1/33
2/33
Digital Accounting:
symbolisms, the audit
ecosystem
6th University of Kansas International
conference on XBRL
April 25-27, 2013
Miklos A. Vasarhelyi
Rutgers University
AT&T Bell Laboratories
3
Internal value Chain
External value Chain
External value Chain
Process 1
Process 2
•There are many structural relationships in the value chain
•Companies will substantially outsource and just keep the “filet
mignon”
•New information technologies obsolete traditional measurement4/33
and assurance
Identification of
elementary
accounting
elements
Continuous
reporting
structures
Behavioral
issues in
continuous
reporting
Competitive
issues in detail
reporting
Structuring
audit as a Web
service
Universal data bus
Selective
Layered
Reporting
Accounting
bots
Web Services
Audit
Servic
e
Exogenous
alarming
FD rule
Fraud Profiling
Independence
Fraud
detection
Service5/33
and audit bots
XML derivative
transactions
Traditional data item
Explanatory labels (tags)
•Identity, units, source, etc.
Control labels
•E-signatures, sequence numbers,
invisible markers,
•Control signals
6/33
The digital data
life-cycle
Independence of
M&C devt. and
assuror
CA technology
alarm
• Continuity equations
• Control tagging
• Automatic
confirmations
standards
Management action
Structures
For
Continuous
Reporting
Control Tags
for
CA
Tagging
Unstructured
Information
reports
Xbrl/gl
Inv. purchase
Control
monitoring and
reliability
Labor purchase
ERPS / databases
Alarming for
missing controls
Serv. purchase
Contingencies
for close-to-theevent assurance
Can you
continuously
assure and stay
independent?
Continuous
Assurance
•Transaction
assurance
•Estimate
assurance
•Rule
assurance
Control
Continuous
Are continuous
assessment thru
reporting
•Judgment
assurances
metrics
7/33
assurance
controls?
Call for Real Time
Reporting
Reliable Systems
Corporate Accountability
Understandable
Disclosures
Financial &
Non financial measures
Information Dissemination
AICPA says: Current Model is the
Foundation
8/33
AUTOMATING
Modern systems: un-auditable
because they:
• Incorporate enormous quantities of both endogenous and
exogenous data
• Encompass many real time or close to real time processes that
are customer visible and sensitive
• Integrate gracefully with external (outsourced) systems
• Have some degree of automatic decision making built into the
systems
• Are not directly observable neither in terms of data nor in
terms of controls
• Incorporate a range of different technologies / vendors with
modified ERPs adapted to the organization’s business processes
• Sit on common cloud environments
• Are part of a product ecosystem (e.g. Amazon’s Kindle, Apple
Music, etc)
CAR Lab Advisory Board Meeting
6/28/2016
10
“Traditional method un-auditability”
(TMU) is reflected by
• Data is so large that sampling has very little value
• Data is so large that it is not practical to perform a large
number of full population tests
• Analytic technology is now such that forensic preventive models
can be developed to filter out transactions that would have been
ex-post facto reviewed
• Traditional confirmations add very little evidence; new methods
of third party validation [e.g. confirmatory extranets;
(Vasarhelyi, 2008)] must be put in place
• Relationship between non-financial and financial processes can
be developed to monitor and confirm processes
• Business processes are so rapid that firms may fail or processes
collapse before management notices and auditors verify
CAR Lab Advisory Board Meeting
6/28/2016
11
Automating
•
•
•
•
•
Reducing the latencies
Adopting audit robot (software agents)
Adopting real robots
Formalizing decisions
Adopting an audit by exception
philosophy
– Exceptional exceptions
CAR Lab Advisory Board Meeting
6/28/2016
12
The Audit Ecosystem:
Integrating Artificial
Intelligence and Expert
systems in the audit
domain
Miklos A. Vasarhelyi
Rutgers University
13
Ecosystems (economist)
•
•
•
Pioneers such as Amazon have built cloud-based “ecosystems” that
make content such as its electronic books widely available. Even
though the firm has its own e-reader, the Kindle, and has hatched
a tablet computer too, it has also created apps and other software
that let people get at their digital stuff on all sorts of devices,
including PCs.
Other companies are developing their own ecosystems in a bid to
make people’s mobile-computing experience even more seamless.
Google’s recent $12.5 billion acquisition of Motorola Mobility,
which makes smartphones, tablets and other gadgets, will enable it
to produce a new crop of devices to show off its cloud services,
such as Gmail and Google Docs, to best effect.
Apple is stepping up its integration efforts, rolling out an “iCloud”
in which people can store up to 5GB of content for nothing, and
more if they pay.
14
Apps!!!!!!!
15
A new world in assurance
• Companies are based on “big data” and
respond often on a close to real time basis
• The financial cycles are now bipolar
– Internal ERP based management data respond
close to real-time, accounts like cash, A/R,
A/P, and manufacturing are close to real-time
– Statutory financial reporting is quarterly
• while internal financial management is close to realtime to decrease occupation of capital
16
Continuous audit systems
• The continuous audit will need to be a
highly formalized system independent in
the first and second harmonic of human
reaction interference
– These systems will be conceptually analogous to
meta-controls and will force redefinition of
audit independence, materiality and audit roles
– They will be constructed in a hybrid mode with
progressive automation of key elements
17
The new audit ecosystem
•
•
•
•
Embedded into corporate ERPs?
Producing audit evidence and evaluating on a frequent basis?
Cloud-based tapping information at all locations?
Implementing audit heuristics at process levels?
– Issues with knowledge capture
– Issues with knowledge creation (how will experience be
obtained / developed?)
• Delivering evidence on an alert basis with scores and
frequent indicators
• Depending on much higher standardization than just ADS
• How will the profession (external) integrate into this
scenario?
18
A Progressive Automation
Scenario
Audit plan
Dashboard
Assertions:
• Existence
• Completeness
• Valuation &
allocation
• Classification &
understandability
Analytic
Audit
evidence
Query
Trend
Ratio
Data
matching
Query
Dashboard
•
•
•
•
•
Exception
Benchmark
Confirmation
Tracing
Relationship
Classify
19
Cloud
points of
entry
Cooperating
agent
(discriminant
Function)
Activity
Monitoring
Duplicat
e
Manual
Detectio
entry
n
Split
flag
agent
transactio
n
agent
Populatio
n
integrity
agent
Krons & Daemons’Single
function (agents)
Exception
Selection
methods
Auditor
Exception
evaluation
Assurance
Ecosystem
Processes
sale
Collect
cash
20
Conclusions
• AI has had slow evolution and is still a science in
early stages
• Expert systems were the leading AI application
area but have lost its “independence”
• Case-based reasoning and neural networks are
appropriate for specific domain problems
• Intelligent Agents will have an important role on
the Internet
• They will fit into the audit ecosystem
• Some major quandaries exist in the evolving
paradigm
• http://raw.rutgers.edu
– A wide range of presentations / videos and papers
from the multiple CA and CR conferences promoted
by Rutgers
• miklosv@rutgers.edu
– Miklos A. Vasarhelyi
22
22
23/33