ACTG 379 Final Exam Full Chapter Study
Co-occurrence Grouping
an approach that attempts to discover associations between individuals based on transactions involving them.
Target
an expected attribute or value we want to evaluate.
Decision support system
an information system that support decisions-making activity within a business by combining data and expertise to solve problems and perform calculations.
Scenarios For Changes in R&D Credit
fixed-base %, ceiling for fixed-base %, floor of current QREs, Credit %, Current/future levels of qualified research activity.
Example KPIs of Tax Risk
frequency and magnitude of tax audit adjs., Frequency of concerns pertaining to the organization's tax position, Levels of late filing or error penalties and fines, Number of resubmitted tax returns due to errors.
Diagnostic Tax Analytics
help identify items of interest, such as high tax areas or excluded transactions.
Cockpits
similar to dashboards but narrower in scope and focus. Allows the tax function to highlight potential high impact or single areas of concern like reconciliation.
Common theme between A.I. and Machine Learning
use algorithms and statistical models to generate a previously unknown model that relies on patterns and inferences.
Predictive Tax Analytics
use historical data and new information to identify future tax liabilities. A regression and what-if analysis and requires a specific target, such as value of a tax credit or deferred tax asset.
Artificial intelligence
used to create more accurate predictions and recommendations.
IMPACT model question for tax functions 1
What can analytics do to reduce the overall current and future tax liabilities?
Permanent BTDs
should be tracked by tax managers to ensure compliance and dispute overpayments of taxes.
Cockpits
similar to dashboards but narrower in scope and focus than dashboard.
Example of Unsupervised Approach
"Do our vendors form natural groups based on similar attributes?"
Tax Risk
(financial & reputational) Risk of misreporting or tax provision Adjustments.
Casual modeling
A data approach similar to regression but used when the relationship between dependent and independent variables where it is hypothesized that the independent variables cause or are associated with the dependent variable.
Classification
A data approach that attempts to assign each unit in a population into a few categories potentially to help with predictions. Used to predict whether a new vendor belongs to one class, or another based on the behavior of others.
Cluster Analysis (Clustering)
A data approach that attempts to divide individuals into groups in a useful or meaningful way.
Regression
A data approach that attempts to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model. Used to predict a specific value to answer a question.
Similarity matching
A data approach that attempts to identify similar individuals based on data known about them.
Link Prediction
A data approach that attempts to predict a relationship between 2 data items.
Class
A manually assigned Category applied to a record based on an event.
Unsupervised Approach
A method used for data exploration looking for potential patterns of interest.
3 sources of IRS Info
A repository of tax returns from prior years stored in a data warehouse, Data from social media on taxpayers, Personal financial data about each taxpayer (including SSN, bank accounts, & property holdings. Mostly gathered from prior returns, but also credit reports)
Tax data mart
A subset of a company-owned data warehouse focused on the specific needs of the tax department. Used to extract past and real-time data from the financial reporting system that is most applicable to the function.
Data Marts
A subset of the data warehouse focused on a specific function or department to assist and support its needed data requirements.
Supervised approach
An approach used to learn more about the basic relationships between independent and dependent variables that are hypothesized to exist.
Benford's Law
An observation about the frequency of leading digits in many real-life sets of numerical data. The law states that in many naturally occurring collections of numbers, the significant lending digit is likely to be small.
Documenting Book-Tax Differences
Assessing differences between the amount of income reported for financial purposes compared to the amount reported to the IRS for tax purposes. Used to identify and reconcile permanent/temporary differences.
Parts of Classification
Casual modeling, Similarity matching, Link Prediction.
Application of Diagnostic Tax Analytics
Creating a trend analysis for sales and use tax paid in different locations to identify seasonal patterns or abnormal transaction volume that warrant further investigation.
Structure of a Regression Model
Dependent Variable = f(Independent Variables)
Example KPIs of Tax Cost
Effective tax rate (ETR), Cash taxes paid, effect of loss carryforwards, Expiration of tax credits, Tax adj. in response to new tax legislation, Deferred taxes.
3 inputs of Tax Data in a Data Warehouse (Ex 9-1)
Enterprise data, Tax Tables, Reporting Data
What-if Scenario analysis
Evaluation of impact of different tax scenarios/alternatives on various outcome measures including amount of taxable income or tax paid. Attempt to optimize inputs to reach a goal.
3 Data Mart outputs of a Tax Data in a Data Warehouse (Ex 9-1)
Financial Data Mart, Tax Data Mart, Marketing Data Mart.
IMPACT model question for tax functions 2
How might tax analytics reduce the cost of compliance and tax planning by companies?
Tax Efficiency and Effectiveness
How well the technology, processes, and people carrying out the tax function operate.
Steps of Data Reduction
Identify the attribute to reduce/focus on, Filter the results, Interpret the results, Follow up on Results.
Steps of Classification
Identify the classes you wish to predict, Manually classify an existing set of records, Select a set of models, Divide Data into training and testing sets, Generate your model, Interpret results and select the "best" model.
Steps of Profiling
Identify the desired objects or activity , Determine the types you want to perform, Set boundaries or thresholds for the activity, Interpret the results and monitor the activity and/or generate a list of exceptions, Follow up on exceptions.
Steps of Regression Analysis
Identify the variables that might predict an outcome (independent variables), Determine the functional form of the relationship, Identify the parameters of the model, Evaluate the goodness of fit.
IMPACT model question for tax functions 3
If certain tax legislation passes, what level of exposure (additional tax) might the company face?
Tax Planning Questions
Impact of new tax rate on tax liability? // Are we minimizing tax burden by tracking all eligible deductible expenses/transactions that qualify for tax credits? // Impact of relocating headquarters to different city, state, country? // Tax exposure in case of merger or significant change in ownership? // Do transfer pricing contracts on certain products put us at higher risk of tax audit because of abnormal margins? // What monthly trends can we identify to help avoid surprises? // Can we reduce the number of assumptions in tax plan? // How are tax complexities addressed resulting from online sales due to new legislation? // How would tax law changes affect pension/profit-sharing plans/ to top employee compensation packages (including stock options)? // How would using different independent contractors affect payroll tax liabilities?
Examples of Tax Efficiency and Effectiveness
Levels of technology/tax training, Amount of time spent of compliance vs. strategic activities, Level of job satisfaction of the tax personnel, Improved operational efficiency.
Examples of Tax Sustainability
Number of company tax audits closed and significance of assessment over time, The effective tax rate (ETR) over time.
Tax Planning (TP)
Predictive analysis of potential tax liability and the formulation of a plan to reduce the amount of taxes paid.
Predictive Analytics
Procedures used to generate a model that can be used to determine what is likely to happen in the future.
2 primary methods of diagnostic analytics
Profiling and cluster analysis
Input variables for R&D Credit
Qualified research activities, wages, bonuses, stock options, supplies used for research, contract research exp. Paid to a third party, Avg. gross receipts over a 4yr. period, limits on research credit, carryforward credit balance.
Examples of Predictive Analytics
Regression, Forecasting, Classification, and other Predictive Modeling.
Examples of Descriptive Analytics
Summary statistics (count, minimum, maximum, average, median), distributions, and proportions, data reduction
2018 Tax Cuts and Jobs Act Tax Reform
Tax legislation offering a major change to the existing tax code. Allows investors to deter or eliminate taxes on capital gains in opportunity zones if gains are reinvested in opportunity zones.
Tax cost
The actual amount of tax paid.
R&D Tax credit
Under code section 41 for R&D. Is received by documenting an appropriate level of detail.
Fuzzy match
a computer-assisted technique of finding matches that are less than 100% perfect by finding correspondences between portions of the text of each potential match.
Profiling
a data approach that attempts to characterize the "typical" behavior of an individual, group, or population by generating summary statistics about the data. Done using structured data
Support vector machines
a discriminating classified that is defined by a separating hyperplane that works first to find the widest margin. (or biggest pipe)
Data Warehouse
a repository of data accumulated from internal and external sources, including financial data, to help management decision making.
Test data
a set of data used to assess the degree and strength of a predicted relationship established by the analysis of the training data.
Decision trees
a tool used to divide data into smaller groups.
Tax Data Analytics
allows tax departments to view multiple years, periods, jurisdictions, and differing scenarios of data typically through the use of a dashboard.
Tax focused KPIs
appear on dashboard or cockpits, consistent with the "C" (communicate insights) and the "T" (Track Outcomes) of the IMPACT Model.
Data Reduction
attempts to reduce the amount of information that needs to be considered to focus on the most critical items.
Structured data
data that are organized and reside in a fixed field with a record or file. Such data are generally contained in a relational database or spreadsheet and are readily searchable by search algorithms.
Summary statistics
describe the location, spread, shape, and dependence of a set of observations.
Management accounting relies heavily on
diagnostic analytics in the planning and controlling process.
Tax Authorities
evaluate credits & deductions & track trends over time
Training data
existing data that have been manually evaluated and assigned a class, which assists in classifying the test data.
Machine Learning
learns from past data to predict better outcomes.
Examples of Permanent BTDs to be Tracked
penalties/fines (excluded from TI), Meals and Entertainment (100% books, 50% tax), Int. on municipal bonds (non-taxed income), Life insurance proceeds (non-taxed income), Dividends received deduction (Tax based on % of ownership), Excess Depreciation.
Diagnostic analytics
procedures that explore the current data to determine why something has happened the way it has, typically comparing the data to a benchmark. As an example, allows users to drill-down in the data and see how it compares to a budget, competitor, or trend and discover the numbers driving an outcome.
Prescriptive analytics
procedures that model data to enable recommendations for what should be done in the future. These typically include developing more advanced machine learning and A.I. models to recommend a course of action based on a current problem. Most complex and expensive because they require structured and unstructured data.
Descriptive analytics
procedures that summarize existing data to determine what has happened in the past. (Summary statistics, distributions, proportions)
Descriptive Tax Analytics
provide insight into the current processes, policies, and calculations related to determining tax liability.
Tax Regulators
reconcile financial reporting data and tax data to reconcile BTDs
Tax Sustainability
refers to the ability to sustain similar tax performance over time. ("T" Track Outcomes)
Type of Data for Data reduction
structure data (data that are stored in a database or spreadsheet and are readily searchable)
Regression is a _______ method used to predict specific values
supervised
Classification is a __________ used to predict the class of a new observation
supervised method
Decision boundaries
technique used to mark the split between one class and another.
Use of Visualizations in Tax Analytics
to evaluate tax compliance based on expected rates, income, or sales.
