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This document discusses how the DATA Act could enable predictive analytics across the government. It provides contact information for three individuals at Datamininglab.com and describes a predictive modeling tool used from 2010-2012 that initiated 94 workers' compensation fraud cases, closed 12 cases, and resulted in over $8 million in cost savings and recoveries. Finally, it compares the information available in USASpending.gov/FPDS to the more comprehensive agency data available through the DATA Act, noting the DATA Act could support scoring contracts across agencies for fraud risk.

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DATA
Act:
Enabling
Government‐Wide
 Predic9ve
Analy9cs
 Contacts:
 Antonia
de
Medinaceli,
Director
of
Fraud
Analy9cs
 •  antonia@datamininglab.com

 Isaiah
Goodall,
Director
of
Business
Development
 •  goodall@datamininglab.com

 Gerhard
Pilcher,
Vice
President
and
Senior
Scien9st
 •  pilcher@datamininglab.com

 1

RADR
–
Return
on
Investment
 Workers
Compensa0on
Fraud
‐

 Workers’
Compensa9on
Fraud
 Predic0ve
Modeling
Tool
 October
2010
–
June
2012
 Time
Period
 (~1.5
years)
 94
cases
ini9ated
and
 Cases
Ini0ated
/
Closed
 under
inves9ga9on;

 12
cases
closed
 $8
Million
+
(recoveries,
 Cost
Savings
and
 res9tu9ons,
and
cost
 Recoveries:
 avoidance)
since
October
 2010

 2
 Copyright © Elder Research, Inc. All Rights Reserved.
USPS
OIG
Agency
Data
(DATA
Act)
 More
informa0on–
Higher
Confidence
 Universal
data
set
–
find
fraud,
waste,
 and
abuse
across
mul9ple
agencies
 Contract
Fraud
RADR
 •  Score
all
USPS
contracts
for
risk
of
 fraud,
waste,
or
abuse
 •  35
metrics
 •  74%
ac9onable
leads
 USASpending.gov
/
FPDS
 Less
informa0on
–
Lower
confidence
 •  7
metrics
 •  No
payment
data
 •  Incomplete,
not
always
reported