{"id":320784,"date":"2025-11-11T09:23:40","date_gmt":"2025-11-11T14:23:40","guid":{"rendered":"https:\/\/www.reviews.com\/?p=118893"},"modified":"2025-11-11T09:23:41","modified_gmt":"2025-11-11T14:23:41","slug":"social-media-underwriting-process","status":"publish","type":"post","link":"https:\/\/www.reviews.com\/insurance\/life\/social-media-underwriting-process\/","title":{"rendered":"Insurance Companies Can See Your Social Media. Time to Scrub Your Profiles?"},"content":{"rendered":"\n\n\n

Insurance is not an industry known for tech innovation or startup unicorns<\/a>. Yet over the past few years insurers have modernized core workflows (e.g., automated underwriting, electronic health records, model governance) while keeping tight controls on data sources that can affect eligibility and price\u2014especially social media, which regulators now treat as a high\u2011risk \u201cexternal consumer data\u201d category subject to strict oversight.<\/p>\n\n\n\n

\u201cChange in the insurance industry has, in the past at least, occurred at the speed of molasses,\u201d says Georgia-based personal insurance agent<\/a> Jenny Saint Preux. In parallel with modernization, guardrails have tightened: New York formalized life\u2011underwriting limits on external data beginning in 2019, the NAIC adopted an AI supervision bulletin in 2023<\/a>, and Colorado implemented binding rules requiring governance and bias testing for life insurers\u2019 use of external data and algorithms under SB21\u2011169<\/a>.<\/p>\n\n\n\n

We also live in a time when AI and data\u2011driven tools advance quickly\u2014but insurers face higher compliance expectations on fairness, transparency, and data provenance. Federal privacy enforcement and data\u2011broker scrutiny have intensified, including the FTC\u2019s 2024 action<\/a> restricting sale of sensitive location data, and California\u2019s CPPA launching a public data broker registry<\/a> that increases visibility and consumer deletion rights\u2014both developments that complicate acquiring social\u2011media\u2011derived signals.<\/p>\n\n\n\n

And yes, life insurers may look at public social media in limited situations. But research and supervisory materials indicate there is no credible evidence of widespread, routine use of individual social media posts to determine whether you\u2019re insured or what you pay for life insurance in regulated markets. Recent regulatory moves focus on preventing unfair discrimination if such data were ever used, not on endorsing it for pricing (New York proposal<\/a>).<\/p>\n\n\n\n

Maybe you\u2019ve heard murmurings about insurers \u201ccreeping\u201d on your profiles; the topic has been covered by media heavy\u2011hitters from the New Yorker<\/a> to Forbes<\/a> and the Wall Street Journal<\/a>. Today\u2019s reality is different: mainstream life underwriting relies on validated evidence such as applications, prescription histories, EHR, MIB, and MVR; social media appears primarily in fraud\/SIU, contestable-claim reviews, or marketing\u2014not as a standard, automated underwriting input (NAIC model bulletin<\/a>; Colorado DOI<\/a>).<\/p>\n\n\n\n

Industry direction and regulatory sources indicate social media is not a standard input in U.S. life underwriting. Where it appears, use is narrow (e.g., verification or fraud\/SIU) and not determinative for pricing\u2014there is no evidence of routine premium setting from posts (NY DFS proposal<\/a>; NAIC 2023<\/a>).<\/span><\/p><\/blockquote>\n\n\n\n

At face value, the idea of a life insurer reviewing your social feed feels invasive. Public sentiment backs that up: global insurance studies report willingness to share social media data with insurers in the low\u2011teens\u2014by far the least acceptable category compared with telematics or health data (Capgemini WIR 2024<\/a>). Broader privacy trackers also find sustained discomfort with organizations scraping or using social content for decisions, and rising expectations for AI transparency (ICO tracker<\/a>; Cisco 2025 Privacy Benchmark<\/a>).<\/p>\n\n\n\n

Fortunately, formal checks and balances now shape how any external consumer data can be used. New York\u2019s life\u2011specific guidance has been in place since 2019<\/a>. The NAIC\u2019s model bulletin adopted in 2023<\/a> sets a national supervisory baseline for AI systems, and Colorado\u2019s rules under SB21\u2011169<\/a> require life insurers to implement governance, inventories, and bias testing for external data and models. Together these frameworks raise the bar for any attempt to use social media in underwriting.<\/p>\n\n\n\n

Unlike big tech, insurers operate under state insurance oversight led by commissioners<\/a>, with growing attention to algorithms, third\u2011party data, and fairness. In addition, federal consumer\u2011protection agencies are tightening rules on the data supply chain\u2014for example, the FTC\u2019s 2024 settlement<\/a> with a location\u2011data broker limits downstream use of sensitive signals, and the CFPB proposed in 2024 to treat many data brokers as consumer reporting agencies when data is sold for eligibility decisions like insurance (Reuters<\/a>).<\/p>\n\n\n\n

Which brings us to New York State\u2019s Insurance Circular Letter No. 1<\/a>, the touchstone many states and carriers use to benchmark acceptable life\u2011underwriting practices involving external data such as social media.<\/p>\n\n\n\n

The circular letter was released by New York\u2019s Department of Financial Services (NYSDFS) and requires life insurers to justify any external data or models they use, avoid unfair or proxy discrimination, provide meaningful reasons for adverse decisions, and oversee third\u2011party vendors. In short, external data can be considered only with demonstrable risk relevance, testing, and transparency (NYDFS<\/a>).<\/p>\n\n\n\n

\u201cThe Department fully supports innovation and the use of technology to improve access to financial services. Indeed, insurers\u2019 use of external data sources has the potential to benefit insurers and consumers alike by simplifying and expediting life insurance sales and underwriting processes.\u201d<\/span><\/p><\/blockquote>\n\n\n\n

The letter defines \u201cexternal data sources\u201d broadly, including \u201cretail purchase history; social media, internet or mobile activity; geographic location tracking; the condition or type of an applicant\u2019s electronic devices (and any systems or applications operating thereon); or based on how the consumer appears in a photograph.\u201d<\/p>\n\n\n\n

Translation for consumers: these sources are in scope, but insurers must be able to explain and validate how any such data affects a life\u2011underwriting decision and show it is not a proxy for protected traits. Generic or opaque reason codes aren\u2019t sufficient\u2014NYSDFS expects tailored, specific explanations when adverse action is taken (NYDFS 2019<\/a>).<\/p>\n\n\n\n

In practice, life carriers continue to prioritize high\u2011signal, auditable, permissioned, or regulated data (Rx histories, EHR, MVR, MIB, certain credit\u2011based mortality indices) over social media. Pilots using social feeds for underwriting have been rare and have not translated into standardized pricing inputs, in part because explainability, validation, and fairness hurdles are high under today\u2019s rules.<\/p>\n\n\n\n

\u201cOn a macro scale, insurance companies are using third-party data more and more to help their underwriting,\u201d says John Holloway, co-founder of life insurance site NoExam.com<\/a>. Reports from data sources such as MIB<\/a>, LexisNexis<\/a>, and MVR<\/a> are common for risk assessment\u2014while direct social media analytics have not become a routine factor in life pricing.<\/p>\n\n\n\n

The challenge for regulators has been applying longstanding fairness standards to new data and AI. That is now materializing: Colorado\u2019s life rules under SB21\u2011169<\/a> require formal governance programs, model\/data inventories, and periodic testing for unfair discrimination; the NAIC\u2019s Model Bulletin<\/a> expects board oversight, documentation, third\u2011party risk management, and monitoring; and New York has proposed expanding AI\/ECDIS oversight across lines (NYDFS 2024 proposal<\/a>).<\/p>\n\n\n\n

\u201cAn insurer should not use an external data source \u2026 for underwriting or rating purposes unless the insurer can establish that the data source does not use and is not based in any way on race, color, creed, national origin, status as a victim of domestic violence, past lawful travel, or sexual orientation in any manner, or any other protected class.\u201d<\/span><\/p><\/blockquote>\n\n\n\n

So where does social media show up? Most commonly in special investigations (SIU) and contestable\u2011period claim reviews as a lead for potential misrepresentation or fraud\u2014uses that are case\u2011by\u2011case, documented, and subject to evidentiary standards and privacy law. Routine, automated use for life underwriting or pricing is not supported by current evidence or regulatory direction.<\/p>\n\n\n\n

\u201cUnderwriters, to my knowledge, are not actively seeking to review applicants\u2019 social media activity,\u201d says Saint Preux. The lift to verify accuracy, avoid proxy discrimination, and generate consumer\u2011facing explanations makes broad deployment impractical under the NAIC and Colorado frameworks, which emphasize governance, bias testing, and third\u2011party oversight.<\/p>\n\n\n\n

\u201cRather,\u201d Saint Preux continues, \u201cthe review has to be prompted by concerns regarding the applicant\u2019s credibility.\u201d In other words, social content\u2014if looked at\u2014is typically considered as non\u2011determinative context in a manual inquiry, not as a scoring variable in an automated workflow.<\/p>\n\n\n\n

One more constraint: platform rules. Meta\u2019s developer policies prohibit using Facebook data to make eligibility determinations, including insurance, limiting direct API pathways for pricing models (Meta platform terms<\/a>). A well\u2011publicized UK attempt in 2016 to price auto insurance using Facebook posts was halted before launch when Facebook blocked access (BBC<\/a>). Expect similar scrutiny for life insurance.<\/p>\n\n\n\n

Bottom line for consumers: there is no verified, widespread practice of using your social posts to set life insurance premiums. If social content is used at all, it is generally limited to narrow, manual reviews (e.g., SIU) under strong governance (NYDFS<\/a>; NAIC 2023<\/a>; Colorado DOI<\/a>).<\/span><\/p><\/blockquote>\n\n\n\n

Practical tip: assume public posts can be seen in an investigation context. Pictures showing tobacco use, frequent drinking, substance dependency, or extreme risk activities could become part of a fact pattern if a carrier investigates misrepresentation. If in doubt, either skip the post or\u2014as a column in the Wall Street Journal<\/a> notes\u2014set sharing to \u201cprivate.\u201d<\/p>\n\n\n\n

And as a rule of thumb, be honest on insurance applications. Insurers that use any external data must be able to provide specific reasons for adverse decisions and show that variables are accurate, relevant, and not unfairly discriminatory. Whether via a database, a traditional exam, or a public post considered during a manual review, inconsistencies are likely to surface under today\u2019s governance expectations.<\/p>\n\n\n\n

For more information about rules and regulations regarding the use of social media and other third party data sources in life insurance underwriting, see the<\/em> New York State Department of Financial Services Circular Letter No. 1, 2019<\/a>. Also relevant are the <\/em>NAIC Model Bulletin on AI systems (2023)<\/a>, Colorado\u2019s <\/em>Regulation 10\u20111\u20111<\/a> for life insurers\u2019 use of external consumer data, and NYDFS\u2019s <\/em>2024 proposed regulation<\/a> on AI and external data.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Insurance is not an industry known for tech innovation or startup unicorns. Yet over the past few years insurers have modernized core workflows (e.g., automated underwriting, electronic health records, model governance) while keeping tight controls on data sources that can affect eligibility and price\u2014especially social media, which regulators now treat as a high\u2011risk \u201cexternal consumer […]<\/p>\n","protected":false},"author":345,"featured_media":118850,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1270],"tags":[],"post_author":[],"yoast_head":"\nInsurance Companies Can See Your Social Media. Time to Scrub Your Profiles? - Reviews.com<\/title>\n<meta name=\"description\" content=\"Understanding if Insurance Companies Can See Your Social Media. 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