and guide Machine Learning (such as neural networks). The notion of training rather than programming systems will become increasingly important.\u00a0<\/span><\/p>\n<h3 id=\"nlp-algorithms-on-the-rise\"><span class=\"ez-toc-section\" id=\"NLP_Algorithms_on_the_Rise\"><\/span><b>NLP Algorithms on the Rise<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/pickl.ai\/blog\/introduction-to-natural-language-processing\/\"><span style=\"font-weight: 400;\">Natural Language Processing algorithms <\/span><\/a><span style=\"font-weight: 400;\">are continuously advancing. AI is becoming proficient at understanding spoken language and facial recognition, helping to make it more useful and intuitive.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These algorithms are evolving unexpectedly, as Google found when Google Translate invented its language to help it translate more effectively.<\/span><\/p>\n<h2 id=\"case-study\"><span class=\"ez-toc-section\" id=\"Case_Study\"><\/span><b>Case Study<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The myriad opportunities in the insurance sector, especially health insurance, motivated me to undertake this capstone project. Health has taken a back seat in this ever-advancing world, but the pandemic has made us realise its importance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Access to healthcare is still a challenge, primarily due to the high costs associated with it. Insurance is the most important factor in improving individuals&#8217; healthcare access.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Given their characteristics, I wish to predict the insurance premium charges of an insuree. Their characteristics include<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Age<\/span><\/p>\n<p><span style=\"font-weight: 400;\">BMI<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Biological Sex<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Smoker<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Region<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Exploratory data analysis yielded excellent insights into the data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"> <img fetchpriority=\"high\" decoding=\"async\" class=\"radius-5 aligncenter wp-image-9515 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age.png\" alt=\"Machine Learning\" width=\"396\" height=\"332\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age.png 396w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-300x252.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-110x92.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-200x168.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-380x319.png 380w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-255x214.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/age-150x126.png 150w\" sizes=\"(max-width: 396px) 100vw, 396px\" \/><\/span><\/p>\n<p><img decoding=\"async\" class=\"radius-5 aligncenter wp-image-9526 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"367\" height=\"325\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi.png 367w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi-300x266.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi-110x97.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi-200x177.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi-255x226.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/BMi-150x133.png 150w\" sizes=\"(max-width: 367px) 100vw, 367px\" \/><\/p>\n<p><img decoding=\"async\" class=\"radius-5 aligncenter wp-image-9527 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"378\" height=\"342\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children.png 378w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children-300x271.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children-110x100.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children-200x181.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children-255x231.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/children-150x136.png 150w\" sizes=\"(max-width: 378px) 100vw, 378px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-9528\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"376\" height=\"347\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers.png 376w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers-300x277.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers-110x102.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers-200x185.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers-255x235.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/smokers-150x138.png 150w\" sizes=\"(max-width: 376px) 100vw, 376px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"radius-5 aligncenter wp-image-9530 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"376\" height=\"353\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges.png 376w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges-300x282.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges-110x103.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges-200x188.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges-255x239.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/distribution-charges-150x141.png 150w\" sizes=\"(max-width: 376px) 100vw, 376px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"radius-5 aligncenter wp-image-9531 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"402\" height=\"278\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges.png 402w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-300x207.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-110x76.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-200x138.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-380x263.png 380w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-255x176.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges-150x104.png 150w\" sizes=\"(max-width: 402px) 100vw, 402px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"radius-5 aligncenter wp-image-9532 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"407\" height=\"280\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2.png 407w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-300x206.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-110x76.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-200x138.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-380x261.png 380w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-255x175.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/charges2-150x103.png 150w\" sizes=\"(max-width: 407px) 100vw, 407px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The data had no NULL values, an important factor in data quality. Each of the independent data features had no outliers, and data wrangling was successfully performed.\u00a0<\/span><\/p>\n<h3 id=\"modelling\"><span class=\"ez-toc-section\" id=\"Modelling\"><\/span><b>Modelling<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">I applied a regression algorithm to predict insurance charges for the insurees. After applying regression to the data set, the prediction was successful with an R-squared value of 0.7488.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"radius-5 aligncenter wp-image-9533 size-full\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes.png\" alt=\"Machine Learning to Predict Insurance Premiums\" width=\"683\" height=\"530\" srcset=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes.png 683w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-300x233.png 300w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-110x85.png 110w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-200x155.png 200w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-380x295.png 380w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-255x198.png 255w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-550x427.png 550w, https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2022\/08\/codes-150x116.png 150w\" sizes=\"(max-width: 683px) 100vw, 683px\" \/><\/p>\n<h3 id=\"scope-for-improvement\"><span class=\"ez-toc-section\" id=\"Scope_for_Improvement\"><\/span><b>Scope for Improvement<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">One could use other machine learning algorithms to improve the accuracy and fine-tuning of the model. A linear regression model\u2019s performance could be improved by using:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Adding interaction terms to model how two or more independent variables together impact the target variable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Polynomial terms addition to model the nonlinear relationship between an independent variable and the target variable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Adding spines to approximate piecewise linear models.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Fitting isotonic regression to remove any assumption of the target function form.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">One could also use non-linear ML algorithms like regression trees to improve performance.\u00a0<\/span><\/p>\n<h2 id=\"challenges-insurers-typically-encounter-when-adopting-machine-learning\"><span class=\"ez-toc-section\" id=\"Challenges_Insurers_Typically_Encounter_When_Adopting_Machine_Learning\"><\/span><b>Challenges Insurers Typically Encounter When Adopting Machine Learning\u00a0<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3 id=\"training-requirements\"><span class=\"ez-toc-section\" id=\"Training_requirements\"><\/span><b>Training requirements<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">AI-powered intellectual systems must be trained in a domain, e.g., claims or billing for an insurer. This requires a separate training system, which insurers find difficult to provide for AI model training. Models need to be trained with huge volumes of documents\/transactions to cover all possible scenarios.\u00a0<\/span><\/p>\n<h3 id=\"right-data-source\"><span class=\"ez-toc-section\" id=\"Right_Data_Source\"><\/span><b>Right Data Source<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The quality of data used to train predictive models is equally important as the quantity in the case of Machine Learning. The datasets need to be representative and balanced so that they can give a better picture and avoid bias. This is important to train predictive models. Generally, insurers struggle to provide relevant data for training AI models.\u00a0<\/span><\/p>\n<h3 id=\"difficulty-in-predicting-returns\"><span class=\"ez-toc-section\" id=\"Difficulty_in_Predicting_Returns\"><\/span><b>Difficulty in Predicting Returns<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">It\u2019s difficult to predict improvements that Machine Learning can bring to a project. For example, it\u2019s not easy to plan or budget a project using Machine Learning, as the funding needs may vary during the project based on the findings.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Therefore, it is almost impossible to predict the return on investment. This makes it hard to get everyone on board the concept and invest in it.\u00a0<\/span><\/p>\n<h3 id=\"data-security\"><span class=\"ez-toc-section\" id=\"Data_security\"><\/span><b>Data security<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The huge amount of data used for Machine Learning algorithms has created an additional security risk for insurance companies. With such an increase in collected data and connectivity among applications, there is a risk of data leaks and security breaches. A security incident could lead to personal information falling into the wrong hands. This creates fear in the minds of insurers.\u00a0<\/span><\/p>\n<h2 id=\"frequently-asked-questions\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><b>Frequently Asked Questions<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3 id=\"can-machine-learning-really-predict-my-insurance-cost\"><span class=\"ez-toc-section\" id=\"Can_Machine_Learning_Really_Predict_my_Insurance_Cost\"><\/span><b>Can Machine Learning Really Predict my Insurance Cost?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Yes, ML algorithms can analyze factors like age, health, and location to estimate insurance premiums. However, these are just estimates, and your actual cost might vary.<\/span><\/p>\n<h3 id=\"is-my-data-safe-when-using-ai-powered-insurance\"><span class=\"ez-toc-section\" id=\"Is_My_Data_Safe_When_Using_AI-powered_Insurance\"><\/span><b>Is My Data Safe When Using AI-powered Insurance?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Data security is a concern with AI. Insurers need robust measures to protect sensitive customer information from leaks or breaches.<\/span><\/p>\n<h3 id=\"what-are-the-benefits-of-nlp-in-insurance\"><span class=\"ez-toc-section\" id=\"What_Are_The_Benefits_of_NLP_in_Insurance\"><\/span><b>What Are The Benefits of NLP in Insurance?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">NLP helps AI understand customer requests and documents. This can streamline tasks like processing claims and improve communication between insurers and clients.<\/span><\/p>\n<h2 id=\"conclusion\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><b>Conclusion<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine Learning offers a powerful tool for insurance companies to improve their operations and customer satisfaction. By leveraging advanced algorithms, insurers can gain valuable insights from vast amounts of data, leading to more accurate premium pricing, efficient claims processing, and better fraud detection.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">However, challenges such as training requirements, data quality, and security concerns need to be addressed for successful ML adoption. As the technology matures and these hurdles are overcome, Machine Learning will undoubtedly play a transformative role in the future of insurance.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"AI in insurance: ML predicts premiums, NLP aids understanding.\n","protected":false},"author":6,"featured_media":9534,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[2],"tags":[110,103,101,104,105,108,109,111,112,102,25,2263,106,107],"ppma_author":[2174,2178],"class_list":{"0":"post-1549","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-machine-learning","8":"tag-amazon-data-engineer-interview-questions","9":"tag-data-engineer-manager-interview-questions","10":"tag-data-engineer-process-interview-questions","11":"tag-data-engineer-technical-interview-questions","12":"tag-data-engineering-tools","13":"tag-faang-data-engineer-question","14":"tag-facebook-data-engineer-interview-questions","15":"tag-google-data-engineer-interview-questions","16":"tag-how-to-prepare-for-the-data-engineer-interview","17":"tag-junior-data-engineer-interview-questions","18":"tag-machine-learning","19":"tag-machine-learning-to-predict-insurance-premiums","20":"tag-python-interview-questions-for-data-engineers","21":"tag-sql-interview-questions-for-data-engineers"},"yoast_head":"<!-- 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