Presentation: The Future of Anti – Fraud Technologies

Presentation prepared for the Jamaica Chapter of the Association of Certified Fraud Examiners at their inaugural staging of the ACFE Jamaica Anti-Fraud Conference held on November 15, 2019 under the theme : Combating Fraud: Your Rights & Responsibilities.

INTRODUCTION

Financial fraud has existed since the dawn of commerce. One of the first recorded instances of fraud is the story of Hegestratos who was a Greek sea merchant in 300 B.C.

While there are varying accounts of the story, all agree that Hegestratos took out an insurance policy on a yet-to-be delivered shipment of corn. His plan was to sink his empty ship with the crew onboard, collect the insurance and sell the corn. Unfortunately for him, Hegestratos' crew discovered him in the act of sabotaging the ship and he drowned after being chased off the deck.

Since Hegestratos' time, criminals have found new ways to commit fraud which include asset misappropriation, vendor fraud, accounting fraud, payroll fraud, data theft, bribery and corruption. The reality is that where there is money, there is an opportunity to commit fraud.

COMBATING FRAUD – TRADITIONAL STRATEGIES VS THE NEW TECHNOLOGIES

To our credit (fortunately or unfortunately... whichever way you view it)A, the ways of combatting fraud has changed with few criminals being chased off the deck of a ship to their deaths. Laws and regulations have been implemented.

Today, several Government agencies exist internationally with the expressed aim of combating fraud. These include the Financial Conduct Authority (FCA) in the United Kingdom, the European Anti-Fraud Office in the European Union Commission and the U.S. Securities and Exchange Commission. In Jamaica. we have the Major Organised Crime and Anti- Corruption Agency (MOCA) and the Financial Investigations Division (FID). Important legislation such as the US Foreign Corrupt Practice Act (1977), US Computer Fraud and Abuse Act (1986) and UK Proceeds of Crime Act (2002) have also meant that Governments have created a supporting framework to punish fraudulent activities.

However, there remains a responsibility for organisations to implement measures to reduce instances of fraud – it comes down to the financial bottom line. This is a serious imperative when considering the findings of the 2014 Association of Certified Fraud Examiners (ACFE) Report to the Nations: Occupational Fraud & Abuse, which states that the typical organization loses 5 percent of its revenues to fraud each year! Even worse, the 2018 ACFE Report to the Nations: Global Study on Occupational Fraud and Abuse stated that the median cost of occupational fraud is $130,000 per case and the median duration is 16 months.

Traditional ways of combatting fraud are based on audit and compliance, risk management, client verification and surveillance systems for transactions. These traditional ways have served us well but times are changing and ways of detecting fraud must follow suite.

Technology

From the printing press to the computer, technology has changed our lives. Some believe that technology is a two-edged sword because it has allowed criminals to automate anti-money laundering tasks and perpetrate global financial crimes.

What is clear, however, is that efforts to stop fraud must employ new technologies in this fight. Artificial intelligence, machine learning, data analytics, biometrics, case management software, digital forensics, robotics, blockchain and online evidence capturing represent new artillery.

But, what really is this technology and what is it capable of?

• Data analysis technology enables auditors and other fraud examiners to analyze transactional data to obtain insights into the operating effectiveness of internal controls and to identify indicators of fraud risk or actual fraudulent activities.
• Online evidence capturing often implicates privacy, verification, and retention considerations that are not present when an organization captures or analyzes its own internal data. Because of the specialized nature of this type of data collection, various software programs have been developed to assist with collecting, documenting, and preserving online evidence.
• Case management software handles reactive tasks pertaining to the investigation of alleged or confirmed fraud. It can also deal with proactive activities relating to the identification of trends in fraud, its perpetrators and victims.
• Digital forensics and e-discovery software represent useful ways to capture digital evidence.

What is clear is that each of these technologies have different benefits. Therefore, clarity about the realities of your business and the scope of its anti-fraud programme are critical considerations before implementing anti- fraud technologies.

Artificial Intelligence

In recent years, artificial intelligence has become the buzzword within the industry due to the overwhelming move to digital and the increase in online transactions. Experts propose combining supervised and unsupervised machine learning as part of a broader Artificial Intelligence fraud detection strategy. The aim is to enable digital businesses to quickly and accurately detect automated and increasingly complex fraud attempts. But, what does this really mean?

Artificial intelligence can be used to reduce fraud in the following ways:

1. To spot potential money laundering activity by analysing transactional customer data
2. To identify complex fraud patterns
3. To detect bribery and corruption through the analysis of multiple sources of information found in emails, phone calls, messaging, and expense reports.
4. To capitalize on large-scale, universal data networks of transactions through fine-tune and scale supervised machine learning algorithms which simultaneously improves fraud prevention scores.

AI Considerations

Before rushing off to implement new AI technologies to combat crime, we must remember the following:

• AI as an anti-fraud technology is not a panacea. It has shortcomings - the inherently secretive nature of corruption and bribery makes it difficult to track using AI. Further, there are issues of data privacy and confidentiality especially when personal emails or phone calls are involved.
• AI risk management and crime detection should not be conducted in isolation. It should be linked to the broader AI strategy
• Increased use of AI tools for crime prevention could also cause external risks to cascade in unexpected ways. For example, banks may cause customer experience issues if they repeatedly identify customer activities as “suspicious” and block accounts when customers try to make a legitimate spend.
• Humans are still important to the process. While AI technologies assess fraud with minimal human intervention, humans are still needed to change algorithms based on patterns in data sets being analysed… at a minimum.

Take Up of Anti- Fraud Technologies + Flow

While AI does present exciting opportunities, we still have low take up for anti-fraud technologies across the board. The ACFE’s 2019 Anti-Fraud Technology Benchmarking Report states that only (39%) of companies use case management software, (26%) use digital forensics and e-discovery software and (30%) use evidence capturing software.

For us at Flow, we are leading from the front by deploying anti-fraud technologies which include AI, robotics and case management software. We have also made use of this technology to process huge volumes of data on which we apply our business rules. This means that we process approximately 10 billion data transactions monthly from over 150 data sources. Already, we are reaping the benefits having significantly reduced mobile data bypass fraud by making fraudsters mobile bypass apps useless.

The insurance industry has also signalled its intention to invest in anti-fraud technology. The 2019 Coalition Against Insurance Fraud report titled, The State of Insurance Fraud Technology, states the (64%) are looking to invest in predictive modelling, (43%) in link analysis/social network analysis, (36%) in text mining and (32%) in exception reporting/anomaly detection. The insurance industry has a vested interest in catching fraudsters because it goes to the core of their business model which requires them to investigate and pay fraud claims. However, this is just one industry. Could it be that we have forgotten the risk of not investing in technology?

We often speak of how Blockbuster and Blackberry became obsolete because they did not change their business model, but we can draw parallels with anti-fraud measures - not implementing anti-fraud technologies mean that companies are leaving themselves exposed amidst the march of fraudulent crime. Therefore, reputation risks, increased bleeding of funds, reduced business prospects and eventual insolvency are real possibilities.

CONCLUSION

So, what is the solution? We must combine the traditional regulatory strategies to combat fraud with the efficiencies of new technologies available.

Anti-fraud technology, like any other technology, is not the “silver bullet” in fraud protection and prevention nor is fraud detection and prevention a static process. It is an ongoing cycle involving monitoring, detection, decisions, case management and learning to feed improvements in detection back into the system. Organizations should strive to continually learn from incidents of fraud and incorporate the results into future monitoring and detection processes. This requires an enterprise-wide analytics life cycle approach.

The great news is that by combining traditional regulatory strategies with new ant-fraud technology, we are making a strike for the good guys and protecting the bottom line of our companies.

To stay ahead of the curve, the next generation of technologies aim to automate manual processes associated with combining large data sets and employing behavioral analytics. Indeed, there are exciting times ahead!