EY’s Forensic Technology & Discovery Services (FTDS) practice provides a wide range of eDiscovery, data analytics and cyber breach investigation and response management capabilities, on a global basis.
These are slides from a lecture I gave at the School of Applied Sciences in Münster. In this lecture, I talked about **Real-World Data Science** at showed examples on **Fraud Detection, Customer Churn & Predictive Maintenance**.
Data Stewardship is an approach to Data Governance that formalises accountability for managing information resources on behalf of others and for the best interests of the organization
Data Stewardship consists of the people, organisation, and processes to ensure that the appropriately designated stewards are responsible for the governed data.
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Big data is more of an opportunity than a problem -- 76% consider it an opportunity, 28% already have a big data initiative in place and another 37% plan to. The possibilities of big data are endless. It starts with thinking about how to use different data in a differentiated way.
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Paul also talks about the exclusive reveal of the Sagittarius Sitecore 8 GDPR Tool as well as the latest release of Sitecore (version 9) and how these features will help brands tackle GDPR where previous versions have not.
These are slides from a lecture I gave at the School of Applied Sciences in Münster. In this lecture, I talked about **Real-World Data Science** at showed examples on **Fraud Detection, Customer Churn & Predictive Maintenance**.
Data Stewardship is an approach to Data Governance that formalises accountability for managing information resources on behalf of others and for the best interests of the organization
Data Stewardship consists of the people, organisation, and processes to ensure that the appropriately designated stewards are responsible for the governed data.
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Tackling GDPR in Sitecore Versions 8 & 9Sagittarius
Agency CEO, Paul Stephen, explores the opportunity that is GDPR and how brands and marketers alike can benefit from the regulation.
Paul also talks about the exclusive reveal of the Sagittarius Sitecore 8 GDPR Tool as well as the latest release of Sitecore (version 9) and how these features will help brands tackle GDPR where previous versions have not.
Paul Stephen - GDPR The Opportunity & Sitecore ToolSagittarius
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In this webinar on-demand:
Automation helps a company’s bottom-line through cost savings and efficiencies. In many cases, it allows workers to stay safe, as automation enables workers to reduce or avoid returning to the office to process manually-based workflows such as scanning and printing invoices, purchase orders, and even checks.
Design a standardized global AP process that supports local requirements such as multi-language, multi-currency, and more
Increase adoption of purchase orders for faster and more accurate processing
Extend your ERP's functionality to invoice processes in a new way, and utilize the best features of both Canon’s Accounts Payable Automation solution and your existing ERP
Maximize your HCM solution by leveraging Canon’s content repository
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Paul Stephen, Sagittarius Agency CEO, presents why he believes GDPR offers a fantastic opportunity for marketers to get their data in order and the overarching benefits it poses for brands. He also touches on how Sitecore 9 will support GDPR as well as a Sitecore 8.x GDPR tool that the Sagittarius team have developed.
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Organizations continue to struggle to connect the dots and extract meaningful insight from the growing volume and variety of data in Hadoop.
Our Solution: Data Refinement, Entity Resolution and Analysis: Novetta Entity Analytics unifies the data scattered across your systems to give you a single unified view of the people, organizations, locations, and other entities or “things” and their relationships in your enterprise. By revealing the real-world networks, behaviors, and trends of the entities and relationships that exist within corporate data repositories and data silos, you can connect the dots to do completely new things such as enhance the customer experience, do more targeted marketing and reduce the risk of fraud. Novetta Entity Analytics makes Hadoop data useful to anyone using an adaptive process to unify all types of data – regardless of schema – and allows analysts to look at and connect their data in entirely new ways.
The Benefits:
- Accelerate operational insights by constructing complete 360 degree views of a customer, organization, location, product, event, at any volume from any source whether structured or unstructured
- Improve customer service and retention by identifying dissatisfied customers and service problems found in call details, transactions and other volumes of interaction data and documents
- Increase revenues by creating unified customer profiles and relationships to products and services improving cross-sell/up-sell opportunities
- Detect threat and fraud by connecting the dots between people, organizations and events across data sources including transactional details
-Lower costs by solving large complex data integration and management problems using a predictable, linearly scalable platform
OUR DIFFERENTIATORS
Understands unstructured content in context
Uncovers relationships
Finds the signal within the noise
Paul Stephen - GDPR The Opportunity & Sitecore ToolSagittarius
Agency CEO, Paul, explores GDPR and the opportunity for brands and marketers as well as how those using Sitecore can tackle the regulation in Versions 8-9.
Make The Most Of The New Normal – Leverage Your ERP’s Capabilities
In this webinar on-demand:
Automation helps a company’s bottom-line through cost savings and efficiencies. In many cases, it allows workers to stay safe, as automation enables workers to reduce or avoid returning to the office to process manually-based workflows such as scanning and printing invoices, purchase orders, and even checks.
Design a standardized global AP process that supports local requirements such as multi-language, multi-currency, and more
Increase adoption of purchase orders for faster and more accurate processing
Extend your ERP's functionality to invoice processes in a new way, and utilize the best features of both Canon’s Accounts Payable Automation solution and your existing ERP
Maximize your HCM solution by leveraging Canon’s content repository
Since 2013, pass-through owners have faced a potentially higher tax rate (39.6%) on their business income than their C corporation competitors (35%). This rate disparity puts them at a competitive disadvantage and hinders growth. http://gt-us.co/1SPWvqZ Learn more about how a business equivalency rate ensures all businesses are taxed equally.
Paul Stephen, Sagittarius Agency CEO, presents why he believes GDPR offers a fantastic opportunity for marketers to get their data in order and the overarching benefits it poses for brands. He also touches on how Sitecore 9 will support GDPR as well as a Sitecore 8.x GDPR tool that the Sagittarius team have developed.
Three big questions about AI in financial servicesWhite & Case
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Unveiling the Power of Data Analytics Transforming Insights into Action.pdfKajal Digital
Data analytics is the process of examining raw data to discover patterns, correlations, trends, and other valuable information. Its significance lies in its ability to transform data into actionable insights, ultimately leading to informed decision-making and improved business outcomes. From optimizing operational processes to enhancing customer experiences, data analytics offers a plethora of benefits across various sectors.
Big Data Analytics Fraud Detection and Risk Management in Fintech.pdfSmartinfologiks
Big data analytics is crucial for fraud detection and prevention as well as risk management. As per the Association of Certified Fraud Exmainers’ Reports to the Nations, organizations proactively using data monitoring can minimize their fraud losses by an average of about 54% and identify scams in half the time.
Big data analytics is alternating the patterns in which companies prevent fraud. AI, machine learning, and data mining tech stacks help counteract the hydra of fraud attempts affecting more than 3 billion identities each year.
Behavioral Analysis for Financial Crime Threat Mitigationaccenture
In this new Accenture Finance & Risk presentation we explore how behavioral analysis can help financial services firms strengthen their ability to identify financial crime threats and facilitate complex investigation. Get more on financial crime: https://accntu.re/2qN476b
Dark Data Revelation and its Potential BenefitsPromptCloud
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Organizations continue to struggle to connect the dots and extract meaningful insight from the growing volume and variety of data in Hadoop.
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The Benefits:
- Accelerate operational insights by constructing complete 360 degree views of a customer, organization, location, product, event, at any volume from any source whether structured or unstructured
- Improve customer service and retention by identifying dissatisfied customers and service problems found in call details, transactions and other volumes of interaction data and documents
- Increase revenues by creating unified customer profiles and relationships to products and services improving cross-sell/up-sell opportunities
- Detect threat and fraud by connecting the dots between people, organizations and events across data sources including transactional details
-Lower costs by solving large complex data integration and management problems using a predictable, linearly scalable platform
OUR DIFFERENTIATORS
Understands unstructured content in context
Uncovers relationships
Finds the signal within the noise
Analytics Trends 2015: A below-the-surface lookDeloitte Canada
Big Data is a big deal for everyone these days and only growing in importance, especially when it comes to analytics generating actionable insights. Deloitte has identified eight significant analytics trends to watch in 2015 – including one supertrend that will impact everything else.
What exactly is big data? What exactly is big data? .pptxTusharSengar6
big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three “Vs.” Put simply, big data is larger, more complex data sets, especially from new data sources.
Data observability is a collection of technologies and activities that allows data science teams to prevent problems from becoming severe business issues.
Unified Information Governance, Powered by Knowledge GraphVaticle
As a knowledge graph database, Grakn is ideal for storing metadata and data lineage information. Many applications, such as data discovery, data governance, and data marketplaces, depend upon metadata for management. User experiences can be enhanced by leveraging a hyper-scalable graph database like Grakn, rather than traditional graph databases. Additionally, inference-driven use cases predominantly depended on RDF Triple Stores, requiring additional plug-ins to derive the inferences. With Grakn, this can now be achieved natively.
DATA VIRTUALIZATION FOR DECISION MAKING IN BIG DATAijseajournal
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2. Key to unlocking invisible information using forensic
“lookback”
Forensic Data Analytics as a topic and its adoption within the industry had long been overdue.
With the advent of technology and increasing incidents of fraud, there has been a significant rise
in adoption of Forensic Data Analytics. Due to this, company appointed auditors and independent
directors are now seeking to implement proactive fraud-prevention solutions and are avoiding post-
incident remediation processes.
Forensic Data Analytics is a science used to proactively seek opportunities to prevent and detect
fraud, waste and abuse by leveraging information in corporate data assets. It enables identification
of meaningful patterns and correlations in existing historic data to predict future events and assess
the reasons for various fraudulent activities. Such insightful predictive information is generally
“invisible,” but provides a platform on which organizations can take business decisions related to
fraud, disputes and misconduct.
The greatest value of forensic analytics is when it forces us
to notice what we did not expect to see.“
“
3. Forensic Data Analytics 3
Big data is a reality:
The volume, variety and velocity of
data coming into the organization have
reached unprecedented levels. About
2.5 exabytes of data are created each
day, and that number is doubling every
40 months
Recent scams in the limelight:
In the recent times, India has been hit
with multi billion value scams associated
with the following:
• Anti Money Laundering
• Bribery and Corruption
• Procurement fraud and collusion in
bidding process
• Accounting misstatement
Issues in managing big data:
Big data requires high performance
analytics to process billions of rows
of data with hundreds of millions of
data combinations. The traditional
data warehousing techniques may
not be able to identify anomalies in
the existing data set thus preventing
proactive fraud management
Adoption of forensic data analytics:
The associated risks could have been
mitigated if key stakeholders would
have paid attention to anomalies at
an earlier stage. This could have been
possible if existing data assets were
analyzed from forensic perspective to
avoid wrongful or criminal deception
intended to result in financial or
personal gain.
1. Big data
• Proactive fraud prevention management
• Controlling the magnitude of fraud in a reactive
set up
• Effective and focused internal controls
• Improving regulatory and compliance environment
How does forensic data analytics help organizations?
Evolution of forensic
data analytics
2. Manage
data
3. Key Risk
Events
4.
Forensic
Data
Analytics
Forensic analytics is the oil of
the 21st century which protects
organizations combustion
engine from going bust
Absence of forensic evidence
is not evidence of forensic
absence
Torture the data, and it will
confess to anything
Without big data analytics,
companies are blind and deaf,
meandering aimlessly like a
deer on freeway
4. Forensic Data Analytics4
Our forensic analytic models are developed to
identify variances in data sets, which may impact
an organization’s profit and loss statement. This
model also touches on various aspects, from simple
narration captured in a transaction to complicated
sentiments and tone analysis. It also includes data
within applications and data recorded on social and
professional networks for further analysis. This analysis
helps a company to move beyond identification of low
value pilferage to implementing controls on existing
and potential weak areas. Any dataset in historic, near
real time and real time form can be assimilated through
big data solutions to help a company improve its
bottom line by checking fraudulent activities
Capability landscape
Forensic Data Analytics can be used as a standalone
service or in conjunction with existing practices
such as investigations, audits, process review and
due diligence. In the current context, data exists
in structured (multiple form of databases) and
unstructured forms (emails, office documents,
presentations, Excel sheets, PDF files, archive files,
text and image files) in organizations. Using EY’s
proprietary tools, raw data can be transformed
into formats that can be analyzed, and with the
help of advanced analytical capabilities, anomalies
can be identified that may indicate potential fraud.
Some of our key offerings include, but not limited
to, identification of fraud in vendor, customer and
employee registration, procurement to pay, order to
cash, sales and distribution, travel and entertainment,
payroll disbursment.
EY_Class
Assets
Cost of R evenue
Expense
Expenses
Functional Transfer Ac..
Liabilities & Stockholde..
Local Legal Accounts (..
Other income and ded..
EY_Account_Name
Product/Program R ela..
Purchases notcapitali..
(G )/L on Sales of Equip..
13th Month Salaries #1
A&P - Customer Events
A&P - Trade s hows
A&P Collaterals - Prod..
A/P - Credit out of Debi..
EY_TIME_TAG
After office hours entries
W ithin Office hours ent..
EY_Entry_week_day
Sunday
Monday
Tuesday
W ednesday
Thursday
Friday
Saturday
EY_Entry_month_end
No
Yes
S ample Dashboard
User_ID
AKLERK
ANVSCHAIK
BATCHUSER
BJANKI
CKLEIN
CLABRAVEGA
GGOOSEN
JHAMAKER
NWINTER
PWENNEKES
RVBEUSEKOM
SAMEIER
SKAYA
TKOPPENS
TSMITS
0M
100M
200M
Amount
0K
50K
DistinctcountofJournal_ID
1,864
91
2,541 333
4
716 291
34
50,276
79,779
2 2,393 3,705
9,131
4,869
J ournal E ntries and Amount Per User Debit/Credit
Credit
Debit
EY_Account_Name
-60M -40M -20M 0M 20M 40M 60M
Amount
NL trading account NX
Trade R ec'bles - R eceivables
Agency Billing Settlement Ac..
FSMA R evenue - Other Disc..
R ental R ev. - Short Term R e..
58,874,500
60,565,488
Amount per Account Name
EY_Sub_Category
-60M -40M -20M 0M 20M 40M 60M
Amount
Accounts R eceivable: Trade
Other Current Assets: Miscel..
Due to (from) Trade and Oth..
R ental R evenue: R ental Agr..
Deferred R ental R evenue
Deferred R evenue Managed..
67,944,770
58,874,500
-67,944,770
Amount per S ub C ategory
Account Name
Effective_Date
2011
J uly August September October November December
2012
J anuary February
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
-10M 0M 10M
Amount
Agency Billing Settlement Ac..
Agency Billing Settlement Ac..
Billing Settlement A (165799..
Deferred R ev. - FM (213009..
Deferred R ev. - FSMA (2130..
Deferred R evenue - R ental (..
FM R ev. - Additional Sales (..
FM R ev. - FSMA R ev. Varia..
-801,576
-620,377
-943,525
-393,707
-615,525
-192,406
-454,933
-274,752
-254,811
-83,159
Account name per month (C alculated Based on Document Number)
Figure 1: Structured output from unstructured data
Unstructured data
Forensic data analytics
Structured output
5. Forensic Data Analytics 5
Link Analysis
Link Analysis is a data-analysis technique used to
evaluate relationships (connections) between nodes,
including organizations, people and transactions. Key
applications of this technique include analysis of EPBX
data, mobile bills and user logical access records that
help a company map its user footprint.
In a recent incident in a manufacturing company, its
phone records were analyzed across different zones
to determine the nexus between its employees and
selected vendors on procurement and disposal of
scrap. Using Link Analysis, we were able to establish
“hidden” relationships and information leakage from
suspected employees to identified vendors for possible
“kickbacks.”
Our key differentiator in forensic
data analytics
The size and width of
connectors indicate
frequency of the calls
Employee-
vendor nexus
Vendor group
Third party
Employee group
Figure 2: Link Analysis
At EY, data analytic techniques applied to internal or
external fraud follows a four pillar approach — WHO-
WHAT-WHEN- WHY. This approach looks at any
situation from all possible angles and highlights key
issues. This does not only help in managing risks, but
also in identification of potential growth areas.
Increasing concerns about fraud and vulnerability can
be alleviated by a range of forensic techniques, some
of which are presented below.
“ ”
The key to identify fraud lies in the ability to
comprehend what lies beneath.
6. Forensic Data Analytics6
Social Network Analysis
Social Network Analysis views relationships in terms
of network theory, which consists of nodes and ties.
Nodes represent individual “actors” within the network
and Ties represent relationships between individuals,
e.g., friendships, kinship, organizational position, etc.
Social Network Analysis, along with Link Analysis,
helps to identify related parties, conflict of interest, bid
rigging, among other fraud.
In a large consumer products company, the India lead
had appointed his relatives as distributors, and through
known vendors, managed distribution of products in
key states. Social Network Analysis, followed with a
background check, helped to reveal the nexus. This
led to a full-blown investigation and the company now
undergoes vendor due diligence before it carries out
any business.
Concept Clustering
Concept Clustering involves grouping similar entities
or behavior into tight semantic clusters for the purpose
of identifying anomalies or red flag. It is used actively,
along with an electronic data review. In this example,
Concept Clustering was executed on more than a
million documents to identify all the information with
terms such as “gifts,” “incentive” and “facilitation.”
We were able to bring these down to a sizable volume
with the required criteria that was analyzed in a time-
bound manner. Concept Clustering can be effectively
used on structured and unstructured data.
Sentiment Analysis
Known as behavioral analysis, this refers to the
application of text analytics to identify and extract
subjective information including the attitudes of
writers, their affective state and the intended
emotional quotient. It determines whether expressed
opinions in a document are positive, negative or
neutral. The “fraud triangle” can be applied to
categorize events into rationalization, opportunity and
pressure to identify sentiments. Organizations use this
data to conduct behavioral training, stem attrition,
and identify disgruntled employees and potential fraud
conversation.
Figure 3: Social Network Analysis
India sales head
Vendor network in east
Vendor network in west
Relatives as key distributors
Vendor network in south
Vendor network in north
India lead managing business throughout
India through relatives as key distributors
Figure 5: Sentiment Analysis
Miscellaneous
DerogatoryCursingConfusedSurprisedAngry
Fraud Cash Gift
Figure 4: Concept Clustering
7. Forensic Data Analytics 7
Tag Cloud
One of the most widely used visual techniques is a Tag
Cloud. This is a good example of expressing complex
data that can be understood intuitively. A Tag Cloud
is the visual representation of communication relating
to transactional data entries. It is represented by a
combination of words in varied fonts, sizes or colors.
This format is useful for quickly determining the
important terms to identify key fraud issues
Interactive CXO dashboards
A useful feature of analytics is that an entire data set
can be converted to a meaningful dashboard for a CXO
analysis.
Such dashboards help in understanding databases and
spreadsheets of any size with their easy drag and drop
interface. They not only display information visually
in seconds, but also create interactive maps with the
click of a mouse. They can effectively analyze time
series from years to months to the actual time in a day.
Their most helpful feature is their capability to combine
different databases to a single view and publish
interactive dashboards on the Web.
Here, we have sliced the entire expense dump of an
organization from four key lenses including WHERE
(geography), WHAT (type of expense), HOW (expense
description) and WHO (the employee who incurred the
expense). Having multi-dimensional data on a common
platform helps a company perform an insightful analysis
to determine the tests that need to be performed on
expense data.
Figure 7: Interactive CXO Dashboard
Figure 6: Tag Cloud
Data Visualization —
identifying the “hidden” from “not so apparent”
Data Visualization techniques have proved to be effective, since humans can better absorb large pieces of
information in a visual format than that displayed in numbers or text. When the result of a fraud identification query
is combined with Data Visualization, e.g., an account payable or journal entry data, a significant amount of useful
and previously invisible information can be reviewed at one go.