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Basel III FRTB: data pooling innovation to lower capital charges
BACKGROUND: Anticipated to overhaul the structure of market risk teams, IT teams, and trading desks within banks by 2023, Basel III's Fundamental Review of the Trading Book requirements will also increase capital charges banks will incur globally. The case study focuses on describing what is ne...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116640/ https://www.ncbi.nlm.nih.gov/pubmed/35024281 http://dx.doi.org/10.1186/s40854-021-00252-2 |
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author | Huang, Jimmy Yicheng |
author_facet | Huang, Jimmy Yicheng |
author_sort | Huang, Jimmy Yicheng |
collection | PubMed |
description | BACKGROUND: Anticipated to overhaul the structure of market risk teams, IT teams, and trading desks within banks by 2023, Basel III's Fundamental Review of the Trading Book requirements will also increase capital charges banks will incur globally. The case study focuses on describing what is needed with regards to the risk factor eligibility test (RFET) as well as for implementing a data pool to lower capital charges. By establishing a consortium of banks per region to implement a data pooling solution, participants can prove a wider breadth of modellable risk factors per asset class and use the Internal Models Approach (IMA) of valuing risk to lower capital charge requirements significantly. CASE DESCRIPTION: First, a description on the historical context surrounding the Fundamental Review of the Trading Book rules and the business requirements needed to comply with the risk factor eligibility test is made. Then an examination is conducted on the innovative data pooling initiative implemented by CanDeal, TickSmith Corp., and the 6 largest Canadian banks to lower capital charge requirements under the Fundamental Review of the Trading Book. DISCUSSION AND EVALUATION: A description is made on what types of data, expertise, and technology is needed to calculate for risk factor modellability. It is up to each firm to decide if the benefits to using the Internal Models Approach to lower capital charges outweighs implementation and running costs of the underlying data platform. Implementing a data pool for each region comes with challenges that include anti-competition law that may block the initiative, varied benefits to each competitive participant, and data security concerns. CONCLUSION: It is evident that the data pool innovation provides benefits to lowering capital charges as the Canadian banks have seen an increase of modellability by several factors using the sample bond asset class. While each firm must still determine internally if the benefits outweighs the technological costs they will incur, it is clear that regulators are pushing for increased data retention and scrutiny. |
format | Online Article Text |
id | pubmed-8116640 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-81166402021-05-13 Basel III FRTB: data pooling innovation to lower capital charges Huang, Jimmy Yicheng Financ Innov Case Study BACKGROUND: Anticipated to overhaul the structure of market risk teams, IT teams, and trading desks within banks by 2023, Basel III's Fundamental Review of the Trading Book requirements will also increase capital charges banks will incur globally. The case study focuses on describing what is needed with regards to the risk factor eligibility test (RFET) as well as for implementing a data pool to lower capital charges. By establishing a consortium of banks per region to implement a data pooling solution, participants can prove a wider breadth of modellable risk factors per asset class and use the Internal Models Approach (IMA) of valuing risk to lower capital charge requirements significantly. CASE DESCRIPTION: First, a description on the historical context surrounding the Fundamental Review of the Trading Book rules and the business requirements needed to comply with the risk factor eligibility test is made. Then an examination is conducted on the innovative data pooling initiative implemented by CanDeal, TickSmith Corp., and the 6 largest Canadian banks to lower capital charge requirements under the Fundamental Review of the Trading Book. DISCUSSION AND EVALUATION: A description is made on what types of data, expertise, and technology is needed to calculate for risk factor modellability. It is up to each firm to decide if the benefits to using the Internal Models Approach to lower capital charges outweighs implementation and running costs of the underlying data platform. Implementing a data pool for each region comes with challenges that include anti-competition law that may block the initiative, varied benefits to each competitive participant, and data security concerns. CONCLUSION: It is evident that the data pool innovation provides benefits to lowering capital charges as the Canadian banks have seen an increase of modellability by several factors using the sample bond asset class. While each firm must still determine internally if the benefits outweighs the technological costs they will incur, it is clear that regulators are pushing for increased data retention and scrutiny. Springer Berlin Heidelberg 2021-05-13 2021 /pmc/articles/PMC8116640/ /pubmed/35024281 http://dx.doi.org/10.1186/s40854-021-00252-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Case Study Huang, Jimmy Yicheng Basel III FRTB: data pooling innovation to lower capital charges |
title | Basel III FRTB: data pooling innovation to lower capital charges |
title_full | Basel III FRTB: data pooling innovation to lower capital charges |
title_fullStr | Basel III FRTB: data pooling innovation to lower capital charges |
title_full_unstemmed | Basel III FRTB: data pooling innovation to lower capital charges |
title_short | Basel III FRTB: data pooling innovation to lower capital charges |
title_sort | basel iii frtb: data pooling innovation to lower capital charges |
topic | Case Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116640/ https://www.ncbi.nlm.nih.gov/pubmed/35024281 http://dx.doi.org/10.1186/s40854-021-00252-2 |
work_keys_str_mv | AT huangjimmyyicheng baseliiifrtbdatapoolinginnovationtolowercapitalcharges |