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Elder Research is a recognized leader in the science, practice, and technology of advanced analytics. Topics on our blog cover analytics tips, analytical modeling, data and text mining tools, data visualization, analytics best practices, case studies, etc. to provide business leaders with actionable information on real world analytics problems.
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New Tool Helps States Reduce Unemployment Insurance OverpaymentElder Research has extensive experience helping enterprises find and eliminate fraud, waste and abuse (FWA). For several state-level labor departments, we have assisted with identifying fraudulent unemployment insurance (UI) claims. This capability is critical today, during the unfortunate record-setting unemployment over the last few months. This blog is dedicated to help agencies – who are wary of domestic and foreign abusers of the UI system – by describing our successful work, where...
Elder Research has extensive experience helping enterprises find and eliminate fraud, waste and abuse (FWA). For several state-level labor departments, we have assisted with identifying fraudulent unemployment insurance (UI) claims. This capability is critical today, during the unfortunate record-setting unemployment over the last few months. This blog is dedicated to help agencies – who are wary of domestic and foreign abusers of the UI system – by describing our successful work, where and how it is being used, and how to leverage the lessons learned and tools built to identify FWA.
Policy Impact on COVID-19 Spread
As COVID-19 began to take off in the U.S. early this year, federal, state, and county governments hurried to contain it. Policies restricting movement, closing businesses, etc., have become a staple of government policy, including many stay-at-home directives across the U.S. These measures have been met with varying levels of enthusiasm, but they are rooted in an understanding about how epidemic diseases spread. Now, with several months of data, we can begin to test whether these policies...
As COVID-19 began to take off in the U.S. early this year, federal, state, and county governments hurried to contain it. Policies restricting movement, closing businesses, etc., have become a staple of government policy, including many stay-at-home directives across the U.S. These measures have been met with varying levels of enthusiasm, but they are rooted in an understanding about how epidemic diseases spread. Now, with several months of data, we can begin to test whether these policies have been effective in their primary function and to what extent a controlled “reopening” raises a community’s COVID-19 risk profile.
AUC: A Fatally Flawed Model Metric
The blog Recidivism, and the Failure of AUC published on Statistics.com showed how the use of “Area Under the Curve” (AUC) concealed bias against African-Americans defendants in a model predicting recidivism, that is, which defendants would re-offend. There, a model varied greatly in its performance characteristics depending on whether the defendant was white or black. Though both situations resulted in virtually identical AUC measures, they led to very different false alarm vs. false...
The blog Recidivism, and the Failure of AUC published on Statistics.com showed how the use of “Area Under the Curve” (AUC) concealed bias against African-Americans defendants in a model predicting recidivism, that is, which defendants would re-offend. There, a model varied greatly in its performance characteristics depending on whether the defendant was white or black. Though both situations resulted in virtually identical AUC measures, they led to very different false alarm vs. false dismissal rates. So, AUC failed the analysts relying on it, as it quantified the wrong property of the models and thus missed their vital real-world implications.
Sira-Kvina Hydro Power – Tracking Down Why the Generator Failed
In early 2020, Sira-Kvina Kraftselskap, a large producer of hydroelectric power in Norway, suffered a breakdown of one of its major generators. Company technicians went through established diagnostics to identify the cause, but they were unable to pinpoint the trouble. Efforts to restart the generator continued to fail and the shutdown dragged on for months....
In early 2020, Sira-Kvina Kraftselskap, a large producer of hydroelectric power in Norway, suffered a breakdown of one of its major generators. Company technicians went through established diagnostics to identify the cause, but they were unable to pinpoint the trouble. Efforts to restart the generator continued to fail and the shutdown dragged on for months.
Four Common Data Engineering Pitfalls (and How to Avoid Them)
Your company has made it a strategic priority to become more data-driven. Good! A major anticipated component of this transition is to implement new data technology (e.g., a data lake). Resources are thrown at identifying source systems and pulling information into a new, analytically-focused data repository or an even bigger data lake. Time is spent creating an ETL pipeline to move data from one place to another. Web endpoints are created to facilitate access for data customers. Dashboards...
Your company has made it a strategic priority to become more data-driven. Good! A major anticipated component of this transition is to implement new data technology (e.g., a data lake). Resources are thrown at identifying source systems and pulling information into a new, analytically-focused data repository or an even bigger data lake. Time is spent creating an ETL pipeline to move data from one place to another. Web endpoints are created to facilitate access for data customers. Dashboards are created that show information available in this centralized and optimized data source. At a brief with the company executive team 12 months later, the excited response from the C-level is a resounding: So how has any of this effort made us more data-driven?
Natural Language Processing for RegTech: Uncovering Hidden Patterns in Regulatory Documents
Natural language processing (NLP) is a branch of artificial intelligence aimed at giving computers the ability to use and understand human language and speech. Technology features we take for granted every day are a product of NLP. When you dictate a text message to Siri or ask Alexa the weather, that’s natural language processing. When our email services filter out spam, check our spelling and grammar, and even autocomplete entire messages, that’s NLP too. NLP is also a key part of Elder...
Natural language processing (NLP) is a branch of artificial intelligence aimed at giving computers the ability to use and understand human language and speech. Technology features we take for granted every day are a product of NLP. When you dictate a text message to Siri or ask Alexa the weather, that’s natural language processing. When our email services filter out spam, check our spelling and grammar, and even autocomplete entire messages, that’s NLP too. NLP is also a key part of Elder Research's approach to RegTech.
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