You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


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Abstract:

Apparatuses, computer readable media, methods, and systems are described
for identifying risk assessment queries for assessing risk of a process,
providing the identified risk assessment queries to a client device for
presentation, receiving response data from the client device comprising
responses to the risk assessment queries, determining response values for
at least some of the risk assessment queries based on the received
response data, and calculating a process risk metric based on the
determined response values.

Claims:

1. An apparatus comprising: at least one processor; a storage storing a
plurality of risk assessment queries; at least one memory storing
computer executable instructions that, when executed by the at least one
processor, cause the apparatus at least to: identify one or more risk
assessment queries from the plurality of risk assessment queries for
assessing risk of a process; provide the identified risk assessment
queries to a device for presentation; receive response data from the
device comprising responses to the identified risk assessment queries;
determine response values for at least some of the identified risk
assessment queries based on the received response data; and calculate a
process risk metric for the process based on the determined response
values.

2. The apparatus of claim 1, where the process risk metric is calculated
by adding a process total severity value to a process weighted average;
and where the process weighted average is calculated by taking a sum of a
series of response values multiplied by the number of responses
associated with each of the response values, then dividing the sum by the
number of responses associated with a non-zero response value.

3. The apparatus of claim 1, where the determining of the response values
for at least some of the risk assessment queries includes: identifying a
predetermined combination of two or more query responses; and determining
a single response value based on the identified combination of two or
more query responses.

4. The apparatus of claim 1, where the identifying of the risk assessment
queries includes selecting a subset of risk assessment queries from the
plurality of risk assessment queries based on relevance to the process.

5. A non-transitory computer-readable medium storing computer-executable
instructions that, when executed, cause an apparatus at least to perform:
identifying risk assessment queries for assessing risk of a process;
providing the identified risk assessment queries to a client device;
receiving response data from the client device comprising responses to
the risk assessment queries; determining response values for at least
some of the risk assessment queries; and calculating a process risk
metric of the process.

6. The non-transitory computer-readable medium claim 5, where the process
risk metric is calculated by adding a process total severity value to a
process weighted average.

7. The non-transitory computer-readable medium claim 6, where the process
weighted average is calculated by taking a sum of a series of possible
response values multiplied by the number of responses associated with
each of the response values, then dividing the sum by the number of
responses associated with a positive response value.

8. The non-transitory computer-readable medium claim 5, where the
determining of the response values for at least some of the risk
assessment queries includes: identifying a predetermined combination of
two or more query responses; and determining a single response value
based on the identified combination of two or more query responses.

9. The non-transitory computer-readable medium claim 5, where the
identifying of the risk assessment queries includes selecting a subset of
risk assessment queries based on relevance to the process.

10. The non-transitory computer-readable medium claim 5, where the risk
assessment queries are selected so as to elicit responses relating to
information security associated with the process.

11. The non-transitory computer-readable medium claim 5, where each of
the identified risk assessment queries is associated with a weight value,
and the weight values are used to identify at least some of the response
values.

12. The non-transitory computer-readable medium claim 5, where the
instructions, when executed, cause the apparatus at least to further
perform: comparing the calculated process risk metric to at least one
additional process risk metric; using this comparison to identify a high
risk process; and causing assignment of additional resources to the
identified high risk process.

13. A method comprising: identifying risk assessment queries for
assessing risk of a process; providing the identified risk assessment
queries to a client device for presentation; receiving response data from
the client device comprising responses to the risk assessment queries;
determining, by at least one processor, response values for at least some
of the risk assessment queries based on the received response data; and
calculating, by the at least one processor, a process risk metric based
on the determined response values.

14. The method of claim 13, where the process risk metric is calculated
by adding a process total severity value to a process weighted average.

15. The method of claim 14, where the process weighted average is
calculated by taking a sum of a series of possible response values
multiplied by the number of responses associated with each of the
response values, then dividing the sum by the number of responses
associated with a positive response value.

16. The method of claim 13, where the determining of the response values
for at least some of the risk assessment queries includes: identifying a
predetermined combination of two or more query responses; and determining
a single response value based on the identified combination of two or
more query responses.

17. The method of claim 13, where the identifying of the risk assessment
queries includes selecting a subset of risk assessment queries based on
relevance to the process.

18. The method of claim 13, where the risk assessment queries are
selected so as to elicit responses relating to information security
associated with the process.

19. The method of claim 13, where each of the identified risk assessment
queries is associated with a weight value, and the weight values are used
to identify at least some of the response values.

20. The method of claim 13, further comprising: comparing the calculated
process risk metric to at least one additional process risk metric; using
this comparison to identify a high risk process; and cause assignment of
additional resources to the identified high risk process.

Description:

BACKGROUND

[0001] Businesses in many customer service and consumer retail sectors
often handle sensitive customer information such as credit card numbers,
bank account numbers, social security numbers, phone numbers, addresses,
email addresses, birthdates, passwords, and other sensitive information.
This information may often be stored in databases owned by a business
and/or transported across networks (LANs, WANs, the Internet, etc.).
Often, this customer information may be used in various processes. For
example, a customer's credit card information and address may be used
while processing a credit card transaction for an online purchase. As
another example, a customer's social security number and date of birth
may be used as part of a credit check process for determining if a new
bank account, line of credit, or other financial product may be provided
to the customer. Due to the sensitive nature of this customer
information, security of such information may be vital.

[0002] Often, processes that involve the handling, processing, storage, or
communication of sensitive customer information may include a level of
risk. In some instances, it may be difficult to identify risk factors
associated with a particular process or set of processes. It may also be
difficult to identify processes or sets of processes that may be in need
of risk reduction measures.

BRIEF SUMMARY

[0003] The following presents a simplified summary in order to provide a
basic understanding of some aspects of the disclosure. The summary is not
an extensive overview of the disclosure. It is neither intended to
identify key or critical elements of the disclosure nor to delineate the
scope of the disclosure. The following summary merely presents some
concepts of the disclosure in a simplified form as a prelude to the
description below.

[0004] According to aspects of example embodiments, apparatuses, computer
readable media, methods, and systems are described for identifying risk
assessment queries for assessing risk of a process, providing the
identified risk assessment queries to a client device for presentation,
receiving response data from the client device comprising responses to
the risk assessment queries, determining response values for at least
some of the risk assessment queries based on the received response data,
and calculating a process risk metric based on the determined response
values.

[0005] Aspects of the embodiments may be provided in at least one
computer-readable medium and/or memory storing computer-executable
instructions that, when executed by at least one processor, cause a
computer or other apparatus to perform one or more of the process steps
described herein.

[0006] These and other aspects of the embodiments are discussed in greater
detail throughout this disclosure, including the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The present disclosure is illustrated by way of example and not
limited in the accompanying figures in which like reference numerals
indicate similar elements and in which:

[0008]FIG. 1 shows an illustrative operating environment in which various
aspects of the disclosures may be implemented in accordance with example
embodiments.

[0009]FIG. 2 is an illustrative block diagram of workstations and servers
that may be used to implement the processes and functions of certain
aspects of the present disclosure in accordance with example embodiments.

[0010]FIG. 3 illustrates an example graphical user interface (GUI)
presented by a user terminal to present risk assessment queries and
elicit responses to the risk assessment queries from an end user in
accordance with example embodiments.

[0011]FIG. 4 illustrates an example categorization scheme for
categorizing queries and associating weights with queries and query
combinations in accordance with example embodiments.

[0012] FIG. 5 is a flow diagram of an example method for collecting and
assessing risk assessment information in accordance with example
embodiments.

DETAILED DESCRIPTION

[0013] In the following description of the various embodiments, reference
is made to the accompanying drawings, which form a part hereof, and in
which is shown by way of illustration various embodiments in which the
disclosure may be practiced. It is to be understood that other
embodiments may be utilized and structural and functional modifications
may be made without departing from the scope and spirit of the present
disclosure.

[0014]FIG. 1 illustrates an example of a suitable computing system
environment 100 that may be used according to one or more illustrative
embodiments. The computing system environment 100 is only one example of
a suitable computing environment and is not intended to suggest any
limitation as to the scope of use or functionality contained in the
disclosure. The computing system environment 100 should not be
interpreted as having any dependency or requirement relating to any one
or combination of components shown in the illustrative computing system
environment 100.

[0015] The disclosure is operational with numerous other general purpose
or special purpose computing system environments or configurations.
Examples of well known computing systems, environments, and/or
configurations that may be suitable for use with the disclosed
embodiments include, but are not limited to, personal computers (PCs),
server computers, hand-held or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputers, mainframe computers, distributed
computing environments that include any of the above systems or devices,
and the like.

[0016] With reference to FIG. 1, the computing system environment 100 may
include a computing device 101 wherein the processes discussed herein may
be implemented. The computing device 101 may have a processor 103 for
controlling overall operation of the computing device 101 and its
associated components, including random-access memory (RAM) 105,
read-only memory (ROM) 107, communications module 109, and memory 115.
Computing device 101 typically includes a variety of computer readable
media. Computer readable media may be any available media that may be
accessed by computing device 101 and include both volatile and
nonvolatile media, removable and non-removable media. By way of example,
and not limitation, computer readable media may comprise a combination of
computer storage media and communication media.

[0017] Computer storage media include volatile and nonvolatile, removable
and non-removable media implemented in any method or technology for
storage of information such as computer readable instructions, data
structures, program modules or other data. Computer storage media
include, but is not limited to, random access memory (RAM), read only
memory (ROM), electronically erasable programmable read only memory
(EEPROM), flash memory or other memory technology, CD-ROM, digital
versatile disks (DVD) or other optical disk storage, magnetic cassettes,
magnetic tape, magnetic disk storage or other magnetic storage devices,
or any other medium that may be used to store the desired information and
that may be accessed by computing device 101.

[0018] Communication media typically embodies computer readable
instructions, data structures, program modules or other data in a
modulated data signal such as a carrier wave or other transport mechanism
and includes any information delivery media. Modulated data signal
includes a signal that has one or more of its characteristics set or
changed in such a manner as to encode information in the signal. By way
of example, and not limitation, communication media includes wired media
such as a wired network or direct-wired connection, and wireless media
such as acoustic, RF, infrared and other wireless media.

[0020] Although not shown, RAM 105 may include one or more are
applications representing the application data stored in RAM 105 while
the computing device is on and corresponding software applications (e.g.,
software tasks), are running on the computing device 101.

[0021] Communications module 109 may include a microphone, keypad, touch
screen, and/or stylus through which a user of computing device 101 may
provide input, and may also include one or more of a speaker for
providing audio output and a video display device for providing textual,
audiovisual and/or graphical output.

[0022] Software may be stored within memory 115 and/or storage to provide
instructions to processor 103 for enabling computing device 101 to
perform various functions. For example, memory 115 may store software
used by the computing device 101, such as an operating system 117,
application programs 119, and an associated database 121. Also, some or
all of the computer executable instructions for computing device 101 may
be embodied in hardware or firmware.

[0023] Computing device 101 may operate in a networked environment
supporting connections to one or more remote computing devices, such as
computing devices 141, 151, and 161. The computing devices 141, 151, and
161 may be personal computing devices or servers that include many or all
of the elements described above relative to the computing device 101.
Computing device 161 may be a mobile device communicating over wireless
carrier channel 171.

[0024] The network connections depicted in FIG. 1 include a local area
network (LAN) 125 and a wide area network (WAN) 129, but may also include
other networks. When used in a LAN networking environment, computing
device 101 may be connected to the LAN 125 through a network interface or
adapter in the communications module 109. When used in a WAN networking
environment, the computing device 101 may include a modem in the
communications module 109 or other means for establishing communications
over the WAN 129, such as the Internet 131 or other type of computer
network. It will be appreciated that the network connections shown are
illustrative and other means of establishing a communications link
between the computing devices may be used. Various well-known protocols
such as TCP/IP, Ethernet, FTP, HTTP and the like may be used, and the
system may be operated in a client-server configuration to permit a user
to retrieve web pages from a web-based server. Any of various
conventional web browsers may be used to display and manipulate data on
web pages.

[0025] Additionally, one or more application programs 119 used by the
computing device 101, according to an illustrative embodiment, may
include computer executable instructions for invoking user functionality
related to communication including, for example, email, short message
service (SMS), and voice input and speech recognition applications.

[0026] Embodiments of the disclosure may include forms of
computer-readable media. Computer-readable media include any available
media that may be accessed by a computing device 101. Computer-readable
media may comprise storage media and communication media and in some
examples may be non-transitory. Storage media include volatile and
nonvolatile, removable and non-removable media implemented in any method
or technology for storage of information such as computer-readable
instructions, object code, data structures, program modules, or other
data. Communication media include any information delivery media and
typically embody data in a modulated data signal such as a carrier wave
or other transport mechanism.

[0027] Although not required, various aspects described herein may be
embodied as a method, an apparatus, a data processing system, as a
computer-readable medium storing computer-executable instructions,
combination thereof, or other implementations. For example, a
computer-readable medium storing instructions to cause a processor to
perform steps of a method in accordance with aspects of the disclosed
embodiments is contemplated. For example, aspects of the method steps
disclosed herein may be executed on a processor on a computing device
101. Such a processor may execute computer-executable instructions stored
on a computer-readable medium.

[0028] Referring to FIG. 2, an illustrative system 200 for implementing
example embodiments according to the present disclosure is shown. As
illustrated, system 200 may include one or more workstation computers
201. Workstations 201 may be local or remote, and may be connected by one
of communications links 202 to computer network 203 that is linked via
communications links 205 to server 204. In system 200, server 204 may be
any suitable server, processor, computer, or data processing device, or
combination of the same. Server 204 may be used to process the
instructions received from, and the transactions entered into by, one or
more participants.

[0029] Computer network 203 may be any suitable computer network including
the Internet, an intranet, a wide-area network (WAN), a local-area
network (LAN), a wireless network, a digital subscriber line (DSL)
network, a frame relay network, an asynchronous transfer mode (ATM)
network, a virtual private network (VPN), or any combination of any of
the same. Communications links 202 and 205 may be any communications
links suitable for communicating between workstations 201 and server 204,
such as network links, dial-up links, wireless links, hard-wired links,
etc.

[0030] The steps that follow in the Figures may be implemented by one or
more of the components in FIGS. 1 and 2 and/or other components,
including other computing devices.

[0031] In general, information pertaining to the security of sensitive
information may be received from one or more process owners or users. The
information may be elicited by presenting a series of questions to a
process owner or user. In some implementations, the received information
may be related to the processing or security of sensitive information,
such as social security numbers, credit card numbers, bank account
numbers, passwords, customer information (address, phone number, email,
etc.) or other sensitive information. The received information may be
used to assess the risk associated with a particular process or data
handling scheme. The assessed risk for a particular process may be
compared to the relative risk levels identified for other processes. This
comparison of identified risk levels may be used to prioritize risk
treatment among several processes, or may be used to identify one or more
processes that may be in need of attention in order to reduce risk. In
some implementations, resource prioritization may be performed to
mitigate the risk for selected high risk processes. This may involve
changing processes or controls related to processes.

[0032] The methods for identifying risk associated with processes (as
described below in greater detail) may be adjusted to meet the dynamic
nature of varying processes and process characteristics to effectively
identify the nature and sensitivity level of data associated with
processes. Existing process controls may be evaluated for risk, and
controls may be modified, or new controls may be put in place to mitigate
risk associated with a particular process. Additionally, risk assessment
methods may be used to create a control environment which in turn
facilitates compliance with regulations and/or industry standards.
Benefits may include proactive identification of potential security gaps
and information risks in respective processes; structured sharing of
security gaps and information risks with process owners; and development
of risk mitigation procedures. Additionally, process owners may be
enabled to have a closer insight into risk factors associated with a
process and justifications behind changes to controls or processes to
reduce risk.

[0033] Turning now to FIG. 3, a graphic user interface (GUI) 300 includes
a Risk Assessment Query Form (form) 302 for eliciting information from a
process owner. The GUI 300 may be presented to a user on a graphic
display of a desktop computer, laptop computer, mobile device, or other
computing device. For example, the GUI 300 may be displayed on a display
screen in communication with, or incorporated into the computing device
101 or the computing device 151 shown in FIG. 1. The GUI 300 presents the
form 302 to a user. The form 302 includes a number of queries 304. The
queries may be presented to the user to elicit input from the user. In
the example shown the queries 304 are intended to elicit yes/no
responses. The user may indicate the answer to a query 304 by selecting
one of a number of checkboxes 306. For example, the user may indicate a
response to a query 304a by selecting a checkbox 306a (e.g., by using a
mouse to position a cursor over the checkbox 306a and "click" on the
checkbox 306a). In response to the user input, the GUI 300 may display a
checkmark 308 in the checkbox 306a to indicate that the user has
indicated a "yes" answer to the query 304a. In some implementations,
means other than checkboxes may be used to indicate a user's answers to
the queries 304. For example, the form 302 may include radio buttons for
receiving and indicating user responses. As another example, the form 302
may include text boxes for receiving user input. As yet another example,
the form 302 may include pull down boxes to allow a user to select from a
number of preselected answers (e.g., yes, no, not applicable, etc.).

[0034] In addition to the queries 304 shown in FIG. 3, below are some
example queries to solicit information about one or more processes.

[0035] Query 1: Has access control been applied on a shared/network folder
(read/write/full control/modify) for ensuring access only to authorized
associates and is access to a folder being revoked on transfer/attrition
of an associate?

[0036] Query 2: Does a process store data on a Card Verification Value
(CVV) or personal identification number (PIN) after the intended usage
criteria is fulfilled?

[0037] Query 3: Is customer/associate confidential information being sent
over email to any external email address, including vendors/contractors
having an internal email address?

[0039] Query 5: Are emails containing customer confidential information
deleted from a sent folder and any other locally stored personal storage
table (PST) files after the business need has been completed?

[0040] Query 6: Is this a Voice Process (e.g., involving
customers/partners communication over the phone, such as, for example,
Collection, Activation, etc.)?

[0049] In the example shown in FIG. 3, the queries 304 may be selected so
as to gather information pertaining to information security. For example,
the queries 304 may be directed towards procedures for protecting
information. The answers received in response to the queries may then be
used to assess risk associated with a particular process or data handling
scheme. In some implementations, the queries 304 may be selected from a
query database. For example, referring to FIG. 1, the computing device
101 may access a query database stored within the database 121 or in an
external database in communication with the computing device 101. The
computing device 101 may select a number of queries from the query
database. The computing device 101 may then provide the selected queries
to the computing device 151 for presentation to a user of the computing
device 151 as part of the GUI 300. In some implementations, a user who is
filling out the form 302 may pause midway through answering the queries,
save the results entered so far, and resume filling out the form 302 at a
subsequent time. The partially completed form 302 may be stored, for
example, in memory of the computing device 151 or the computing device
101.

[0050] In some implementations, the queries 304 may be selected from the
query database so as to be related to a specific process. The selected
queries 304 may include one or more general queries that are included for
all processes which are being assessed, regardless of the type of
process. In some implementations, a number of criteria may be used to
identify queries that are tailored to a specific process. For example,
each process environment may be associated with one or more inclusion
filters that parse only selected ones of the queries 304 from the query
database. The computing device 101 may apply the inclusion filters to the
query database to retrieve queries based on one or more of operations
type (e.g., credit card services, fraud management, IT support,
application development), platform used (e.g., database, server,
application, voice, etc.), facility used (e.g., Internet, email, etc.),
and the like. For example, if a particular process involves the handling
or processing of customer social security numbers, the inclusion filters
may identify queries related to the handling and security of social
security numbers as being relevant to the process and included as part of
the queries 304. In some instances, queries in the query database may be
sequenced with regard to their relevance to a particular process or
facility, and a predetermined number of queries may be selected for
presentation as the queries 304 based on relevance of the subsequent
queries to the earlier queries. In some instances, all queries that are
identified as relevant may be selected for presentation as the queries
304. In some implementations, all of the queries in the query database
may be selected for presentation. In some implementations, the same set
of queries may be presented in conjunction with each Risk Assessment
Query Form 302 without regard to relevance to a specific process or data
handling scheme.

[0051] As mentioned previously, in some implementations, the queries 304
may be selected so as to elicit responses from a user that may be used to
assess the risk associated with a particular process. The questions may,
for example, be presented to a process owner or process manager for a
particular process or set of processes. For example, query 304a asks if
the network associated with a process includes firewall software. As
another example, query 304b asks if wireless network communications are
encrypted.

[0052] In an example, a process may relate to a voice process for banking
business/support operations. This process may include credit card
services, fraud management, global wealth management customer care, etc.
In such an example, the following queries may be asked:

[0053] Query 1: Is this a Voice Process (e.g., involving
customers/partners communication over the phone, for example, Collection,
Activation, etc.)?

[0059] Query 7: Is there any requirement in the process to replay the
recorded call? (e.g., Quality/Training purpose).

[0060] Query 8: Are recorded calls only accessible only to selected
individuals?

[0061] Referring again to FIG. 3, queries 304 may be selected so as to
elicit information regarding general information security, customer
sensitive data handling, data classification, document security controls,
information transfer channels, system and business application controls,
and/or operational controls. The queries 304 may also be identified using
requirements of information security baselines or standards, such as
national or international data security standards. For example, queries
may be identified or generated based on the Payment Card Industry Data
Security Standard (PCI DSS) requirements. As another example, standards
for electronic health care transactions as defined by Health Insurance
Portability and Accountability Act (HIPAA) may be used to identify or
generate queries. Other guidelines may be used when generating or
identifying queries to include in the queries 304, such as industry best
practices for a particular industry, or data privacy regulations. For
example, queries may be generated or identified so as to comply with the
UK Data Protection Act of 1998.

[0062] In the example shown, the queries 304 may be intended to elicit yes
or no responses. In some implementations, some or all of the queries 304
may elicit responses other than yes or no responses. For example, the
form 302 may include text boxes to allow a user to enter text in response
to one or more of the queries 304. As another example, the form 302 may
include sliding scales that allow users to indicate a number within a
range in response to a one or more of the queries 304. For example, a
query could ask a user to indicate on a scale of 1-10 the likelihood of
employees accessing sensitive information for non-work related purposes.

[0063] In some implementations, the user responses may be provided to a
processing device to be used for assessing risk associated with a process
or set of processes. For example, referring to FIG. 1, the computing
device 151 may display the form 302 to a user and collect responses from
the user. The computing device 151 may then provide the user responses to
the computing device 101 for further processing. As another example, the
computing device 151 may use the user response information to assess a
risk level associated with a process. In some implementations, the user
responses may be reviewed to ensure accuracy prior to being used to
assess a risk level. For example, a process owner may provide answers
using the form 302, and a manager may review the answers provided by the
process owner to ensure accuracy of the responses. Also, information
security practitioners may validate the responses in some cases and
analyze the information received through the queries to modify the
outcome of the risk level.

[0064] In some implementations, weights may be associated with some or all
of the queries 304. In some implementations, each query may be associated
with a weight in the query database. In some implementations, weights may
be assigned to the queries based on one or more factors. For example, the
computing device 101 may select a number of queries from the query
database for presentation as the queries 304. The computing device may
assign weights to each of the selected queries based on the
importance/relevance of that query to a particular process. For example,
the query 304b may be associated with a weight of 2 for a first process
and associated with a weight of 4 for a second process. In some
implementations, the weights may be assigned on a scale of 1-20. In some
implementations, the weights may be assigned on a scale of 1-10. In some
implementations, the weights may be assigned on a scale of 1-6. In some
implementations, another scale may be used for weighting queries. In some
implementations, the weights may be the same for all types of risk, and,
in some implementations, the weights may differ for each type of risk. In
some implementations, some, but not all, types of risk may have the same
weight. In some implementations, weights may not be required.

[0065] Turning to FIG. 4, queries (e.g., the queries 304 from FIG. 3) may
be grouped into two or more categories. The categories may be used to
identify query responses, or combinations of query responses, that
indicate situations which are used to derive risk associated with a
process. In the example shown, the queries are separated into two
categories. In the example shown, a table 402 displays category one
queries. Category one queries may be identified as queries for which a
particular response indicates a direct risk situation associated with a
process without regard to other query responses. For example, a response
of "no" in response to a question of "is there a firewall installed on
the network" may be identified as a risk associated with a process. As
another example, a response of "yes" to a query of "Do sub-manager level
employees have access to customer social security numbers" could also be
identified as a direct risk situation considering existing available
information about their privileges. In some example implementations, if
there is a sequence of related queries and if a response to a particular
one of the queries is identified as a non-risk, then the subsequent
queries in the sequence may also be identified as a non-risk.

[0066] Referring again to FIG. 4, category two queries are displayed in a
table 404. The category two queries may be identified as queries for
which an increased risk factor is only assigned when a particular
response for a first query occurs in conjunction with a particular
response for a second query (or in conjunction with particular responses
for second and third queries, etc.). For example, table 404 identifies
query 3 as a category two query. In some implementations, a lookup table
406 may identify query response combinations that lead to increased risk
and identify weights for the query response combinations. The lookup
table 406 (as well as the tables 402 and 404) may be stored, for example,
in RAM 105 or ROM 107 of the computing device 101 of FIG. 1.

[0067] The below examples may be of category one queries which may
independently indicate risk exposure.

[0068] Query 1. Has access control been applied on a shared/network folder
(read/write/full control/modify) for ensuring access only to authorized
associates and access are getting revoked from folder on
transfer/attrition of an associate?

[0069] Query 2. Does the process store CVV/PIN data after the intended
usage criteria is fulfilled?

[0070] The below examples may be of category two queries for which an
increased risk factor is only assigned when a particular response for a
first query occurs in conjunction with a particular response for a second
query (or in conjunction with particular responses for second and third
queries, etc.). In the below example, a response to Query 1 below does
not independently pose any risk, but there is the potential for risk
exposure when combined with Query 2 or 3.

[0071] Query 1. Is customer/associate confidential information sent over
email to any external email address, including any vendors/contractors
having an internal email address?

[0078] Query 3: Are conversations with customers, containing confidential
information, being recorded (e.g., using Voice call recording tools such
as, for example, by NICE Systems)?

[0079] Query 4: Is access to recorded customer calls restricted to
employees based on justified business need?

[0080] In the example shown in FIG. 4, the lookup table 406 identifies
query 3 and query 7 as a query combination for which a particular
combination of responses (e.g., a yes answer to query 3, and a no answer
to query 7) may be a risk-increasing combination. The lookup table 406
further identifies queries 4, 6, and 7 as a set of queries for which a
particular combination of responses may be identified as risk-increasing.
The lookup table 406 identifies the combination of queries 4, 6, and 7 as
having a weight of 4. As discussed above, the weights may be
predetermined, the weights may be assigned based on the relevance of
queries (and query combinations) to a particular process, or weights may
not be assigned.

[0081] In some implementations, the lookup table 406 may include query
combinations that include one or more category one queries. For example,
a category one query may be identified as being associated with a direct
risk situation, and a weight may be associated with the category one
query. The lookup table 406 may additionally identify a query combination
that includes the category one query increases the weight associated with
the query. For example, query 5 may be associated with a weight of 4 in
table 402. The lookup table 406 may further associate a combination of
query 5 with query 3 as having a weight of 6. As another example, table
402 indicates a weight of 2 associated with query 8. The lookup table 406
indicates an increased weight of 4 when a particular response for query 8
is combined with a particular response for query 10. Additionally, the
lookup table 406 indicates an additional increase to a weight of 5 when
particular risk-increasing responses to query 8 and query 10 are combined
with a particular response to query 12.

[0082] Turning now to FIG. 5, an example process 500 is shown for
collecting and assessing risk assessment information in accordance with
an example embodiment. The method may be implemented by the computing
device 101, computer, or other apparatus. The order of the blocks
depicted in FIG. 5 may be rearranged, one or more blocks may be repeated
in sequential and/or non-sequential order, and/or one or more blocks may
be omitted. Further, other blocks may be added to the flow diagram.

[0083] The process 500 may be used for identifying a risk factor
associated with a process and may include a block 502 of identifying risk
assessment queries for assessing risk of a process. For example, a
plurality of queries may be stored in a database. The set of queries may
be selected from the queries stored in the database. In some
implementations, a number of criteria may be used to select queries that
may be relevant to a particular process or set of processes. For example,
a number of queries related to encryption of electronic communications
may be selected as being relevant to a process that involves transfer of
sensitive information between computing devices across one or more
networks. The queries may be selected for presentation to a process owner
to allow the owner to provide information related to risk management for
a particular process or set of processes.

[0084] At block 504, the identified queries may be provided to a client
device for presentation to a user. For example, referring to FIG. 1, the
computing device 101 may provide the identified queries to the computing
device 151 for presentation to a user of the computing device 151. In
some implementations, the user may be the owner of the process for which
risk is being assessed. In some implementations, the user may be a
different employee associated with the process, or another user of the
client device.

[0085] At block 506, response data may be received from the client device.
For example, referring to FIG. 1, the computing device 101 may receive
response data from the computing device 151. The response data may be
query responses provided by the user in response to the queries presented
by the client device.

[0086] At block 508, response values for queries may be determined based
on the received response data. For example, a "Not Applicable" (NA)
response, or a query for which no response is provided, may not be
considered when calculating risk. As another example, a risk-increasing
response may be identified for each query. For example, for the query "Is
anti-virus software installed," a response of "No" may be identified as
risk-increasing while a response of "Yes" may be identified as
non-risk-increasing. In this example, if the response to the query is
"No" (risk-increasing) the weight associated with the query may be
assigned as the response value. For example, if the weight associated
with the query is 5, a response value of 5 may be identified for the
response of "No." If the response to the query is "Yes"
(non-risk-increasing) a value of zero may be identified as the response
value. In some implementations, a negative value may be identified for a
non-risk-increasing response. In some implementations, a positive value
that is less than the weight associated with a query may be identified as
the response value for a non-risk-increasing response. As previously
described, in some implementations, a particular response to a query will
not be identified as risk-increasing unless a corresponding response to a
second query also occurs.

[0087] The following provides an example of determining a response value
based on a combination of queries for a process that involves use of
email and processing of credit card information.

[0088] Query 1. Is customer/associate confidential information sent over
email to any external email address, including vendors/contractors having
an internal email address?

[0089] Response to Query 1--Yes

[0090] Query 2. Are these emails being encrypted (e.g., using POSTX, PGP,
and TLS)?

[0091] Response to Query 2--No

[0092] Query 3. Are emails containing customer confidential information
deleted from sent folder and any other locally stored PST files after the
business need is over?

[0096] Based on the response data, then a response value may be calculated
as follows:

[0097] a) Query 1 and 2 (Email facility) combined together result in a
risk scenario and, based on the response data, may be assigned an
intermediate risk value of 1.

[0098] b) Query 3 (Email facility) may be a risk increasing query for
point (a) and, based on the response data, may be assigned an
intermediate risk value of 1.

[0099] c) Query 4 (Credit Card operations) is a question identifying an
independent risk and, based on the response data, may be assigned an
intermediate risk value of 1.

[0100] The response value for the process is a sum of the intermediate
risk values, and may result in the response value being a)+b)+c)=1+1+1=3
for this process.

[0101] At block 510, a Process Weighted Average (PWA) may be calculated
using the identified response values. The PWA may be calculated as the
summation of each response value from a series of response values
multiplied by the number of queries (or query combinations) associated
with that response value (e.g., 5 times the number of queries (or query
combinations) associated with a response value of 5) divided by the
summation of the number of queries (or query combinations) associated
with a non-zero or positive risk value (e.g., the number of queries (or
query combinations) associated with a risk-increasing response). For
example, if the series of response values is 1-6, the summations would
occur across the range of 1-6. The equation for calculating Process
Weighted Average may be represented as:

[0102] In some implementations, the values of i range from 1-6. Using the
above equation in an example, if there are two response values of 5 and
one response value of 3 for a process, the PWA may be calculated as

PWA=((5*2)+(3*1))/(2+1)=4.33

[0103] At block 512, a Process Total Severity (PTS) value may be
calculated. The PTS may be calculated as the sum of all response values
associated with a process. Following the above example where two response
values of 5 and one response value of 3 is associated with a process, the
PTS for the process may be calculated as

PTS=5+5+3=13

[0104] At block 514, a Process Risk Metric may be calculated based on the
Process Total

[0105] Severity value and the Process Weighted Average. The Process Risk
Metric may be calculated as the sum of the Process Total Severity value
and the Process Weighted Average for a process. In some implementations,
Process Weighted Average and Process Severity value may be used
selectively or not used at all, and Process Risk Metric may be calculated
as mentioned in block 508. Following the above example, the Process Risk
Metric for the process having two response values of 5 and one response
value of 3 would be

Process Risk Metric=13+4.33=17.33

[0106] In some implementations, the blocks of the process 500 may be
repeated for multiple processes or sets of processes to identify a
process risk metric for each process or set of processes. The process
risk metrics for multiple processes may be compared to make decisions
related to the processes. For example, if several candidate processes are
under consideration for adoption as a new process, the process risk
metric may be used in selecting a process from the candidate processes
(e.g., having a lowest process risk metric score). In an example, risk
treatment of processes may be prioritized based on process risk metric
scores. The process risk metrics may be used to identify processes that
are in most need of attention and/or resources in order to reduce risk
(e.g., identify one or more processes having the highest process risk
metric scores). Resources may then be allocated to the highest risk
processes to implement and/or revise controls to reduce the risk of the
identified high risk processes. This may help to ensure that a finite
amount of resources may be focused on the processes that most require
these resources (e.g., processes that have the highest process risk
metric scores).

[0107] In some implementations, the process 500 may include greater or
fewer blocks than shown in the example in FIG. 5. For example, the
process 500 may include an additional block of identifying a high risk
process from among a set of processes using the process risk metric for
the process. In another example, the process 500 may include an
additional block of ranking processes (e.g., in ascending/descending
order) based on their process risk metric scores. In some
implementations, the blocks of the process 500 may be completed in a
different order. For example, the Process Total Severity value may be
calculated prior to the Process Weighted Average being calculated.

[0108] Aspects of the embodiments have been described in terms of
illustrative embodiments thereof. Numerous other embodiments,
modifications and variations within the scope and spirit of the appended
claims will occur to persons of ordinary skill in the art from a review
of this disclosure. For example, one of ordinary skill in the art will
appreciate that the steps illustrated in the illustrative figures may be
performed in other than the recited order, and that one or more steps
illustrated may be optional in accordance with aspects of the
embodiments. They may determine that the requirements should be applied
to third party service providers (e.g., those that maintain records on
behalf of the company).