Credit Risk Measurement, Decision Analysis, Transformation and Upgrading for Financial Big Data

Wu, Wenrui

doi:10.1155/2022/8942773

Cited by 3 publications

(1 citation statement)

References 79 publications

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“…Tis study focuses on the assessment of partial or hidden risks. According to [71], knowledge discovery based on MCDM methods is a widely emerging feld of the risk management of fnancial institutions. Combining the PRISM method with Guilford's pairwise comparison is an alternative to the original PRISM method, which uses deterministic scales for assessing the FMEA factors.…”

Section: Discussion and Managerial Implicationsmentioning

confidence: 99%

Compliance Risk Assessment in the Banking Sector: Application of a Novel Pairwise Comparison-Based PRISM Method

2023

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Up-to-date compliance management uses a risk-based approach based on international standards. In addition to techniques and practices, implementing compliance measures is determined by principles and culture. Compliance risk assessment is an evolving field in theory and practice. Compliance risk management is complex and highly dependent on the decisions of experts. This article presents a new compliance risk assessment method based on a commercial banking case study. In the study, the Guilford method is used to extend the Partial Risk Map (PRISM) assessment technique, and the steps of the proposed pairwise comparison-based PRISM method are described in detail. Since risk assessment is critical to the operation and development of compliance management systems, the proposed risk assessment method involves testing individual evaluations’ consistency and the results’ robustness. The best-fitting and outlier experts can be identified based on testing the impact of individual expert rankings on the aggregated ranking. The main finding is that top partial risks can be identified by applying the proposed pairwise comparison-based PRISM technique; therefore, possible optimal risk mitigation strategies and measures can be designed.

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Section: Discussion and Managerial Implicationsmentioning

confidence: 99%

Compliance Risk Assessment in the Banking Sector: Application of a Novel Pairwise Comparison-Based PRISM Method

2023

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Optimizing bank credit risk assessment models using big data analytics

Yang,

2024

Applied Mathematics and Nonlinear Sciences

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With the strong promotion of financial globalization and marketization and the rapid development of financial industry innovation, credit risk management is becoming an important work that banks need to pay more and more attention to. This paper focuses on the construction of the bank credit risk model to carry out research. First of all, according to the credit characteristics selection method, the optimal indicators are combined with the indicators for the correlation test of variables. On this basis, the sample data is calculated using the up-sampling method of SMOTE to complete the algorithm and sampling. After obtaining the data, data preprocessing is carried out using the MinMaxScaler scaler method, and the processed data is inputted into the improved momentum BP neural network to complete the credit risk assessment. Profiling with risk feature data, it is obtained that each feature is not a separate individual from the other. They are interdependent and connected and have obvious correlations. For example, there are 47 features in the dataset with sample missing ratios greater than 0.97, which is too high and indicates an invalid feature. The results of the study show that SMOTE’s up-sampling method and Momentum BP algorithm can quickly utilize big data to provide a more accurate decision basis for bank credit risk assessment.

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Presentation of DeMa (Decision Support Software and Database for Wellfield Management) and Its Application for the Wadi Al Arab Wellfield

Alqadi

Dwairi

Merchán-Rivera

et al. 2023

Water

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This article aims to present the structure and the workflow of a new software DeMa (Decision Support Software and Database for Wellfield Management), to support wellfield managers in their decision-making processes. There is a recognized need to improve the management of groundwater resources, especially with the increased demand for fresh water in arid and semi-arid regions. DeMa differentiates from other available software, by combining data collected for the well’s maintenance, operation, design, installations, and cost data with the collected hydrological field measurements. Additionally, DeMa links the different information and provides an effective graphical representation of the data. We applied the software to the Wadi Al Arab wellfield case study to support wellfield managers in the decision-making process of three typical problems: identification of missing data and information concerning the wells, identification of maintenance needs for a well, and identification of a suitable location for a new well. In the application to the Wadi Al Arab wellfield (Jordan), we collected data and documents from the Yarmouk Water Company (YWC), the Jordan Ministry of Water and Irrigation (MWI), and private drilling companies. The software application highlights the beneficial effects of the digitalization of water resources management by improving data availability and management and achieving data and research-based decisions on the wellfield.

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Credit Risk Measurement, Decision Analysis, Transformation and Upgrading for Financial Big Data

Cited by 3 publications

References 79 publications

Compliance Risk Assessment in the Banking Sector: Application of a Novel Pairwise Comparison-Based PRISM Method

Compliance Risk Assessment in the Banking Sector: Application of a Novel Pairwise Comparison-Based PRISM Method

Optimizing bank credit risk assessment models using big data analytics

Presentation of DeMa (Decision Support Software and Database for Wellfield Management) and Its Application for the Wadi Al Arab Wellfield

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