Title of article :
RiskVA: A Visual Analytics System for Consumer Credit Risk Analysis
Author/Authors :
Wang, Xiaoyu UNC Charlotte - Charlotte Visualization Center, USA , Jeong, Dong UNC Charlotte - Charlotte Visualization Center, USA , Chang, Remco UNC Charlotte - Charlotte Visualization Center, USA , Ribarsky, William UNC Charlotte - Charlotte Visualization Center, USA
From page :
440
To page :
451
Abstract :
Consumer credit risk analysis plays a significant role in stabilizing a bank’s investments and in maximizing its profits. As a large financial institution, Bank of America relies on effective risk analyses to minimize the net credit loss resulting from its credit products (e.g., mortgage and credit card loans). Due to the size and complexity of the data involved in this process, analysts are facing challenges in monitoring the data, comparing its geospatial and temporal patterns, and developing appropriate strategies based on the correlation from multiple analysis perspectives. To address these challenges, we present RiskVA, an interactive visual analytics system that is tailored to support credit risk analysis. RiskVA provides interactive data exploration and correlation, and visually facilitates depictions of market fluctuations and temporal trends for a targeted credit product. When evaluated by analysts from Bank of America, RiskVA was appreciated for its effectiveness in facilitating the bank’s risk management.
Keywords :
risk management , visual analytics , human computer interaction , design study
Journal title :
Tsinghua Science and Technology
Journal title :
Tsinghua Science and Technology
Record number :
2535490
Link To Document :
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