LEADER 03936nam 22005055 450 001 9911015634303321 005 20250712130226.0 010 $a9783031955433$b(electronic bk.) 010 $z9783031955426 024 7 $a10.1007/978-3-031-95543-3 035 $a(MiAaPQ)EBC32207846 035 $a(Au-PeEL)EBL32207846 035 $a(CKB)39633599700041 035 $a(DE-He213)978-3-031-95543-3 035 $a(EXLCZ)9939633599700041 100 $a20250712d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Risk of Artificial Intelligence in Credit Ratings $eExploring the Efficiency, Development and Impact /$fby Daniel Cash, Nataliya Tkachenko 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Palgrave Macmillan,$d2025. 215 $a1 online resource (112 pages) 311 08$aPrint version: Cash, Daniel The Risk of Artificial Intelligence in Credit Ratings Cham : Palgrave Macmillan,c2025 9783031955426 327 $aChapter 1 Introduction -- Chapter 2 Generative AI: Concept, Applications, and Implications -- Chapter 3 The Growing Adoption of AI within the World of Credit Ratings -- Chapter 4 The Regulatory Perspective -- Chapter 5 Recommendations -- Chapter 6 Conclusion. 330 $aAs the leading credit rating agencies begin to heavily invest in the adoption of artificial intelligence, historic systemic failures serve as a reminder of the effect of mis-regulation and misdiagnosis in the credit rating world. As the industry turns towards technologies that can massively enhance the speed, efficiency, but also the temptation to transgress within the credit rating world, there are critical questions that need to be asked to shape the response that will be needed. For regulators and policymakers, the multivariant threat that the adoption of artificial intelligence within the credit rating world poses will require an extensive but nuanced response to counter it. This book presents these issues, reveals intricate implications, and provides for a considered response that regulators and policymakers should consider. Daniel Cash is Reader in Law at Aston University and a Senior Fellow at the United Nations University Centre for Policy Research. Daniel?s research is exclusively concerned with the regulation of the credit rating industry, with a wider focus on the financial regulation of financial service providers, and the relationship between the financial sector and its impact upon society. He has authored a number of books, edited collections, and articles on the credit rating industry specifically. Nataliya Tkachenko is an AI strategy lead for sustainable finance at the AI Centre of Excellence (Lloyds Banking Group). She is also a visiting fellow at the Cambridge Centre for Finance, Technology and Regulation (University of Cambridge Judge Business School) and an Executive Director of UK Multimodal AI Network, funded by EPSRC. She obtained her PhD in Computer Science from the University of Warwick in 2019, and continues to pursue her interest in how AI transforms financial industry, what are the biggest opportunities and associated risks. She?s part of AI Assurance working groups within DRCF and IOSCO. 606 $aFinancial services industry 606 $aArtificial intelligence 606 $aFinancial Services 606 $aArtificial Intelligence 615 0$aFinancial services industry. 615 0$aArtificial intelligence. 615 14$aFinancial Services. 615 24$aArtificial Intelligence. 676 $a332.17 700 $aCash$b Daniel$0848303 701 $aTkachenko$b Nataliya$01833124 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9911015634303321 996 $aThe Risk of Artificial Intelligence in Credit Ratings$94408045 997 $aUNINA