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Case Study

With the ability to link and clean external data from infoUSA to internal state data using DataMatch Enterprise, the Department of Taxation forecasts bringing in at least an additional $15 million dollars in revenue for the state. This revenue can be distributed to local governments, libraries and school districts.

Company Profile

The State Department of Taxation collects and administers 21 state taxes, three local taxes and oversees real estate property tax. The department also distributes revenue to local governments, libraries and school districts. Its mission is to provide quality service to state taxpayers by helping them comply with their tax responsibilities and by fairly applying the tax law. The Commercial Audit team is responsible for handling five tax types.

Business Situation

The Department of Taxation has over 200, mostly remote, commercial tax auditors, who are tasked with regulating over 2 million businesses in the region. They received a tip that a very specific law was being broken by numerous companies in the state. Corporations are required to pay all back taxes, interest and a penalty that equals 30-50% of the past tax owed if it is proven that they intentionally broke the law.

Up until this point, the auditors lacked the business intelligence to figure out which audits to pursue. These auditors, often working within a 120-mile radius of their home, would select audits to work at random, without having solid knowledge on which leads to actively pursue.

Our Solution

The executive administrator from the Commercial Tax division recruited a data science team to ferret out leads for the auditors. The team took the time to digest and understand the clues that the state audit team had shared with them about this hot tip.

To be able to make better sense of the state’s data, the team decided to enrich it by matching against external data from infoUSA. DataMatch Enterprise was used to link those records/clues/attributes/fields of information from infoUSA to the decades of data that had been collected but never mined, within the state’s Teradata system.

Using DME to match up the external and internal data, the team was able to make the data more usable and contextual for analysis. They then layered their data science on top of this stable foundation, building models and running routines until they narrowed down the potential leads that the commercial auditors could chase – from nearly 2 million records to 100k records.

Integrate data sources from across the enterprise with data matching software
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Link records/clues/attributes/fields

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Data more usable and real to be analyzed

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Save time and frustration

With the ability to link and clean external data from infoUSA to internal state data, the state forecasts bringing in at least an additional $15 million dollars in revenue for the state. This revenue can be distributed to local governments, libraries and school districts.

Benefits

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Data science, business intelligence and predictive analytics can now be layered on top of the accurate foundational data that DME produced. DME accurately does complex, cross column/cross database record linkage and data matching in record times. DME makes human-like decisions at computer speed, speeding up the time it takes to make sense of data from disparate data sources.

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With the ability to link and clean external data from infoUSA to internal state data, the state forecasts bringing in at least an additional $15 million dollars in revenue for the state. This revenue can be distributed to local governments, libraries and school districts.

Background

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