Every year, countless people are conned out of their money by criminals. These swindlers frequently change maneuvers to evade detection. To succeed, they rely on a complex “modus operandi” (method of operation, or MO) and sophisticated, dynamically evolving fraud schemes.

As they investigate fraud schemes and scams, the police face challenges at every turn. They contend with high volumes of data, staff shortages, and fragmented methods and locations for storing data. Analytics is a crucial tool for law enforcement to use in detecting and preventing these crimes.

Data management and evidence-based policing: Where it begins

Successful investigations start with a strong data management foundation that stores and provides timely access to high-quality, trustworthy and relevant information. When this data is used with analytics, it supports investigators in doing their jobs more effectively. It also helps law enforcement gain the trust of the communities they serve and gives them the information they need to protect people from harm – whether physical, emotional or financial.

Evidence-based policing augments traditional policing approaches with data-driven insights from artificial intelligence (AI) and other analytics-based tools. Together, this improves resource allocation and leads to better outcomes for police departments and the communities they serve.

Overcoming the challenge of bare-bones police forces

Due to officer shortages on the front lines, investigators who focus on fraud are often used to fill in gaps. This happened frequently during the pandemic, but it also happens when local police are faced with a large-scale event that requires additional support. As a result, fraud investigators’ specialized skills may be missing from intricate fraud inquiries. Because criminals rapidly develop new techniques, officers investigating financial crimes are behind the curve when they return to their usual duties.

Fraud investigators face tremendous stress in managing large volumes of complex investigations. Their burden is intensified because investigations need to be handled with exceptional accuracy and speed to counter imminent risks. As soon as the criminal’s MO is understood, investigators must share that information and take preventative action to stop the criminal activity and protect innocent people.

The investigative cycle is constantly adapting to keep up to date with continual changes in the criminal landscape and tactics used to carry out the crime. Analytics helps officers understand manipulation techniques, digital mediums used and victim profiles targeted. In turn, officers know which interventions will make a tangible difference in the criminal’s operating environment.

Allocating the work evenly

Automation, analytics and workflow management help ease the burden by clearly depicting an accurate view of workflow and volume. Supervisors can easily see:

• How work has been allocated.
• What the bottlenecks are.
• Ways to better manage the process – and therefore the progress – of investigations.

Guided by analytics insights, supervisors can allocate tasks evenly across teams and identify urgent training needs. Analytics also streamlines the management of heavy volumes of criminal reports. Manual reviews could become burdensome without this technology and lead to investigational inefficiencies.

Spotting trends and responding faster

A central reporting model for fraud and scams solves problems inherent in relying on multiple platforms – and is beneficial for investigating and preventing fraud. With this approach, law enforcement can:

• Triage all reports quickly and efficiently based on risk level and degree of criminality.
• Get a comprehensive look at potential future issues.
• Gain an overall view of the extent and reach of criminal activities.
• Understand what drives and facilitates fraud – including social media, websites and chat messaging services.
• Identify fraud trends faster and more accurately.
• Implement a best practices intervention and disruption strategy.
• Share results with the public from this easy-to-use analytics tool.

Having a single platform allows law enforcement to collect data centrally in a variety of formats, including victim information. From there, investigators can understand and analyze:

• The geographic range of fraud.
• Specific fraud tactics.
• Victim demographics.
• The monetary value of fraud schemes and scams.
• Intervention points.
• Opportunities for disruption and fraud prevention.

Obtaining a single view of information overcomes many issues inherent to multiplatform solutions. A comprehensive view allows investigators and senior officers to make fast, informed decisions based on all available data. For victims of fraud or scams, these efforts can make a huge difference in their lives by limiting the extent of financial and reputational damage.

In my experience, many officers and staff dealt with convoluted work practices stemming from multiple databases that stored information – constraining their ability to search and find data quickly. Analytics gave us more effective, efficient ways of accessing information so we could step back and look at the full investigations process.

Effectively gauging risk

Most law enforcement agencies lack sufficient numbers of officers and staff, so they constantly juggle heavy workloads. To manage these demands, investigators need to understand which cases represent the highest risk so they can prioritize accordingly.

Triaging information early in the investigation is vital. It's essential in identifying which incident, case, suspect or victim presents the most significant threat, risk and harm. Subsequently, this knowledge helps dictate the action law enforcement takes and the pace at which it happens.

SAS sends automatic alerts based on the assessed risk level so investigators can quickly digest fraud reports and determine the highest priority cases. A “risk scorecard” reflects various risk criteria – all informed by law enforcement expertise. For example, the scorecard could flag someone known for violent crimes.

An embedded risk definition generates alerts to investigators that direct them to read the most pertinent information first. These alerts are valuable – not just for supporting investigations but also for protecting communities and officers performing their duties.

 Linking small crimes to a bigger picture

With thousands of daily reports related to attempted fraud, perpetrated fraud and scams, SAS Analytics is essential to helping police quickly identify connections among fraud and scam networks. Two of the key technologies that uncover relationships that would otherwise go unnoticed are entity analytics and text analytics.

With these techniques, investigators can efficiently assess and identify links to previous reports, suspects, and any other linked entity across the entire database. More importantly, this approach helps investigators quickly determine their next steps.

An example 

Consider a law enforcement agency that received 30,000 fraud reports in a month. About 2,000 appeared to be limited, with just one victim for each report and a low amount of fraud (in the $50 to $100 range). If reviewed individually, each case would appear to be low risk and low priority. However, on conducting an overarching analysis of all the incidents, the investigator discovered the same telephone number in 1,100 of those reports.

This example illustrates how investigators can find similar MO, data and suspects through a comprehensive view across numerous reports. In turn, they can link a single suspect to multiple crimes. This builds a stronger case against that person, supports a longer sentence for the criminal and helps ensure a safer community.

Understanding outcomes

Law enforcement agencies are committed to organizational learning. This approach helps officers understand more about the impact of their efforts and how procedures and policies should change to become more effective.

By extracting insights from the crime – and the organization’s response – investigators can evaluate whether their actions reduced the number of crimes committed and prevented crimes from recurring. This analysis also helps agencies determine whether they have protected victims from additional fraud attempts.

Such historical analysis is priceless. It’s the only way to know how specific past police responses to fraud and scams affected criminals’ ability to operate and prey on victims. Analytics can also improve the way law enforcement organizations investigate future crimes of fraud and scams by making it easy to promote and embed best practices throughout the investigations process.

Why analytics from SAS?

Law enforcement agencies that use a single analytics platform can overcome significant obstacles to conducting fast, thorough investigations into fraud and scams. A solid data and analytics approach to investigations often leads to deeper insights, more efficient working methods, increased arrests, stronger criminal cases and a safer community.