Automated ESG Report Analysis by Joint Entity and Relation Extraction

Adrien Ehrhardt; Minh Tuan Nguyen

doi:10.1007/978-3-030-93733-1_23

Automated ESG Report Analysis by Joint Entity and Relation Extraction

Adrien Ehrhardt
, Minh Tuan Nguyen

École Polytechnique

Crédit Agricole Assurances

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

The banking industry has lately been under pressure, notably from regulators and NGOs, to report various Environmental, Societal and Governance (ESG) metrics (e.g., the carbon footprint of loans). For years at Crédit Agricole, a specialized division examined ESG and Corporate Social Responsibility (CSR) reports to ensure, e.g., the bank’s commitment to de-fund coal activities, and companies with social or environmental issues. With both an intensification of the aforementioned exterior pressure, and of the number of companies making such reports publicly available, the tedious process of going through each report has become unsustainable. In this work, we present two adaptations of previously published models for joint entity and relation extraction. We train them on a private dataset consisting in ESG and CSR reports annotated internally at Crédit Agricole. We show that we are able to effectively detect entities such as coal activities and environmental or social issues, as well as relations between these entities, thus enabling the financial industry to quickly grasp the creditworthiness of clients and prospects w.r.t. ESG criteria. The resulting model is provided at https://github.com/adimajo/renard_joint.

Original language	English
Title of host publication	Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings
Editors	Michael Kamp, Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastian Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	325-340
Number of pages	16
ISBN (Print)	9783030937324
DOIs	https://doi.org/10.1007/978-3-030-93733-1_23
Publication status	Published - 1 Jan 2021
Event	21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021 - Virtual, Online Duration: 13 Sept 2021 → 17 Sept 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1525 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021
City	Virtual, Online
Period	13/09/21 → 17/09/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 12 Responsible Consumption and Production

Keywords

NLP
Named Entity Recognition
Relation extraction

Access to Document

10.1007/978-3-030-93733-1_23

Cite this

Ehrhardt, A., & Nguyen, M. T. (2021). Automated ESG Report Analysis by Joint Entity and Relation Extraction. In M. Kamp, M. Kamp, I. Koprinska, A. Bibal, T. Bouadi, B. Frénay, L. Galárraga, J. Oramas, L. Adilova, Y. Krishnamurthy, B. Kang, C. Largeron, J. Lijffijt, T. Viard, P. Welke, M. Ruocco, E. Aune, C. Gallicchio, G. Schiele, F. Pernkopf, M. Blott, H. Fröning, G. Schindler, R. Guidotti, A. Monreale, S. Rinzivillo, P. Biecek, E. Ntoutsi, M. Pechenizkiy, B. Rosenhahn, C. Buckley, D. Cialfi, P. Lanillos, M. Ramstead, T. Verbelen, P. M. Ferreira, G. Andresini, D. Malerba, I. Medeiros, P. Fournier-Viger, M. S. Nawaz, S. Ventura, M. Sun, M. Zhou, V. Bitetta, I. Bordino, A. Ferretti, F. Gullo, G. Ponti, L. Severini, R. Ribeiro, J. Gama, R. Gavaldà, L. Cooper, N. Ghazaleh, J. Richiardi, D. Roqueiro, D. Saldana Miranda, K. Sechidis, ... G. Graça (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings (pp. 325-340). (Communications in Computer and Information Science; Vol. 1525 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-93733-1_23

Ehrhardt, Adrien ; Nguyen, Minh Tuan. / Automated ESG Report Analysis by Joint Entity and Relation Extraction. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings. editor / Michael Kamp ; Michael Kamp ; Irena Koprinska ; Adrien Bibal ; Tassadit Bouadi ; Benoît Frénay ; Luis Galárraga ; José Oramas ; Linara Adilova ; Yamuna Krishnamurthy ; Bo Kang ; Christine Largeron ; Jefrey Lijffijt ; Tiphaine Viard ; Pascal Welke ; Massimiliano Ruocco ; Erlend Aune ; Claudio Gallicchio ; Gregor Schiele ; Franz Pernkopf ; Michaela Blott ; Holger Fröning ; Günther Schindler ; Riccardo Guidotti ; Anna Monreale ; Salvatore Rinzivillo ; Przemyslaw Biecek ; Eirini Ntoutsi ; Mykola Pechenizkiy ; Bodo Rosenhahn ; Christopher Buckley ; Daniela Cialfi ; Pablo Lanillos ; Maxwell Ramstead ; Tim Verbelen ; Pedro M. Ferreira ; Giuseppina Andresini ; Donato Malerba ; Ibéria Medeiros ; Philippe Fournier-Viger ; M. Saqib Nawaz ; Sebastian Ventura ; Meng Sun ; Min Zhou ; Valerio Bitetta ; Ilaria Bordino ; Andrea Ferretti ; Francesco Gullo ; Giovanni Ponti ; Lorenzo Severini ; Rita Ribeiro ; João Gama ; Ricard Gavaldà ; Lee Cooper ; Naghmeh Ghazaleh ; Jonas Richiardi ; Damian Roqueiro ; Diego Saldana Miranda ; Konstantinos Sechidis ; Guilherme Graça. Springer Science and Business Media Deutschland GmbH, 2021. pp. 325-340 (Communications in Computer and Information Science).

@inproceedings{11ed69cfbd6243119727e67e40796893,

title = "Automated ESG Report Analysis by Joint Entity and Relation Extraction",

abstract = "The banking industry has lately been under pressure, notably from regulators and NGOs, to report various Environmental, Societal and Governance (ESG) metrics (e.g., the carbon footprint of loans). For years at Cr{\'e}dit Agricole, a specialized division examined ESG and Corporate Social Responsibility (CSR) reports to ensure, e.g., the bank{\textquoteright}s commitment to de-fund coal activities, and companies with social or environmental issues. With both an intensification of the aforementioned exterior pressure, and of the number of companies making such reports publicly available, the tedious process of going through each report has become unsustainable. In this work, we present two adaptations of previously published models for joint entity and relation extraction. We train them on a private dataset consisting in ESG and CSR reports annotated internally at Cr{\'e}dit Agricole. We show that we are able to effectively detect entities such as coal activities and environmental or social issues, as well as relations between these entities, thus enabling the financial industry to quickly grasp the creditworthiness of clients and prospects w.r.t. ESG criteria. The resulting model is provided at https://github.com/adimajo/renard\_joint.",

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note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021 ; Conference date: 13-09-2021 Through 17-09-2021",

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doi = "10.1007/978-3-030-93733-1\_23",

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editor = "Michael Kamp and Michael Kamp and Irena Koprinska and Adrien Bibal and Tassadit Bouadi and Beno{\^i}t Fr{\'e}nay and Luis Gal{\'a}rraga and Jos{\'e} Oramas and Linara Adilova and Yamuna Krishnamurthy and Bo Kang and Christine Largeron and Jefrey Lijffijt and Tiphaine Viard and Pascal Welke and Massimiliano Ruocco and Erlend Aune and Claudio Gallicchio and Gregor Schiele and Franz Pernkopf and Michaela Blott and Holger Fr{\"o}ning and G{\"u}nther Schindler and Riccardo Guidotti and Anna Monreale and Salvatore Rinzivillo and Przemyslaw Biecek and Eirini Ntoutsi and Mykola Pechenizkiy and Bodo Rosenhahn and Christopher Buckley and Daniela Cialfi and Pablo Lanillos and Maxwell Ramstead and Tim Verbelen and Ferreira, \{Pedro M.\} and Giuseppina Andresini and Donato Malerba and Ib{\'e}ria Medeiros and Philippe Fournier-Viger and Nawaz, \{M. Saqib\} and Sebastian Ventura and Meng Sun and Min Zhou and Valerio Bitetta and Ilaria Bordino and Andrea Ferretti and Francesco Gullo and Giovanni Ponti and Lorenzo Severini and Rita Ribeiro and Jo{\~a}o Gama and Ricard Gavald{\`a} and Lee Cooper and Naghmeh Ghazaleh and Jonas Richiardi and Damian Roqueiro and \{Saldana Miranda\}, Diego and Konstantinos Sechidis and Guilherme Gra{\c c}a",

booktitle = "Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings",

}

Ehrhardt, A & Nguyen, MT 2021, Automated ESG Report Analysis by Joint Entity and Relation Extraction. in M Kamp, M Kamp, I Koprinska, A Bibal, T Bouadi, B Frénay, L Galárraga, J Oramas, L Adilova, Y Krishnamurthy, B Kang, C Largeron, J Lijffijt, T Viard, P Welke, M Ruocco, E Aune, C Gallicchio, G Schiele, F Pernkopf, M Blott, H Fröning, G Schindler, R Guidotti, A Monreale, S Rinzivillo, P Biecek, E Ntoutsi, M Pechenizkiy, B Rosenhahn, C Buckley, D Cialfi, P Lanillos, M Ramstead, T Verbelen, PM Ferreira, G Andresini, D Malerba, I Medeiros, P Fournier-Viger, MS Nawaz, S Ventura, M Sun, M Zhou, V Bitetta, I Bordino, A Ferretti, F Gullo, G Ponti, L Severini, R Ribeiro, J Gama, R Gavaldà, L Cooper, N Ghazaleh, J Richiardi, D Roqueiro, D Saldana Miranda, K Sechidis & G Graça (eds), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings. Communications in Computer and Information Science, vol. 1525 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 325-340, 21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021, Virtual, Online, 13/09/21. https://doi.org/10.1007/978-3-030-93733-1_23

Automated ESG Report Analysis by Joint Entity and Relation Extraction. / Ehrhardt, Adrien; Nguyen, Minh Tuan.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings. ed. / Michael Kamp; Michael Kamp; Irena Koprinska; Adrien Bibal; Tassadit Bouadi; Benoît Frénay; Luis Galárraga; José Oramas; Linara Adilova; Yamuna Krishnamurthy; Bo Kang; Christine Largeron; Jefrey Lijffijt; Tiphaine Viard; Pascal Welke; Massimiliano Ruocco; Erlend Aune; Claudio Gallicchio; Gregor Schiele; Franz Pernkopf; Michaela Blott; Holger Fröning; Günther Schindler; Riccardo Guidotti; Anna Monreale; Salvatore Rinzivillo; Przemyslaw Biecek; Eirini Ntoutsi; Mykola Pechenizkiy; Bodo Rosenhahn; Christopher Buckley; Daniela Cialfi; Pablo Lanillos; Maxwell Ramstead; Tim Verbelen; Pedro M. Ferreira; Giuseppina Andresini; Donato Malerba; Ibéria Medeiros; Philippe Fournier-Viger; M. Saqib Nawaz; Sebastian Ventura; Meng Sun; Min Zhou; Valerio Bitetta; Ilaria Bordino; Andrea Ferretti; Francesco Gullo; Giovanni Ponti; Lorenzo Severini; Rita Ribeiro; João Gama; Ricard Gavaldà; Lee Cooper; Naghmeh Ghazaleh; Jonas Richiardi; Damian Roqueiro; Diego Saldana Miranda; Konstantinos Sechidis; Guilherme Graça. Springer Science and Business Media Deutschland GmbH, 2021. p. 325-340 (Communications in Computer and Information Science; Vol. 1525 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Automated ESG Report Analysis by Joint Entity and Relation Extraction

AU - Ehrhardt, Adrien

AU - Nguyen, Minh Tuan

PY - 2021/1/1

Y1 - 2021/1/1

N2 - The banking industry has lately been under pressure, notably from regulators and NGOs, to report various Environmental, Societal and Governance (ESG) metrics (e.g., the carbon footprint of loans). For years at Crédit Agricole, a specialized division examined ESG and Corporate Social Responsibility (CSR) reports to ensure, e.g., the bank’s commitment to de-fund coal activities, and companies with social or environmental issues. With both an intensification of the aforementioned exterior pressure, and of the number of companies making such reports publicly available, the tedious process of going through each report has become unsustainable. In this work, we present two adaptations of previously published models for joint entity and relation extraction. We train them on a private dataset consisting in ESG and CSR reports annotated internally at Crédit Agricole. We show that we are able to effectively detect entities such as coal activities and environmental or social issues, as well as relations between these entities, thus enabling the financial industry to quickly grasp the creditworthiness of clients and prospects w.r.t. ESG criteria. The resulting model is provided at https://github.com/adimajo/renard_joint.

AB - The banking industry has lately been under pressure, notably from regulators and NGOs, to report various Environmental, Societal and Governance (ESG) metrics (e.g., the carbon footprint of loans). For years at Crédit Agricole, a specialized division examined ESG and Corporate Social Responsibility (CSR) reports to ensure, e.g., the bank’s commitment to de-fund coal activities, and companies with social or environmental issues. With both an intensification of the aforementioned exterior pressure, and of the number of companies making such reports publicly available, the tedious process of going through each report has become unsustainable. In this work, we present two adaptations of previously published models for joint entity and relation extraction. We train them on a private dataset consisting in ESG and CSR reports annotated internally at Crédit Agricole. We show that we are able to effectively detect entities such as coal activities and environmental or social issues, as well as relations between these entities, thus enabling the financial industry to quickly grasp the creditworthiness of clients and prospects w.r.t. ESG criteria. The resulting model is provided at https://github.com/adimajo/renard_joint.

KW - NLP

KW - Named Entity Recognition

KW - Relation extraction

U2 - 10.1007/978-3-030-93733-1_23

DO - 10.1007/978-3-030-93733-1_23

M3 - Conference contribution

AN - SCOPUS:85126251657

SN - 9783030937324

T3 - Communications in Computer and Information Science

SP - 325

EP - 340

BT - Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings

A2 - Kamp, Michael

A2 - Koprinska, Irena

A2 - Bibal, Adrien

A2 - Bouadi, Tassadit

A2 - Frénay, Benoît

A2 - Galárraga, Luis

A2 - Oramas, José

A2 - Adilova, Linara

A2 - Krishnamurthy, Yamuna

A2 - Kang, Bo

A2 - Largeron, Christine

A2 - Lijffijt, Jefrey

A2 - Viard, Tiphaine

A2 - Welke, Pascal

A2 - Ruocco, Massimiliano

A2 - Aune, Erlend

A2 - Gallicchio, Claudio

A2 - Schiele, Gregor

A2 - Pernkopf, Franz

A2 - Blott, Michaela

A2 - Fröning, Holger

A2 - Schindler, Günther

A2 - Guidotti, Riccardo

A2 - Monreale, Anna

A2 - Rinzivillo, Salvatore

A2 - Biecek, Przemyslaw

A2 - Ntoutsi, Eirini

A2 - Pechenizkiy, Mykola

A2 - Rosenhahn, Bodo

A2 - Buckley, Christopher

A2 - Cialfi, Daniela

A2 - Lanillos, Pablo

A2 - Ramstead, Maxwell

A2 - Verbelen, Tim

A2 - Ferreira, Pedro M.

A2 - Andresini, Giuseppina

A2 - Malerba, Donato

A2 - Medeiros, Ibéria

A2 - Fournier-Viger, Philippe

A2 - Nawaz, M. Saqib

A2 - Ventura, Sebastian

A2 - Sun, Meng

A2 - Zhou, Min

A2 - Bitetta, Valerio

A2 - Bordino, Ilaria

A2 - Ferretti, Andrea

A2 - Gullo, Francesco

A2 - Ponti, Giovanni

A2 - Severini, Lorenzo

A2 - Ribeiro, Rita

A2 - Gama, João

A2 - Gavaldà, Ricard

A2 - Cooper, Lee

A2 - Ghazaleh, Naghmeh

A2 - Richiardi, Jonas

A2 - Roqueiro, Damian

A2 - Saldana Miranda, Diego

A2 - Sechidis, Konstantinos

A2 - Graça, Guilherme

PB - Springer Science and Business Media Deutschland GmbH

T2 - 21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021

Y2 - 13 September 2021 through 17 September 2021

ER -

Ehrhardt A, Nguyen MT. Automated ESG Report Analysis by Joint Entity and Relation Extraction. In Kamp M, Kamp M, Koprinska I, Bibal A, Bouadi T, Frénay B, Galárraga L, Oramas J, Adilova L, Krishnamurthy Y, Kang B, Largeron C, Lijffijt J, Viard T, Welke P, Ruocco M, Aune E, Gallicchio C, Schiele G, Pernkopf F, Blott M, Fröning H, Schindler G, Guidotti R, Monreale A, Rinzivillo S, Biecek P, Ntoutsi E, Pechenizkiy M, Rosenhahn B, Buckley C, Cialfi D, Lanillos P, Ramstead M, Verbelen T, Ferreira PM, Andresini G, Malerba D, Medeiros I, Fournier-Viger P, Nawaz MS, Ventura S, Sun M, Zhou M, Bitetta V, Bordino I, Ferretti A, Gullo F, Ponti G, Severini L, Ribeiro R, Gama J, Gavaldà R, Cooper L, Ghazaleh N, Richiardi J, Roqueiro D, Saldana Miranda D, Sechidis K, Graça G, editors, Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 325-340. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-93733-1_23

Automated ESG Report Analysis by Joint Entity and Relation Extraction

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this