{"id":3563,"date":"2023-09-28T14:43:17","date_gmt":"2023-09-28T18:43:17","guid":{"rendered":"https:\/\/www.amalgamatedbenefits.com\/amalgamated-life\/?p=3563"},"modified":"2024-07-01T07:40:17","modified_gmt":"2024-07-01T11:40:17","slug":"artificial-intelligence-machine-learning-changing-insurance","status":"publish","type":"post","link":"https:\/\/www.amalgamatedbenefits.com\/amalgamated-life\/artificial-intelligence-machine-learning-changing-insurance\/","title":{"rendered":"Artificial Intelligence & Machine Learning Changing Insurance"},"content":{"rendered":"
\"Insurance<\/figure>\n

Insurance is experiencing major changes at the hands of advanced technologies such Artificial Intelligence (AI) and Machine Learning (ML). From underwriting to customer service, insurers and their policy holders alike are benefiting. Here\u2019s how:<\/p>\n

AI Driving Improved Risk and Fraud Detection<\/h2>\n

One way AI is transforming insurance is in the policy application process. AI is improving risk and fraud detection, as well as helping to mitigate human error thereby enabling insurers to market the best solutions to their customers. In addition to getting the right insurance coverage, customers also gain in AI-driven, streamlined claims processing.<\/p>\n

AI is also proving to be a major asset by automating certain underwriting processes by leveraging its data harnessing powers to streamline, for example, information gathering and document reviews, while leaving more complex processes in high-value underwriting to specialists with the required expertise. Unlike traditional processes which rely on historical data and leave insurers vulnerable, AI-driven processes reflect emerging risks and trends to facilitate more accurate insights and projections.<\/p>\n

ML\u2019s Role in Risk Assessment<\/h3>\n

ML is supporting insurers through its natural language understanding which helps insurers review various information sources such as social media postings and online customer reviews, as well as SEC filings to determine their potential risks. This facilitates more accurate risk assessments which, in turn, enable more on-target premiums. Regarding its fraud detection capabilities, ML\u2019s cognitive algorithms have attained a 75% accuracy rate for identifying fraudulent insurance claims, even going as far as to provide details on suspicious claims and potential exposures, as well as cost assessments for remediation and recommended fraud protection measures.<\/p>\n

Automation Driving Improvements in Other Areas of Operations<\/h4>\n

In addition to the roles AI and ML are playing in underwriting, customer service, risk assessment and fraud detection, these and other advanced technologies are also driving important advancements in other areas of an insurer\u2019s operations. These include:<\/p>\n