Research outputs

Selected research outputs

An explainable AI decision-support-system to automate loan underwriting (Journal article - 2020)
A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans (Conference Paper - 2023)
Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools (Journal article - 2024)
Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm (Journal article - 2024)
Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance (Journal article - 2021)

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2026

Post-Quantum Secure Federated DeFi for Inclusive Banking

Sachan, S., Fickett, D., Buchinger, R., & Miller, T. (2026). Post-Quantum Secure Federated DeFi for Inclusive Banking. In 2026 IEEE Conference on Artificial Intelligence (CAI) (pp. 959-964). IEEE. doi:10.1109/cai68641.2026.11536585

DOI: 10.1109/cai68641.2026.11536585
: Conference Paper

2025

DeFi TrustBoost: Blockchain and AI for Trustworthy Decentralized Financial Decisions

: Preprint

AI Collaboration to Counteract Flaws in High-Stakes Financial Decisions

Sachan, S. (2025). AI Collaboration to Counteract Flaws in High-Stakes Financial Decisions (AIFS0061). Parliamentary committees of the United Kingdom. Retrieved from https://committees.parliament.uk/writtenevidence/140288/pdf/

: Report

PRIVACY-PRESERVING FEDERATED ANALYSIS OF AGRICULTURAL LOAN AND INSURANCE RISK

Lar, E. T. O., Sachan, S., & Miller, T. (2025). PRIVACY-PRESERVING FEDERATED ANALYSIS OF AGRICULTURAL LOAN AND INSURANCE RISK. In Iet Conference Proceedings Vol. 2025 (pp. 98-99). doi:10.1049/icp.2025.2969

DOI: 10.1049/icp.2025.2969
: Conference Paper

Responsible LLM Deployment for High-Stake Decisions by Decentralized Technologies and Human-AI Interactions

Sachan, S., Miller, T., & Nguyen, M. P. (2025). Responsible LLM Deployment for High-Stake Decisions by Decentralized Technologies and Human-AI Interactions. In Ichms 2025 5th IEEE International Conference on Human Machine Systems AI and Large Language Models Transforming Human Machine Interactions (pp. 99-104). doi:10.1109/ICHMS65439.2025.11154208

DOI: 10.1109/ICHMS65439.2025.11154208
: Conference Paper

2024

Optimal Data-Driven Strategy for In-House and Outsourced Technological Innovations by Open Banking APIs

Dezem, V., Sachan, S., Macedo, M., & Longaray, A. A. (2024). Optimal data-driven strategy for in-house and outsourced technological innovations by open banking APIs. FUTURE BUSINESS JOURNAL, 10(1). doi:10.1186/s43093-024-00397-3

DOI: 10.1186/s43093-024-00397-3
: Journal article

Secure and Transparent Lawyer-in-the-Loop Medico-Legal Insurance Decisions by Explainable AI and Blockchain Technology

Sachan, S., & Fairclough, G. (2024). Secure and Transparent Lawyer-in-the-Loop Medico-Legal Insurance Decisions by Explainable AI and Blockchain Technology. In S. Li (Ed.), 10th International Conference on Information Management (ICIM) Vol. 2102. University of Cambridge: Springer Nature Switzerland AG. doi:10.1007/978-3-031-64359-0_3

DOI: 10.1007/978-3-031-64359-0_3
: Conference Paper

Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm

Sachan, S., Almaghrabi, F., Yang, J. -B., & Xu, D. -L. (2024). Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm. International Review of Financial Analysis. doi:10.1016/j.irfa.2024.103149

DOI: 10.1016/j.irfa.2024.103149
: Journal article

Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools

Sachan, S., & Liu (Lisa), X. (2024). Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 129. doi:10.1016/j.engappai.2023.107666

DOI: 10.1016/j.engappai.2023.107666
: Journal article

Blockchain for Ethical and Transparent Generative AI Utilization by Banking and Finance Lawyers; at World Conference on eXplainable Artificial Intelligence (XAI)

Sachan, S., Dezem, V., & Fickett, D. (2024). Blockchain for Ethical and Transparent Generative AI Utilization by Banking and Finance Lawyers. In EXPLAINABLE ARTIFICIAL INTELLIGENCE, PT III, XAI 2024 Vol. 2155 (pp. 319-333). doi:10.1007/978-3-031-63800-8_16

DOI: 10.1007/978-3-031-63800-8_16
: Conference Paper

2023

The Future of Money: What We Need To Know

Sachan, S. (2023). The Future of Money: What We Need To Know. Retrieved from https://e.issuu.com/embed.html?d=well_connected_july_23&u=benham

: Website content

A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans

Sachan, S., Fickett, D. S., Kyaw, N. E. E., Purkayastha, R. S., & Renimol, S. (2023). A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans. In 2023 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN AND CRYPTOCURRENCY, ICBC. doi:10.1109/ICBC56567.2023.10174925

DOI: 10.1109/ICBC56567.2023.10174925
: Conference Paper

Integration of Explainable Deep Neural Network with Blockchain Technology: Medical Indemnity Insurance

Sachan, S., & Muwanga, J. (2023). Integration of Explainable Deep Neural Network with Blockchain Technology: Medical Indemnity Insurance. In Ceur Workshop Proceedings Vol. 3554 (pp. 123-128).

: Conference Paper

2022

Fintech Lending Decisions: An Interpretable Knowledge-Base System for Retail and Commercial Loans

Sachan, S. (2022). Fintech Lending Decisions: An Interpretable Knowledge-Base System for Retail and Commercial Loans. In Unknown Book (Vol. 1602, pp. 128-140). doi:10.1007/978-3-031-08974-9_10

DOI: 10.1007/978-3-031-08974-9_10
: Chapter

2021

Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance

Sachan, S., Almaghrabi, F., Yang, J. -B., & Xu, D. -L. (2021). Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance. EXPERT SYSTEMS WITH APPLICATIONS, 185. doi:10.1016/j.eswa.2021.115597

DOI: 10.1016/j.eswa.2021.115597
: Journal article

2020

Global and local interpretability of belief rule base

Sachan, S., Yang, J. B., & Xu, D. L. (2020). Global and local interpretability of belief rule base. In Unknown Book (Vol. 12, pp. 68-75). Retrieved from https://www.webofscience.com/

DOI: 10.1142/9789811223334_0009
: Chapter

Explainable Artificial Intelligence for Digital Forensics: Opportunities, Challenges and a Drug Testing Case Study

Kelly, L., Sachan, S., Ni, L., Almaghrabi, F., Allmendinger, R., & Chen, Y. -W. (2020). Explainable Artificial Intelligence for Digital Forensics: Opportunities, Challenges and a Drug Testing Case Study. In Digital Forensic Science. IntechOpen. doi:10.5772/intechopen.93310

DOI: 10.5772/intechopen.93310
: Chapter

Generalized Stochastic Petri-Net Algorithm with Fuzzy Parameters to Evaluate Infrastructure Asset Management Policy

Sachan, S., & Donchak, N. (2020). Generalized Stochastic Petri-Net Algorithm with Fuzzy Parameters to Evaluate Infrastructure Asset Management Policy. In 2020 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE). doi:10.1109/fuzz48607.2020.9177562

DOI: 10.1109/fuzz48607.2020.9177562
: Conference Paper

An explainable AI decision-support-system to automate loan underwriting

Sachan, S., Yang, J. -B., Xu, D. -L., Benavides, D. E., & Li, Y. (2020). An explainable AI decision-support-system to automate loan underwriting. EXPERT SYSTEMS WITH APPLICATIONS, 144. doi:10.1016/j.eswa.2019.113100

DOI: 10.1016/j.eswa.2019.113100
: Journal article

2019

Maximum likelihood evidential reasoning-based hierarchical inference with incomplete data

Liu, X., Sachan, S., Yang, J. -B., & Xu, D. -L. (2019). Maximum Likelihood Evidential Reasoning-Based Hierarchical Inference with Incomplete Data. In 2019 25TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 42-47). doi:10.23919/iconac.2019.8895062

DOI: 10.23919/IConAC.2019.8895062
: Conference Paper

Multi-segment deep convolution neural networks for classification of faults in sensors at railway point systems

Sachan, S., & Donchak, N. (2019). Multi-Segment Deep Convolution Neural Networks for Classification of Faults in Sensors at Railway Point Systems. In 2019 25TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 147-152). doi:10.23919/iconac.2019.8895081

DOI: 10.23919/IConAC.2019.8895081
: Conference Paper

Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables

Sachan, S., & Zhou, C. (2019). Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables. Life Cycle Reliability and Safety Engineering, 8(2), 117-127. doi:10.1007/s41872-019-00074-3

DOI: 10.1007/s41872-019-00074-3
: Journal article

2018

A hybrid belief rule based decision support system for assessing credit risk for mortgage lending

Sachan, S., Yang, J. -B., & Xu, D. -L. (2018). A hybrid belief rule based decision support system for assessing credit risk for mortgage lending. In https://www.euro-online.org/media_site/reports/EURO29_AB.pdf.

: Conference Paper

Comments from young scholars: Can machines completely replace humans in manufacturing processes?

Yang, S. (2018). Comments from young scholars: Can machines completely replace humans in manufacturing processes?. FRONTIERS OF ENGINEERING MANAGEMENT, 5(4), 541-547. doi:10.15302/J-FEM-2018207

DOI: 10.15302/j-fem-2018207
: Journal article

2017

Multiple Correspondence Analysis to Study Failures in a Diverse Population of a Cable

Sachan, S., Zhou, C., Wen, R., Sun, W., & Song, C. (2017). Multiple Correspondence Analysis to Study Failures in a Diverse Population of a Cable. IEEE TRANSACTIONS ON POWER DELIVERY, 32(4), 1696-1704. doi:10.1109/TPWRD.2016.2615470

DOI: 10.1109/TPWRD.2016.2615470
: Journal article

2016

Cost Effective Replacement of Power Cables by Stochastic Dynamic Programming Approach

Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2016). Cost Effective Replacement of Power Cables by Stochastic Dynamic Programming Approach. In 2016 INTERNATIONAL CONFERENCE ON CONDITION MONITORING AND DIAGNOSIS (CMD) (pp. 299-302). Retrieved from https://www.webofscience.com/

: Conference Paper

Stochastic dynamic programming approach for proactive replacement of power cables

Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2016). Stochastic dynamic programming approach for proactive replacement of power cables. In Iet Conference Publications Vol. 2016.

: Conference Paper

2015

Failure prediction of power cables using failure history and operational conditions

Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2015). Failure prediction of power cables using failure history and operational conditions. In Proceedings of the IEEE International Conference on Properties and Applications of Dielectric Materials Vol. 2015-October (pp. 380-383). doi:10.1109/ICPADM.2015.7295288

DOI: 10.1109/ICPADM.2015.7295288
: Conference Paper

Prediction of power cable failure rate based on failure history and operational conditions

Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2015). Prediction of power cable failure rate based on failure history and operational conditions. In http://www.jicable.org/2015/prg_sessions_A1_E10.php. Versailles, France.

: Conference Paper

A stochastic electrothermal degradation model of power cables

Sachan, S., Wen, R., Xiang, Y., Yao, L., & Zhou, C. (2015). A stochastic electrothermal degradation model of power cables. Gaodianya Jishu High Voltage Engineering, 41(4), 1178-1187. doi:10.13336/j.1003-6520.hve.2015.04.015

DOI: 10.13336/j.1003-6520.hve.2015.04.015
: Journal article