1. BizFinx : Business Financials
in XBRL
BERNICE QUEK
Accounting and Corporate Regulatory
Authority, Singapore
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2. XBRL
Overall direction is to enable:
 A pro-enterprise financial reporting
environment for businesses in Singapore
 A value-enhancing financial information flow
to the local and international business
community
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3. XBRL Revamp
 Built on XBRL experience
 Consortium consists of Deloitte, IRIS and
CrimsonLogic
 Launched on 3 March 2014
(www.bizfinx.gov.sg)
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4. XBRL Revamp
Consumers
Preparers
Increasing
the breadth
and depth of
XBRL data
Facilitating
preparation
and filing of
XBRL data
Collect what consumers
of financial statements
want for analysis
Burden and effort
required by preparers to
provide the data in XBRL
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5. 5
Training
and help
resources
Experience
the value of
XBRL
More time
for filing
BizFinx
Preparation
Tool
 Free preparation tool
 Offline
 Auto-tagging
 Drag and Drop
 More time for filing –
1st year of
implementation
 Free Data Analysis
 Free seminars +
subsidised courses
 Dedicated hotline
 Dictionary of
suggested synonyms
of taxonomy elements
 Guides
 FAQ
Support for Companies

6. BizFinx Portal
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7. Preparation Tool
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8. BizFinx Portal
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9. Validation Engine
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10. BizFinx Portal
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11. Value Of XBRL Data
 Dynamic financial analysis for business decisions
 Financial indicators available for free data analysis
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12. Value Of XBRL Data
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13. Value Of XBRL Data
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14. Value Of XBRL Data
Corporate Compliance & Financial Profile
(CCFP)
 Business Profile Information
 Compliance Rating
 Key Financial Information (over 3 years)
 Balance Sheet
 Profit and Loss
 CCFP Sample.pdf
or
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15.  Surveillance of companies’ financial statements
 Financial statements with qualified audit opinion
 Non-compliance with Companies’ Act
 Trend analysis of company’s performance over years
and comparison against industry benchmarks
 Monitoring of delinquent public accountants
 E.g. non-compliance with accounting standards not
flagged out by the auditor
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Examples of XBRL Usage
in ACRA
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16. Technology Trends
 Analytics
 Promote consumption of XBRL data
 2014 XBRL International Conference :
“Better Data For Better Decision”
 Mobile Enterprise
 Cloud Computing
 Big Data
 XBRL and non-XBRL data
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17. Business Analytics - Singapore
Financials Direct
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18. Business Analytics – Financial
Strategic Intelligence Reports
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19. Mobile Apps
Potential Market Tools to Present Collated Data
 Mobile applications available in US
 From primary statements to specific data elements in the notes for closer
examination
Source: XBRL: Putting Intelligence Into Financial Reporting in CPA Singapore Magazine – BRIX a
free iphone app (xbrl.us/research/pages/iphone.aspx)
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20. 20
TRADITIONAL IT
Business Processes BPaaS
Corporate Data DaaS
Applications with Business Logic SaaS
Applications without Business Logic
(e.g. database, development tool)
PaaS
Servers and Storage IaaS
CLOUD IT
5 Layers of Cloud
 Infrastructure-as-a-Service (PaaS)
 Virtual machines service accessed over the network providing compute and/or storage
capabilities
 Platform-as-a-Service (PaaS)
 Platform software services (e.g. middleware) on which web service based applications can be
built
 Software-as-a-Service (SaaS)
 Application provided as a service with
end user licence
 Data-as-a-Service (DaaS)
 Data or information delivered from the
Cloud as raw data sets or consumed
through an analytics interface
 Business Process-as-a-Service (BPaaS)
 Business services that are aligned to
Business process and associated
measurable business outcomes
Source: XBRL 26 International Conference : Technology and Market Trends
Cloud Computing

21. BIG Data
 Massive volume
 Structured and unstructured data
 Different sources
 Difficult to process using traditional database
and software techniques

22. Realising the Technology
Solution
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 Data collected by various organizations for various purposes and
requirements
 Data from different sources brought together in a meaningful way
– BIG DATA.
 Cloud computing technology and its advantages are being
leveraged to bring this all together in a big data mash up to
facilitate “Better Data for Better Decision”
Source data from different
sources and formats
Integrate and
compile
Provide platform to analyse
the data
CLOUD BASED SOLUTION
BIG DATA

23. Thank you
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