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Active Analytics
Data analytics begins with a
systematic approach to data
gathering, cleansing and
standardization. Technology allows
for an in-depth analysis of large
volumes of data over multiple
sources .
In order to efficiently risk-rank
transactions and entities for
investigation, Active Analytics
facilitates the detection of hidden
relationships and relationships with
known high-risk entities, and
identifies atypical transactional
patterns through statistical,
keyword, and exception based data
mining.
As the volume of meaningful
data continues to grow and the
quantity and nature of valuable
data sources expands, it becomes
increasingly important to
visualize links indicating a
potential threat to the
organization.
Through continuous feedback, anti-corruption and anti-fraud analytics continue to evolve. This
framework is designed to improve findings by leveraging over a decade of experience in FCPA
and fraud investigations.
How Active Analytics works
Each step works towards improving
the search for entities and
transactions that may pose a threat
to the organization:
1. Data is gathered from multiple
sources and is standardized.
2. Intelligent decision systems
capture expert knowledge and
previous experiences.
3. Exception based & statistical
analysis are used to evaluate
transactions to identify
abnormal events.
4. Entity testing establishes
potential links with known high
risk entities through current
events and third party
databases of known offenders.
5. Visualization and reporting
allow for advanced visual
discovery.
6. Data analysis and field analysis
are combined to select a sample
set of transactions for deeper
investigation.

2
Data Visualization & Reporting – Sample Compliance Sensitive Account Dashboard
Combining technology enabled analytics with a growing wealth of available and disparate information
allows for a more holistic understanding of enterprise data and a better understanding of potential FCPA
and Fraud risks.
Philip Upton
Principal
T: (646) 471-7508
E: philip.upton
@us.pwc.com
Sanjay Subramanian
Principal
T: (703) 918-1509
E: sanjay.subramanian
@us.pwc.com
Justin Offen
Director
T: (678) 419-2993
E: justin.m.offen
@us.pwc.com
Karen Choy
Director
T: (646) 471-5908
E: karen.choy
@us.pwc.com
Aalap Dalal
Manager
T: (646) 471-0111
E: aalap.j.dalal
@us.pwc.com
Global
Distribution of
Amount
Top 10 Vendors
by Transaction
Amount
Location Risk vs
Amount
Deviation
Filtered by
Country
Transaction
Volume vs
Value
Shaded by
Risk
Top 5
Vendors per
Country

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Active Analytics Overview - 1 pager - DISTRIBUTE

  • 1. 1 Active Analytics Data analytics begins with a systematic approach to data gathering, cleansing and standardization. Technology allows for an in-depth analysis of large volumes of data over multiple sources . In order to efficiently risk-rank transactions and entities for investigation, Active Analytics facilitates the detection of hidden relationships and relationships with known high-risk entities, and identifies atypical transactional patterns through statistical, keyword, and exception based data mining. As the volume of meaningful data continues to grow and the quantity and nature of valuable data sources expands, it becomes increasingly important to visualize links indicating a potential threat to the organization. Through continuous feedback, anti-corruption and anti-fraud analytics continue to evolve. This framework is designed to improve findings by leveraging over a decade of experience in FCPA and fraud investigations. How Active Analytics works Each step works towards improving the search for entities and transactions that may pose a threat to the organization: 1. Data is gathered from multiple sources and is standardized. 2. Intelligent decision systems capture expert knowledge and previous experiences. 3. Exception based & statistical analysis are used to evaluate transactions to identify abnormal events. 4. Entity testing establishes potential links with known high risk entities through current events and third party databases of known offenders. 5. Visualization and reporting allow for advanced visual discovery. 6. Data analysis and field analysis are combined to select a sample set of transactions for deeper investigation. 
  • 2. 2 Data Visualization & Reporting – Sample Compliance Sensitive Account Dashboard Combining technology enabled analytics with a growing wealth of available and disparate information allows for a more holistic understanding of enterprise data and a better understanding of potential FCPA and Fraud risks. Philip Upton Principal T: (646) 471-7508 E: philip.upton @us.pwc.com Sanjay Subramanian Principal T: (703) 918-1509 E: sanjay.subramanian @us.pwc.com Justin Offen Director T: (678) 419-2993 E: justin.m.offen @us.pwc.com Karen Choy Director T: (646) 471-5908 E: karen.choy @us.pwc.com Aalap Dalal Manager T: (646) 471-0111 E: aalap.j.dalal @us.pwc.com Global Distribution of Amount Top 10 Vendors by Transaction Amount Location Risk vs Amount Deviation Filtered by Country Transaction Volume vs Value Shaded by Risk Top 5 Vendors per Country