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Ohio DGS 2015 Presentation -Leveraging Big Data and Meaningful Analyticsby Joseph Hammond
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Audit Selection
Joseph L HammondExecutive Administrator – Audit Division
What is the business need?
Simply put, we did not have a structured method for generating audit leads.
Where do you start?• What: The Ohio Department of Taxation project (June, 2015) created a process
that uses statistical data to objectively identify business taxpayers with profiles that merit audit scrutiny.
• Past Practice: No structured method for generating audit leads allowed for subjective selections. Tax Auditors would identify companies to audit based on:– information obtained in the course of auditing other companies– tradition; revisiting companies that had been noncompliant in the past– personal observation; see, hear, or discover some anomaly that prompted
further inquiry
• Current Process: The Tax Commissioner directed the Audit Division to develop an Audit Selection Process that was objective, efficient, fair, and equitable. An Audit team, working with a contract vendor specializing in data analysis, developed an Audit Selection Model that uses software capable of sifting through hundreds of thousands of business taxpayers to identify the small percentage that are likely to be out of compliance with tax law and their tax obligations.
Auditing four taxes: use, sales, employer withholding, and commercial activity
What do you have to start with ?
Business needClear directionSPSS Software4.4 terabytes of data within data warehouseBusiness people IT peopleBusiness process poised for change
Audit Selection Project
Considerations
1. Original Objectives and Value Achieved2. Lifecycle of the Project3. The Leads Produced by the Model4. Geographic Distribution of Leads5. Constructing the Model6. Addressing Questions 7. Data Governance8. Recommendations and Roadmap
Vision for the Project
• Who – You, the Audit Team• What – Create a working audit selection model to
sustain growth, expansion and evolution• Where – Wherever you happen to be when an idea
comes to you• When – Short runway 2/1/15– 6/30/15• Why – We need to be objective, efficient, fair and
equitable
Objectives
Fair & EquitableImprove Taxpayer ComplianceEfficiency
Lifecycle of the Project
• Began in February 2015• Ended in June 2015• One team of auditors and consultants• Took on tax types sequentially
Use Tax
CAT
Sales Tax
EWT
What’s Different About the Modeling Methodology?
Statistical modeling changes the entire approach to identifying leads
Queries require a long time to develop
After data extraction, statistic models evolve and adapt very quickly
Audit Selection is not able to see the filters and rules
Statistic models were developed in partnership with the auditors and are reviewed continuously
Queries do not learn over time Statistic models learn and adapt with every execution
Constructing the Model
Productive Past Audits
Statistical Model
Companies
AuditLeads!
Lead Inventory As Of TodayModel Name CountUSE Predictions 2,472USE Trending 11,362USE non-registered 10,672CAT Predictions 725CAT Trending 2,830SALES Trending 9,673EWT Trending 6,582
Sub total 44,316Overlapping 3,446Unique Leads 40,870
Total Population of Leads
Now2014
Geographic Distribution of Leads
Value Achieved• 5.5 – 6.0% time spent on research• 190 Hours saved per auditor per year
37,071 total hours for all auditors reduced to 250 hours (99.3% reduction)
• Reduce unproductive audits by 50%• 44,316 Audit Leads
7% of companies (compared to over 630,000)
9.14% Avg
0.7% Future
Audit Work Request Process
Data Governance at ODT
• Accomplishments– Formalized New Data and Query Request Processes– Data Governance Council– Data Profiling– Audit Selection Model Data Sourcebook– Data Dashboards
• Audit Selection Model
– Formal approach to Data Quality for Analytics Products