Better Business Through Data Analysis & Monitoring My Account

Top 10 Areas Where Data Analysis Adds the Most Value

Survey Results from Audit & Accounting Professionals

Results from Survey Conducted by Audimation Services, Inc.

During the past year, we gathered responses from our users at events, focus groups and various encounters along the way to see what information would be most helpful in their work. The most common request we receive is, “tell me how data analysis is being used in other organizations.”

We surveyed our extensive database of accounting, auditing and financial professionals to find out what data analysis project or technique has brought them the most value. Nearly 600 individuals provided valid responses, and many provided direct examples of how they are using data analysis in their work. The survey also asked internal auditors to share information about the number of staff, which is as follows:

1. AP/AR

Given the sheer amount of data embedded within Accounts Payable (AP) and Accounts Receivable (AR), data analysis is adding the most value in these areas. Many noted they are reviewing data within the vendor master file, while others mentioned these specific areas:

  • Purchasing to payment analysis
  • Review of operating disbursements, with primary focus on AP
  • Validation of payments to vendors
  • Analyzing AR open order data for system deficiencies within processes
  • Evaluating AR aging files for internal and external financial reporting
  • AR testing and searching for duplicate payments

Notable Quote

“Currently we have been able to add value from a fraud perspective by performing audits of AP vendor master maintenance and AP transactions. We have also added value via our journal entry analysis.”

2. Duplicate Detection

If you’re looking for recovery dollars, fraud, errors, anomalies or outliers, duplicate detection is a proven technique used to find them. Survey respondents indicated value in use of testing, analysis and review of expenses. Common areas for duplicate detection searches include payments, invoices, transactions and vendor returns for credit.

3. Sampling

Sampling is a fundamental part of audit work, and with so many ways to sample, this frontrunner is no surprise. Multiple survey respondents indicated they use IDEA’s statistical sampling methods for their sampling work to set the scope, providing defensible and valuable insights when results are extrapolated against the population. One internal auditor noted they use the statistical functions, summarizations and stratifications to allow management to analyze data to make projections and evaluate past performance.

Some survey respondents provided details, such as using stratified sampling to examine gains and losses on backdated trades, stratify invoices and disbursements, and perform random samples. Data analysis is also used to sample and perform key word searches. One of the many benefits data analysis technology offers is the ability to analyze an entire population of data, as opposed to sampling. However, data analysis also allows you to join, sort and summarize areas of data to analyze smaller data sets.

Notable Quotes 

“We use IDEA to help select sample sizes and perform audit tasks, which has greatly reduced audit time and manpower requirements.”

“The ability to sort through large data populations of GL data has helped us greatly. Being able to combine databases has also been a help since it is hard to have IT create one database at times.”

4. Data Imports/Extractions and Analysis of Large Data Sets

Most auditors or accounting professionals will tell you their biggest challenges are knowing where to apply data analysis, getting the data they need and importing it into an analysis tool. Data analysis software developers have made great strides in developing new technology to simplify data imports, such as the addition of PDF converters, drag-and-drop capabilities, and the expansion of data capacity limits. Survey respondents indicated one of the greatest values data analysis offers them is the ability to convert PDF files, text data and information stored in spreadsheets into an analysis tool. Many responded they were using data analysis to perform data extractions, which would be nearly impossible for them otherwise, and extracting data based on certain criteria such as by name or customer codes. One individual stated their overall use of IDEA and ODBC instead of MS query and SQL to download, analyze and summarize data had saved them hundreds of hours.

Those surveyed said they value the ability to import and handle large amounts of data to be analyzed for different criteria, and setting up different worksheets within a file to perform various audit steps. Auditors are using data analysis to perform big downloads of financial transactions during the audit period, combined with summaries and analysis, to help scope and test during the audit. An internal auditor within the health care industry stated they are using data analysis to obtain entire payment data from an ERP system to conduct analysis on areas such as payment dates on weekends, and search for duplicates and vendor classification coding errors.

Notable Quotes 

“Being able to import various types of reports (text, PDF, Excel, etc.) into the software has been most beneficial when attempting to compare data from various repositories. This process has been used to compare active employee records against payroll registers and building access (security) reports.”

“The most useful aspect of IDEA is the amount of information the program can hold. We do many audits that involve server data, which can be quite large. Without IDEA, we would not be able to analyze this data.”

Data analysis continues to be used to automate manual processes and testing by implementing continuous auditing. Several internal auditors responded they value the ability to develop continuous audit scripts to look for errors in account entry and the use of continuous monitoring for travel and entertainment (T&E), financial statements, p-cards, human resources and accounts payable.

While continuous monitoring can provide near real-time information to identify control breaches, several survey responses indicated they were using continuous monitoring monthly or quarterly. One respondent noted they use continuous auditing in their audit department to monitor credit data, market feeds, credit and financial information to track and flag significant changes. Another stated they use continuous monitoring for Foreign Corrupt Practices Act (FCPA) compliance.

Notable Quote 

“Continuous monitoring of store transactions where we score each unit and research the outliers.”

6. Fraud Detection & Forensic Auditing

While you may stumble upon fraud by searching for outliers or anomalies, many auditors and accountants are using data analysis technology as a forensic tool to search for fraud and schemes. Data analysis tools allow you to look at the data from different angles to get to the root cause of fraud, which is what many of our survey respondents found most valuable. Some of the ways data analysis is being used to search for fraud include trend and pattern analysis to look for indications of diversion of funds or theft, behavioral analysis and monitoring of spending trends.

7. Analysis of P-Cards

Procurement or purchasing cards (p-cards) have simplified the amount of administrative work organizations handle to process small purchases, but also increased risks. While p-card abuse has made headlines, particularly in government departments, they can be managed by implementing proper internal controls to reduce misuse and waste. It’s naturally an area accountants and auditors must analyze to search for evidence of red flags, review transactions and track trends.

Notable Quote 

“The ability to script IDEA tests has enabled our company to automatically identify potentially anomalous procurement card transactions with maximum efficiency.”

7. Payroll & Time Sheets

Hunting for ghost employees, falsifying wage claims and tampering with time sheets are all key areas where data analysis is adding value, according to those surveyed. One respondent indicated they conduct “payroll weekly dollar or total reasonableness testing,” while another stated they use IDEA to perform 30+ analysis procedures on a quarterly basis covering purchase-to-pay, revenue, journal entries and payroll. Data analysis is also bringing value by enabling review of electronic time entry records for compliance with existing policies, procedures and labor regulations.

Notable Quote 

“Through the use of IDEA our payroll department has reduced the time required to review payroll prior to their weekly transmission to ADP from several hours to less than 30 minutes.”

9. Joins and Comparisons

Few will argue that one of the biggest values data analysis brings is the ability to join databases and files to sort, summarize and analyze data – again, enabling users to look at the data from different angles to search for outliers, fraud, errors and other information. Those surveyed provided some applications of using joins to check for anomalies, create inventory turnover or perform open to sell analysis, and extract data from PDFs, then join it together for analysis. One survey participant stated they join databases to save hours reconciling outstanding check lists and another stated they benefit from joining large databases to replace a manual comparison process. Areas were data analysis is being used to compare sets of data include:

  • Active application user accounts against a list of terminated employees
  • Physician scheduling system to the billing system
  • Vendor terms including days paid early and aged receivables
  • Missing invoice numbers
  • Employee/HR to vendor address
  • Tax ID numbers and conflict of interest
  • Review of billing and pricing agreements against contract agreements

Notable Quote 

“Comparing the HR files to the AP vendor files provided information leading to employee fraud of valuable assets and other services. This technique provided the link needed to connect the employee’s address to the AP vendor delivery address, thus giving the needed data for further investigation.”

10. Inventory Audits

Given the massive size of some inventories, data analysis is being used to conduct inventory audits. It is being used to identify potential or obsolete inventory, slow-moving inventory, reconciling the inventory count with the general ledger, and performing sampling, valuations and testing on inventory data. One person surveyed noted they use data analysis as a business intelligence tool to better understand both long- and short-term inventory risk, and another indicated they analyze (oil and gas) well, property and cost center data.

Honorable Mentions from Survey Findings
While reviewing some of the survey comments, we found a few creative, or somewhat unexpected uses of data analysis we thought were worth mentioning:

Centralized Accounting & Data Mining
“Centralized accounting and related services for processing company transactions. There is more volume in terms of transactions, but because it is done via centralized accounting, the data is easier to obtain and analyze.”

Compliance
Several survey respondents noted they find data analysis valuable in meeting industry and documentation standards. One individual stated their internal audit department uses data analysis for planning, executing and document SOX procedures as well as audits of other areas and processes.

Data Warehousing
“A growing number of data warehousing efforts with key data being extracted from legacy systems spread across the enterprise from various product lines. A long overdue process that is showing good results for data analysis on many fronts.”

Population Testing
“We try to incorporate data analysis in every audit we do. The biggest win for us has been performing a lot more population testing, instead of doing sampling. It takes the same amount of time for us, but provides much more clarity and value to the client.”

Summarization
“Summarization of data in IDEA (tool) that couldn’t otherwise be summarized by company personnel. This gave us confidence that a process was working as expected.”

Teaching Tool for College & Universities
IDEA is taught by more than 160+ colleges and universities throughout the U.S. to help educators bring data analysis techniques and technology into the classroom. One professor stated: “I teach fraud examination and forensic accounting at the university, so IDEA fraud analytics has been of the most value for exposing my students to data analysis capabilities in fraud prevention and detection.”

Reconciliation
“The most important project involving IDEA at this organization has been reconciling government data to the organization’s mainframe. This is a requirement of the government contract.”

Revenue Reporting
Many of those surveyed stated they use data analysis for reporting purposes including the distribution of company-wide reports used to analysis financial results. “IDEA has enabled our company to analyze data for balancing and reporting purposes more quickly and efficiently. The program builds on techniques that other software utilizes.” Another survey respondent noted, “Revenue recognition with IDEA that was not feasible to be performed by any other means.”

Creative Uses:

  • Hourly energy bidding analysis
  • Analyzing customer behavior around service renewal periods
  • Analyzing customer surveys
  • Measuring the effectiveness of a promotional program
  • Analysis of financial and student enrollment data
  • Direct billing review project
  • FCPA monitoring
  • Evaluation of fixed asset balances
  • Integration of student information system with online learning management systems
  • Risk assessment
  • Medical bad debt projects
  • Testing information in various system logs
  • Banking – Analysis of where wires were being split to avoid limits
  • Loan grade and portfolio trending

Our survey of nearly 600 accountants, auditors and financial professionals working in various industries provided us with some interesting insights about how data analysis was being used, and which areas they believe were most valuable to their respective organizations. While data analysis has been around for more than 25 years, it continues to evolve in its technology advancements, use and significance. As one of our survey respondents noted, “There’s just an immense amount of ways the data can be analyzed.” Using data analysis technology to help you perform better, more in-depth, analysis in less time with minimal effort is not only effective, but worthwhile.

Survey conducted in 2011 by Audimation Services, Inc. and analyzed by a third-party marketing consultant.

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