Steve Weisman, JD, is a renowned expert in scams, identity theft, and cybersecurity.
As a lawyer, professor at Bentley University, and author of more than ten books, including The Truth About Avoiding Scams, Steve has dedicated his career to understanding and combating fraud.
His expertise has been featured in publications like USA Today and on major media outlets including ABC, CNN, and Fox.
To start, can you tell us a bit about yourself? We’d love to hear about your background and the experiences that have shaped your career in fraud investigation and cybersecurity.
I’m a lawyer from Massachusetts and a professor at Bentley University, where I teach White Collar Crime. Before Bentley, I taught in prison education programs. Many of my students were convicted scammers, and their stories fascinated me. They would often say how fraud used to require skill, but today, a teenager with a computer can pull off the same scams.
Fraud has always interested me because it evolves with technology. For example, the Nigerian email scam is actually an updated version of a 16th-century scam called the “Spanish Prisoner.”
On a personal note, I became a victim of identity theft myself, which deepened my drive to educate others about these threats. I even started a blog, Scamicide.com, to track scams and share advice.
Throughout your career, you’ve covered scams, cybersecurity, and identity theft. What trends in financial fraud have you observed over the years, and how have they influenced the methods investigators use today?
While scams don’t fundamentally change, they evolve with technology. For instance, digital fraud is now a major issue. Groups like the Russian cybercrime group, Karbanak, have electronically robbed banks by exploiting spear phishing.
One notable example is the Bangladesh Bank Heist. Cybercriminals used phishing emails to install malware, learn the bank’s SWIFT system, and impersonate employees. They sent fraudulent transfer requests to the Federal Reserve, nearly succeeding in laundering millions. This case highlights how fraudsters exploit technology and the need for investigators to adapt their methods accordingly.
Fraud schemes have grown increasingly complex. In your view, what are some common investigative challenges that come with this complexity, and how can investigators overcome them?
The complexity of modern fraud schemes lies in the volume of data and the sophistication of cybercriminal tactics, including deepfakes and social engineering. AI offers a significant advantage here. It allows investigators to analyze vast amounts of transactional data in real-time, recognize deepfake patterns, and detect irregularities quickly.
However, investigators must stay ahead by constantly updating their tools and techniques. AI is a double-edged sword—it can be used both for committing and detecting fraud. The key is leveraging it effectively while staying vigilant.
With technology advancing rapidly, data has become more accessible. How do you see the role of data changing in fraud investigations, and what advantages does it bring to uncovering fraud?
Data is pivotal in modern fraud investigations. Advanced data analytics can identify patterns and irregularities across large datasets, often in real-time. This capability is invaluable for tracing financial activities and uncovering money laundering schemes.
AI-powered data analysis can also profile high-risk targets and detect insider threats through behavioral analysis. By harnessing data effectively, investigators can uncover hidden patterns and take proactive measures to prevent fraud.
Artificial intelligence is increasingly applied across many industries, including fraud investigation. What are some of the most promising ways you see AI aiding fraud investigators today?
AI is a game-changer. Its algorithms can analyze vast transactional data, compare it with historical trends, and even predict future risks. For example, AI can identify irregularities in financial activities, enabling investigators to detect and prevent crimes in real-time.
Predictive analytics is particularly promising—it helps investigators anticipate potential fraud by analyzing behaviors and patterns. This proactive approach can stop crimes before they happen.
Many worry that AI could be a double-edged sword, as fraudsters can also use it to their advantage. What risks or ethical considerations should investigators keep in mind when using AI in their work?
AI’s biggest risk lies in the quality of its data. Investigators must ensure their sources are reliable and free of biases. Additionally, ethical concerns around personal data usage must be addressed.
Transparency is essential. People should be aware of how their data is being used. For example, opting into data sharing for security purposes should be a clear and informed choice.
In addition to AI, other technologies like machine learning and data visualization are gaining ground. What impact do you think these technologies have on uncovering hidden patterns in financial transactions?
Machine learning and data visualization are invaluable tools. Machine learning detects anomalies by analyzing historical data and identifying deviations from normal patterns.
Data visualization, on the other hand, helps investigators communicate findings clearly. Visuals make complex data accessible and actionable, which is crucial when presenting evidence or engaging with stakeholders.
Looking at identity theft, a persistent issue in financial fraud, do you think AI-based technologies offer new solutions to prevent or mitigate it, and if so, how?
Absolutely. AI is revolutionizing identity theft prevention. Technologies like multifactor authentication, voice and facial recognition, and behavioral biometrics are enhancing security.
For instance, AI can analyze behavioral patterns to detect suspicious activity, such as unusual login locations or typing speeds. These advancements significantly reduce the risk of identity theft.
For federal and state investigators, integrating new tools can sometimes be challenging. What advice would you offer agencies looking to adopt AI-based solutions for fraud detection and analysis?
Adopting AI requires a phased approach. Start small and focus on unifying data platforms across agencies. AI can enable seamless collaboration by breaking down data silos and sharing insights in real-time.
Agencies should also invest in training and establish feedback loops to continuously refine their models. Collaboration and gradual integration are key to success.
Lastly, looking toward the future, where do you see fraud investigation evolving in the next decade, especially with advancements in AI and other technologies?
The future of fraud investigation lies in 24/7 real-time monitoring powered by AI. This will enable investigators to flag suspicious behavior instantly and even predict crimes before they occur.
Blockchain technology will also play a significant role in securing transactions, and quantum computing will dramatically enhance data processing speeds. These advancements will make fraud investigations more efficient and effective than ever before.
Before We Go
Fraud investigation is entering a new era, driven by AI, machine learning, and advanced data analytics. As Steve points out, staying ahead of fraudsters requires constant innovation, vigilance, and collaboration.
Tools like ScanWriter AI are at the forefront, empowering investigators to stay ahead.
One of the most critical features of ScanWriter AI is its on-premise solution, which ensures your data remains 100% secure. Unlike cloud-based tools, ScanWriter AI processes data locally, eliminating the risks of external storage.
By automating document conversion, providing real-time analytics, and detecting hidden patterns, ScanWriter AI helps fraud investigators tackle even the most complex cases. For federal and state agencies, it’s a game-changer.
Discover how ScanWriter AI can transform your fraud investigations. Learn more here.