The Experts below are selected from a list of 156 Experts worldwide ranked by ideXlab platform

Sang Chan Park - One of the best experts on this subject based on the ideXlab platform.

  • service improvement by business process management using customer complaints in financial service industry
    Expert Systems With Applications, 2011
    Co-Authors: Chong Un Pyon, Jiyoung Woo, Sang Chan Park
    Abstract:

    In financial service industry, service improvement should be considered from process viewpoint and customer viewpoint because the value creation is ultimately linked with internal business processes on the back office and customers are involved as a co-producer of value. In this perspective, customer complaints through call centers are adequate to support the analysis for service improvement in financial service industry. In this study, we propose a web-based decision support system for business process management employing customer complaints, namely Voice of the Customer (VOC), and its handling data for service improvement. It involves VOC conversion for data enrichment and includes analysis of summarization, exception and comparison. The proposed system is evaluated on a major Credit Card Company in South Korea.

  • Visualization method for customer targeting using customer map
    Expert Systems with Applications, 2005
    Co-Authors: Jiyoung Woo, Sung Min Bae, Sang Chan Park
    Abstract:

    An important issue in customer-oriented marketing area is target selection which enables the determination of potential customers. In this paper, we suggest a novel customer targeting method: customer map for a service industry. The customer map is the visualization method for customer targeting. It depicts value distribution across customer needs and customer characteristics. To develop the customer map, we integrate numerous customer data from various data sources, perform data analyses using data mining techniques, and finally visualize the information derived by the former analyses. The customer map helps decision makers to build customer-oriented strategy under the unified goal of customer targeting. It also affords to monitor and perceive real time state and the change of customer value distribution based on their information without preconception. We apply the customer map to a Credit Card Company, build web-based prototype system for the customer map and acquire managerial implications from this study.

Philipp Jovanovic - One of the best experts on this subject based on the ideXlab platform.

  • nonce disrespecting adversaries practical forgery attacks on gcm in tls
    WOOT'16 Proceedings of the 10th USENIX Conference on Offensive Technologies, 2016
    Co-Authors: Hanno Bock, Aaron Zauner, Sean Devlin, Juraj Somorovsky, Philipp Jovanovic
    Abstract:

    We investigate nonce reuse issues with the GCM block cipher mode as used in TLS and focus in particular on AES-GCM, the most widely deployed variant. With an Internet-wide scan we identified 184 HTTPS servers repeating nonces, which fully breaks the authenticity of the connections. Affected servers include large corporations, financial institutions, and a Credit Card Company. We present a proof of concept of our attack allowing to violate the authenticity of affected HTTPS connections which in turn can be utilized to inject seemingly valid content into encrypted sessions. Furthermore, we discovered over 70,000 HTTPS servers using random nonces, which puts them at risk of nonce reuse, in the unlikely case that large amounts of data are sent via the same session.

  • WOOT - Nonce-disrespecting adversaries: practical forgery attacks on GCM in TLS
    2016
    Co-Authors: Hanno Bock, Aaron Zauner, Sean Devlin, Juraj Somorovsky, Philipp Jovanovic
    Abstract:

    We investigate nonce reuse issues with the GCM block cipher mode as used in TLS and focus in particular on AES-GCM, the most widely deployed variant. With an Internet-wide scan we identified 184 HTTPS servers repeating nonces, which fully breaks the authenticity of the connections. Affected servers include large corporations, financial institutions, and a Credit Card Company. We present a proof of concept of our attack allowing to violate the authenticity of affected HTTPS connections which in turn can be utilized to inject seemingly valid content into encrypted sessions. Furthermore, we discovered over 70,000 HTTPS servers using random nonces, which puts them at risk of nonce reuse, in the unlikely case that large amounts of data are sent via the same session.

Antitrust Division - One of the best experts on this subject based on the ideXlab platform.

Henrique Luiz Corrêa - One of the best experts on this subject based on the ideXlab platform.

  • A two-stage fuzzy neural approach for Credit risk assessment in a Brazilian Credit Card Company
    Applied Soft Computing, 2020
    Co-Authors: Diego Paganoti Fonseca, Peter Wanke, Henrique Luiz Corrêa
    Abstract:

    Abstract This study explores and evaluates the use of soft computing systems for clients’ Credit risk assessment in a Brazilian private Credit Card provider through the development of an innovative two-stage process, both involving soft computing techniques (fuzzy and neural networks). We use commercially available Credit score ratings both in the development of our method and for benchmarking. After describing the development of our method, we present a discussion about the comparison of performances of our method and a number of other Credit scoring methods described in literature (for e.g. statistical and soft computing-based). One of the analyzed existing methods for instance involves the use of a soft computing algorithm only – Artificial Neural Networks (ANN) – for client classification into solvent or non-solvent, having a market available Credit score rating as input. One of the most relevant contributions of this study however is the development of what we consider an innovative approach for Credit scoring. This is a two-stage process that involves the use of a fuzzy inference model as input for an ANN model (what we call a fuzzy-neural approach), using commercially available Credit score ratings as response in order to conduct the fuzzy reasoning step of the analysis. The main conclusion of our research is that, in general, our fuzzy-neural method had better results than the pure application of some market available score rating method as input to a Multi-Layer Perceptron (MLP) since it was able to reduce uncertainty by improving predictability and reducing variability of the outcomes when compared to a model with no scores. The performance of a combination of a fuzzy and a neural method was very satisfactory; the vagueness usually present in the information of a Company’ database was to a certain extent, incorporated by our method with good results. From the practical perspective, although our method has not proved to be substantially better than market available options, we demonstrated that it is possible for companies to develop Credit score rating mechanisms internally based on past data by using fuzzy inference systems. Under certain circumstances, companies may find this option preferable than the usual option of paying high fees to large Credit scoring agencies for the use of their proprietary systems.

Jiyoung Woo - One of the best experts on this subject based on the ideXlab platform.

  • service improvement by business process management using customer complaints in financial service industry
    Expert Systems With Applications, 2011
    Co-Authors: Chong Un Pyon, Jiyoung Woo, Sang Chan Park
    Abstract:

    In financial service industry, service improvement should be considered from process viewpoint and customer viewpoint because the value creation is ultimately linked with internal business processes on the back office and customers are involved as a co-producer of value. In this perspective, customer complaints through call centers are adequate to support the analysis for service improvement in financial service industry. In this study, we propose a web-based decision support system for business process management employing customer complaints, namely Voice of the Customer (VOC), and its handling data for service improvement. It involves VOC conversion for data enrichment and includes analysis of summarization, exception and comparison. The proposed system is evaluated on a major Credit Card Company in South Korea.

  • Visualization method for customer targeting using customer map
    Expert Systems with Applications, 2005
    Co-Authors: Jiyoung Woo, Sung Min Bae, Sang Chan Park
    Abstract:

    An important issue in customer-oriented marketing area is target selection which enables the determination of potential customers. In this paper, we suggest a novel customer targeting method: customer map for a service industry. The customer map is the visualization method for customer targeting. It depicts value distribution across customer needs and customer characteristics. To develop the customer map, we integrate numerous customer data from various data sources, perform data analyses using data mining techniques, and finally visualize the information derived by the former analyses. The customer map helps decision makers to build customer-oriented strategy under the unified goal of customer targeting. It also affords to monitor and perceive real time state and the change of customer value distribution based on their information without preconception. We apply the customer map to a Credit Card Company, build web-based prototype system for the customer map and acquire managerial implications from this study.