Founder, Personable Inc.
“Manually tracking money is no longer the solution for professionals.” – Benjamin Chou
The COVID-19 pandemic has presented rare opportunities to commit fraud. For example, a Florida man obtained loans under the Paycheck Protection Program (PPP) valued at $3.4 million by submitting false IRS records.
Bringing cases like this using manual data handling and analysis is burdensome. To develop the evidence you need against the perpetrator, you need to sort through a mountain of financial data.
As a fraud investigator, you spend so much time preparing the transaction data, you may miss seeing the bigger picture. You may not identify the patterns of money moving in and out that characterize fraud, money laundering and other financial crimes. According to one study, up to 85% of financial crimes involve non-analytical and administrative data handling.
. Automated data visualization tools can help you focus on your jobs rather than data entry, and provide a way to automate both laborious data handling and intelligent data modeling.
The COVID-19 pandemic created a pandemic of fraud
The COVID-19 pandemic has opened the door for criminals to defraud state and federal government programs. Fraud investigators at both the state and federal levels have found hundreds of instances of fraud in relief programs.
Since the U.S. Congress passed the CARES Act, the U.S. Department of Justice (DOJ) has prosecuted more than 100 defendants for fraud in over 70 separate cases.
These cases have resulted in businesses fraudulently acquiring government resources that should have gone to businesses, health care facilities and employers that needed assistance.
Here are three ways fraud investigators can benefit from automated data visualization in their pandemic-related fraud investigations.
Benefit #1:Solve crime faster
Time is money. During the COVID-19 pandemic, time can also cost lives and extend the economic downturn.
A slow fraud investigation could allow fraud perpetrators to add millions of dollars to their take. Moreover, slow investigations mean that you can only catch perpetrators after the fact rather than intercepting fraudulent transactions in real-time. According to the United Nations, investigators intercept fewer than 1% of illegal transactions. The rest reach their destination, and investigators may never recover them.
Fortunately, technology today can reduce months of data preparation time to a few days automatically and accurately. For instance, converting financial documents into normalized and reconciled data is possible at super high speed.
Once transactions are collected, fraud investigation software can cleanse the data in more systematic ways. This avoids introducing human error into the data cleansing process while eliminating data artifacts that could slow down an investigation. By flagging and removing duplicate entries, typographical errors and other problematic data, investigators get better source data for their analyses.
Automating the visualization can drastically reduce the data analysis time and expedite the fraud investigation. For analysis, there exists software that can automatically prepare models and even identify suspicious patterns of financial transactions.
Benefit #2: Sidestep technical hurdles
You know financial analysis. However, it could be daunting for you to use complex tools for creating models for data visualizations. With organizations planning to increase their anti-fraud technology budget, you could face a steep on-the-job learning curve.
Excel, Power BI and other popular data handling software can produce powerful data visualizations, but they do not have any built-in intelligence for modeling financial data. Instead, investigators must learn how to create the models that create the visualizations that will assist their analyses. Moreover, even with such powerful software creating models for visualizations is pretty complex.
Instead, you need software specifically designed to provide automated financial data analysis for fraud investigation. For example, software that offers pre-designed data models and auto-populates the models from financial documents.
Benefit #3: Prepare compelling case narratives
Ultimately, the goal of your investigation is to prepare the evidence that will help you identify criminal activity. But this evidence must also convince a judge, jury and even the accused perpetrator of your analysis.
Data visualizations models like “flow of funds” can help you analyze transactional data more efficiently. Data visualizations put data into forms that allow you to identify suspicious patterns of transactions. As a result, investigators get visual confirmation of trends and outliers that can characterize fraud.
For example, an analysis of fraud cases arising from the PPP found that the accused perpetrator mostly either fabricated payroll documents or tax documents. Data visualization that applies Benford’s Law can indicate anomalies in a collection of payroll values or tax values. Genuine values tend to have the first digit of 1, 2 or 3. And falsified values might include first digits that were evenly distributed or favor first digits of 7, 8 or 9.
Data visualizations allow investigators to create interactive or dynamic exhibits for jurors and judges by filtering, identifying and interrelating with data. You can highlight the fraudulent activity and withstand cross-examination from the accused perpetrator’s defense counsel with the correct data visualization.
Move your investigations forward
Rather than spinning in circles and chasing your tail, move your pandemic-related fraud investigations ahead.
Automated data visualization software can relieve yourself (or data entry clerks) of data capturing, cleaning and normalizing. It helps you focus on the data rather than developing technical expertise to create models for the investigation. Develop compelling case narratives using automated data visualizations to produce faster, more efficient and more favorable outcomes in your investigations.
SOURCE: ACFE Insights – A Publication of the Association of Certified Fraud Examiners