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Leading Bank Chooses DataFlux to Create More Accurate, Complete Risk Reports
sponsored by DataFlux Corporation
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Although decision-making was decentralized throughout the company, the bank's corporate headquarters still needed to create credit risk management reports that would allow those local decisions to be consistent with corporate goals and objectives for the entire company. This would ensure that executives at the bank's 50 units would have the information they needed to approach each decision with an eye towards understanding how much lending risk they could assume.
The bank chose DataFlux dfPower Studio to review and compare multiple data sources simultaneously through data quality and data integration workflows. The bank created a set of business logic rules and applying these rules to the data that the bank collects from all its lending units. dfPower Studio uses graphical workflow tools and a powerful, intuitive interface to give high-level data quality and data integration capabilities to business users. Analysts in the credit risk units could automate their accumulated business rules and create a better mechanism for inspecting and correcting data.
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Available Resources from DataFlux Corporation
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sponsored by DataFlux Corporation
PODCAST:
Posted: 25 Jan 2010 |
Premiered:
25 Jan 2010
In this 12 minute podcast, get expert advice for successfully leading data quality management initiatives. Find out more about data quality program planning, required skill sets and common challenges.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 22 Jan 2010 |
Published:
22 Jan 2010
This paper explores how a rigorous data quality program is now a business imperative rather than a luxury. Implemented correctly, it not only gives organizations the agility to better ride out the current recession but also raises their competitiveness when the economy recovers.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 22 Jan 2010 |
Published:
22 Jan 2010
In the summer of 2009, DataFlux conducted a survey to understand data management trends in the financial services industry. The research examined how this industry is approaching managing its data, the breadth and depth of data governance in this sector, what motivates data management strategies, and more.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 22 Jan 2010 |
Published:
22 Jan 2010
This paper provides practical advice that will help the reader understand the pivotal role data quality technology must play in a data migration and describes five distinct implementations of data quality technology in detail.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 22 Jan 2010 |
Published:
22 Jan 2010
This paper reviews aspects of cost reduction and examines some typical financial accounting expense categories. This paper also looks at how data quality services can be applied in those examples to reduce expenses, and examines the potential for applying data quality management as a way to manage and reduce organizational expenses.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 04 Nov 2009 |
Published:
02 Nov 2009
This paper examines the impact of unreliable data on retail banks. Defining the requirements needed to guarantee data reliability in retail banking, it offers a practical approach to creating and governing that data, and shows how you can get started in making trusted data available to improve marketing, customer service, risk management and more.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 04 Nov 2009 |
Published:
02 Nov 2009
Only when data is trusted can it be used in confidence in all insurance operational and analytical process activities. This paper examines the impact of unreliable data on insurance companies. It then defines the requirements needed to guarantee data reliability in insurance and offers a practical approach to creating and governing that data.
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sponsored by DataFlux Corporation
WHITE PAPER:
Posted: 10 Jun 2008 |
Published:
06 Jun 2008
Operational data governance is the process of evaluating data to see if data effectively satisfies the organization's business needs. This is measured with a "data quality scorecard", a management tool for monitoring organizational performance.
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