Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions
Artificial Intelligence (AI) is changing real estate valuation with innovative approaches. This article examines several AI methods – Regression Models, Decision Trees, Random Forests, Artificial Neural Networks, and XGBoost – and explores their applications for improving property valuation accuracy...
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| Format: | Article |
| Language: | English |
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Chamber of Financial Auditors of Romania
2025-02-01
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| Series: | Audit Financiar |
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| Online Access: | http://revista.cafr.ro/temp/Article_9792.pdf |
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| author | Silviu-Ionut BABTAN |
| author_facet | Silviu-Ionut BABTAN |
| author_sort | Silviu-Ionut BABTAN |
| collection | DOAJ |
| description | Artificial Intelligence (AI) is changing real estate valuation with innovative approaches. This article examines several AI methods – Regression Models, Decision Trees, Random Forests, Artificial Neural Networks, and XGBoost – and explores their applications for improving property valuation accuracy and efficiency, with implications for other professions involved, e.g. audit. The author starts by investigating traditional valuation methods' limitations, such as data constraints and subjectivity, and presents how these AI techniques, which are translated in property valuation field as automated valuation methods, tackle these challenges. Regression Models quantify attributes, Decision Trees provide clear insights, Random Forests improve predictions, Artificial Neural Networks design elaborate relationships, and XGBoost furnishes advanced boosting techniques for higher performance. Underscoring that AI is meant to support, not substitute, human assessors, the paper presents how these methods can enhance valuation processes, deliver more reliable valuation reports, and decrease errors, while also exploring future innovations and evolving trends in artificial intelligence for real estate industry and related professions. |
| format | Article |
| id | doaj-art-dde5919146554b9a8a7f53d7b390cad2 |
| institution | Kabale University |
| issn | 1583-5812 1844-8801 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Chamber of Financial Auditors of Romania |
| record_format | Article |
| series | Audit Financiar |
| spelling | doaj-art-dde5919146554b9a8a7f53d7b390cad22025-02-10T15:26:12ZengChamber of Financial Auditors of RomaniaAudit Financiar1583-58121844-88012025-02-01231(177)18019610.20869/AUDITF/2025/177/005Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future DirectionsSilviu-Ionut BABTAN0Accounting and Audit Department, The Faculty of Economics and Business Administration, Babes-Bolyai University, Cluj-Napoca, RomaniaArtificial Intelligence (AI) is changing real estate valuation with innovative approaches. This article examines several AI methods – Regression Models, Decision Trees, Random Forests, Artificial Neural Networks, and XGBoost – and explores their applications for improving property valuation accuracy and efficiency, with implications for other professions involved, e.g. audit. The author starts by investigating traditional valuation methods' limitations, such as data constraints and subjectivity, and presents how these AI techniques, which are translated in property valuation field as automated valuation methods, tackle these challenges. Regression Models quantify attributes, Decision Trees provide clear insights, Random Forests improve predictions, Artificial Neural Networks design elaborate relationships, and XGBoost furnishes advanced boosting techniques for higher performance. Underscoring that AI is meant to support, not substitute, human assessors, the paper presents how these methods can enhance valuation processes, deliver more reliable valuation reports, and decrease errors, while also exploring future innovations and evolving trends in artificial intelligence for real estate industry and related professions.http://revista.cafr.ro/temp/Article_9792.pdfartificial intelligencereal estate valuationauditautomated valuation techniques methods |
| spellingShingle | Silviu-Ionut BABTAN Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions Audit Financiar artificial intelligence real estate valuation audit automated valuation techniques methods |
| title | Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions |
| title_full | Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions |
| title_fullStr | Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions |
| title_full_unstemmed | Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions |
| title_short | Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions |
| title_sort | reforming real estate valuation for financial auditors with ai an in depth exploration of current methods and future directions |
| topic | artificial intelligence real estate valuation audit automated valuation techniques methods |
| url | http://revista.cafr.ro/temp/Article_9792.pdf |
| work_keys_str_mv | AT silviuionutbabtan reformingrealestatevaluationforfinancialauditorswithaianindepthexplorationofcurrentmethodsandfuturedirections |