{"id":6262,"date":"2024-05-25T04:11:47","date_gmt":"2024-05-25T11:11:47","guid":{"rendered":"https:\/\/athis-technologies.com\/news\/?p=6262"},"modified":"2024-05-27T08:29:03","modified_gmt":"2024-05-27T15:29:03","slug":"the-future-of-financial-analysis-how-gpt-4-is-disrupting-the-industry-according-to-new-research","status":"publish","type":"post","link":"https:\/\/athis-technologies.com\/news\/market\/2024\/the-future-of-financial-analysis-how-gpt-4-is-disrupting-the-industry-according-to-new-research\/","title":{"rendered":"The future of financial analysis: How GPT-4 is disrupting the industry, according to new research"},"content":{"rendered":"\n<p>Researchers from the&nbsp;<a href=\"https:\/\/www.chicagobooth.edu\/\" target=\"_blank\" rel=\"noreferrer noopener\">University of Chicago<\/a>&nbsp;have demonstrated that large language models (LLMs) can conduct financial statement analysis with accuracy rivaling and even surpassing that of professional analysts. The findings, published in a working paper titled \u201c<a href=\"https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=4835311\">Financial Statement Analysis with Large Language Models<\/a>,\u201d could have major implications for the future of financial analysis and decision-making.<\/p>\n\n\n\n<p>The researchers tested the performance of&nbsp;<a href=\"https:\/\/venturebeat.com\/ai\/openais-sam-altman-calls-ai-systems-like-gpt-4-safe-enough-for-use\/\">GPT-4<\/a>, a state-of-the-art LLM developed by&nbsp;<a href=\"https:\/\/venturebeat.com\/ai\/openai-shrugs-off-metas-llama-3-ascent-with-new-enterprise-ai-features\/\">OpenAI<\/a>, on the task of analyzing corporate financial statements to predict future earnings growth. Remarkably, even when provided only with standardized, anonymized balance sheets, and income statements devoid of any textual context, GPT-4 was able to outperform human analysts.UnmuteAdvanced SettingsFullscreenPauseRewind 10 SecondsUp NextNewsletters<a target=\"_blank\" href=\"https:\/\/venturebeat.com\/newsletters\/\" rel=\"noreferrer noopener\">Subscribe<\/a>How AI is advancing geospatial intelligence<\/p>\n\n\n\n<p>\u201cWe find that the prediction accuracy of the LLM is on par with the performance of a narrowly trained state-of-the-art ML model,\u201d the authors write. \u201cLLM prediction does not stem from its training memory. Instead, we find that the LLM generates useful narrative insights about a company\u2019s future performance.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/venturebeat.com\/wp-content\/uploads\/2024\/05\/Screenshot_2024-05-24_at_1_04_32_PM_png.png?w=800\" alt=\"\" class=\"wp-image-2956789\"\/><figcaption>A study by researchers at the University of Chicago found that OpenAI\u2019s GPT-4 model outperformed human analysts in predicting corporate earnings, achieving an accuracy score of 0.604 and an F1 score of 0.609. The researchers used a novel approach of providing structured financial data and \u201cchain-of-thought\u201d prompts to guide the AI\u2019s reasoning. (Source: University of Chicago)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-chain-of-thought-prompts-emulate-human-analyst-reasoning\">Chain-of-thought prompts emulate human analyst reasoning<\/h2>\n\n\n\n<p>A key innovation was the use of \u201c<a href=\"https:\/\/www.promptingguide.ai\/techniques\/cot\">chain-of-thought<\/a>\u201d prompts that guided GPT-4 to emulate the analytical process of a financial analyst, identifying trends, computing ratios, and synthesizing the information to form a prediction. This enhanced version of GPT-4 achieved a 60% accuracy in predicting the direction of future earnings, notably higher than the 53-57% range of human analyst forecasts.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">VB EVENT<\/h3>\n\n\n\n<p><strong>The AI Impact Tour: The AI Audit<\/strong><\/p>\n\n\n\n<p>Join us as we return to NYC on June 5th to engage with top executive leaders, delving into strategies for auditing AI models to ensure fairness, optimal performance, and ethical compliance across diverse organizations. Secure your attendance for this exclusive invite-only event.<a href=\"https:\/\/impact.venturebeat.com\/ai-impact-tour\/the-ai-audit\/\">Request an invite<\/a>ADVERTISEMENT<\/p>\n\n\n\n<p>\u201cTaken together, our results suggest that LLMs may take a central role in decision-making,\u201d the researchers conclude. They note that the LLM\u2019s advantage likely stems from its vast knowledge base and ability to recognize patterns and business concepts, allowing it to perform intuitive reasoning even with incomplete information.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/venturebeat.com\/wp-content\/uploads\/2024\/05\/Screenshot-2024-05-24-at-1.15.29%E2%80%AFPM.png?w=800\" alt=\"\" class=\"wp-image-2956791\"\/><figcaption>University of Chicago researchers tested GPT4\u2019s financial analysis capabilities by providing it with anonymized, standardized financial statements and guiding its reasoning with \u201cchain-of-thought\u201d prompts. The model then predicted the direction, magnitude, and confidence of future earnings changes. (Source: University of Chicago)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-llms-poised-to-transform-financial-analysis-despite-challenges\">LLMs poised to transform financial analysis despite challenges<\/h2>\n\n\n\n<p>ADVERTISEMENT<\/p>\n\n\n\n<p>The findings are all the more remarkable given that numerical analysis has traditionally been a challenge for language models. \u201cOne of the most challenging domains for a language model is the numerical domain, where the model needs to carry out computations, perform human-like interpretations, and make complex judgments,\u201d said Alex Kim, one of the study\u2019s co-authors. \u201cWhile LLMs are effective at textual tasks, their understanding of numbers typically comes from the narrative context and they lack deep numerical reasoning or the flexibility of a human mind.\u201d<\/p>\n\n\n\n<p>Some experts caution that the \u201c<a href=\"https:\/\/www.sciencedirect.com\/topics\/engineering\/artificial-neural-network-model#:~:text=An%20ANN%20model%20usually%20utilizes,connectionist%20approach%20in%20the%20computation.\" target=\"_blank\" rel=\"noreferrer noopener\">ANN<\/a>\u201d model used as a benchmark in the study may not represent the state-of-the-art in quantitative finance. \u201cThat ANN benchmark is nowhere near state of the art,\u201d commented one practitioner on the&nbsp;<a href=\"https:\/\/news.ycombinator.com\/item?id=40468518\">Hacker News forum<\/a>. \u201cPeople didn\u2019t stop working on this in 1989 \u2014 they realized they can make lots of money doing it and do it privately.\u201d<\/p>\n\n\n\n<p>Nevertheless, the ability of a general-purpose language model to match the performance of specialized ML models and exceed human experts points to the disruptive potential of LLMs in the financial domain. The authors have also created an&nbsp;<a href=\"https:\/\/chat.openai.com\/g\/g-9P3sIn487-financial-statement-analyzer\" target=\"_blank\" rel=\"noreferrer noopener\">interactive web application<\/a>&nbsp;to showcase GPT-4\u2019s capabilities for curious readers, though they caution that its accuracy should be independently verified.<\/p>\n\n\n\n<p>As AI continues its rapid advance, the role of the financial analyst may be the next to be transformed. While human expertise and judgment are unlikely to be fully replaced anytime soon, powerful tools like GPT-4 could greatly augment and streamline the work of analysts, potentially reshaping the field of financial statement analysis in the years to come.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers from the&nbsp;University of Chicago&nbsp;have demonstrated that large language models (LLMs) can conduct financial statement analysis with accuracy rivaling and even surpassing that of professional analysts. The findings, published in a working paper titled \u201cFinancial Statement Analysis with Large Language Models,\u201d could have major implications for the future of financial analysis and decision-making. The researchers [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":6263,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"amp_status":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[10],"tags":[127,244,415],"jetpack_publicize_connections":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>The future of financial analysis: How GPT-4 is disrupting the industry, according to new research - AthisNews<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/athis-technologies.com\/news\/market\/2024\/the-future-of-financial-analysis-how-gpt-4-is-disrupting-the-industry-according-to-new-research\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The future of financial analysis: How GPT-4 is disrupting the industry, according to new research - AthisNews\" \/>\n<meta property=\"og:description\" content=\"Researchers from the&nbsp;University of Chicago&nbsp;have demonstrated that large language models (LLMs) can conduct financial statement analysis with accuracy rivaling and even surpassing that of professional analysts. The findings, published in a working paper titled \u201cFinancial Statement Analysis with Large Language Models,\u201d could have major implications for the future of financial analysis and decision-making. 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