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INDUSTRY INSIGHT

Analytics wins by a landslide to curb voter and election fraud

Millions of voters, multiple ways to cast a vote and thousands of candidates and issues. Elections are data-rich events, and as the 2020 U.S. presidential campaigns made clear, fraud involving all that data is a hot topic.

Only slightly more than half of eligible U.S. voters cast ballots during the three most recent presidential election cycles, leaving a large swath of votes susceptible to potential chicanery in a normal election year. Moreover, 2020 is anything but normal. COVID-19 safety protocols make this year’s election one of the most complex to date.

The good news? Election-related fraud in the U.S. is exceedingly rare -- but that’s no reason for complacency. Government officials can rely on readily available analytics technologies proven in other industries to safeguard elections. Here’s why: Voting and election data are tailor-made for analytics that can thwart fraud schemes and help ensure every vote counts.

What’s the difference between voter fraud and election fraud?

In general terms, voter fraud is unlawful behavior by individual voters, like accepting money to vote a certain way or impersonating another individual – even a deceased person – to deceptively cast a vote. In contrast, election fraud involves large-scale, illegal interference in an electoral process, like hacking a machine to alter votes after they’ve been cast.

Election-related fraud comes in many flavors, including but not limited to:

  • False registrations: Claiming residence in a jurisdiction where one is not entitled to vote.
  • Duplicate voting: Registering in multiple locations and voting in the same election in more than one jurisdiction or state.  
  • Fraudulent use of absentee ballots: Requesting absentee ballots and voting without the knowledge of the actual voter.  
  • Ineligible voting: Illegal registration and voting by individuals who are not eligible to vote (e.g., non-citizens, certain individuals convicted of felonies). 
  • Altering the vote count.Changing the actual vote count, either in a precinct or at the central location where votes are counted.

What can election pros learn from other industries?

The banking and retail sectors have long battled fraud, and elections officials can apply similar technologies to secure voter data.

  • Banking fraud: Applying advanced analytic technologies like artificial intelligence and machine learning to customer behavior and social networking data helps financial institutions detect, prevent and even predict fraud. 
  • Retail and payments fraud: Amid the explosive growth in online shopping and contactless payments caused by COVID-19, data and analytics capabilities like data visualization and transaction analysis equip investigators with a 360-degree customer view to help authenticate a customer’s true identity and stop fraudulent activity. 
  • Benefits fraud: Government programs spend approximately 10% of their budget preventing fraud, waste and abuse. Analytics already helps agencies at all levels detect would-be fraudsters as they use unemployment scams, procurement and contract fraud, health care schemes and more to exploit government systems and data for financial gain.
  • Anti-money laundering: Advanced analytics help financial institutions detect and report suspicious activity indicative of criminals disguising the origins of “dirty money” earned from illegal enterprises like drug trafficking.

Applying data and analytics to protect elections

Election officials in some states already apply analytics to their voter data. For example, one Midwestern state is using analytics to help identify duplicate voter registrations and voters facing registration revocation due to inactivity ahead of the Nov. 3 election. Other potential ways in which analytics can help safeguard elections include:

  • Identity verification: Analytics applied to scanned state-issued photo ID cards and/or documented signature data can reveal possible fraud by automatically comparing the information and images to a central voter database.
  • Detecting suspicious activity: Applying analytics to absentee ballot and registered voter data allows election officials to spot unusual trends that may warrant further scrutiny. For example, anomalous trends in absentee ballots being returned from a specific precinct could signal a vote harvesting scheme at play.
  • Preventing cyberattacks:  Analytics can also help election officials detect fraudsters or cybercriminals intent on hacking voting machines or election management systems to change voters’ selection, or simply spread election misinformation online. 

The path forward

Election officials report more than 90 million people have participated in early voting in the 2020 election cycle. The pandemic is undoubtedly a contributing factor, but these trends could indicate a permanent change in voter preferences and force a change in election practices.

What about the possibility of online voting? If home buyers can secure a mortgage through a secured app or website, certainly voting online should not be beyond the realm of possibility. Federal, state and local governments must embrace the analytic technologies successfully used by the financial and retail sectors to make it possible for registered voters to cast their ballots safely and securely.

Regardless of one’s political affiliation, keeping votes and elections secure is fundamental to a healthy democracy. We live in an age where the mere hint of malfeasance, true or not, can sow discord and doubt into an election cycle and erode voter confidence. Data and analytics can help instill additional trust in the people and systems that underlie one of our most sacred acts. Now is the time to start planning for the next election.

About the Authors

Alex Boakye is cybersecurity R&D director at SAS.

Steve Bennett is director of public sector and financial services at SAS.

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