According to a report by Juniper, global online payment fraud is projected to cost businesses over $343 billion from 2023 to 2027. This surge in transaction fraud poses significant challenges for fraud investigators, who must conduct thorough examinations of financial data to detect fraudulent activities.
Fortunately, advancements in technology have led to the development of extremely useful financial investigation software. These tools are designed to automatically collect, clean, and organize data for analysis. They automate user-friendly data visualizations, enabling users to effectively identify and prevent fraud and money laundering.
This article delves into the role of technology in uncovering transactional fraud, with a specific focus on ScanWriter by Personable Inc., a key resource for investigators. We will explore how this cutting-edge tool bolsters the fight against transaction fraud, providing actionable strategies for immediate application.
Understanding the Challenges of Investigating Transaction Fraud
The Federal Trade Commission and law enforcement agencies are currently facing a multitude of complexities and challenges when dealing with transaction data while investigating fraud.
Let’s understand these challenges in detail.
#1. Complexity of Financial Transactions
The challenge in detecting transactional fraud lies in the intricate nature of modern financial transactions. These transactions aren’t just numerous; they vary widely in form, ranging from credit card payments and bank transfers to digital transactions. Each type has distinct features and patterns, creating a complex landscape for investigators.
Fraudsters exploit this complexity with advanced techniques. For example, in credit card fraud, the issue isn’t just the quantity of transactions but the sophistication of the fraud. Criminals might use encrypted stolen card details, create convincing counterfeit cards, or employ high-tech skimming devices. These methods mimic normal transaction patterns, making them difficult to detect among the millions of legitimate transactions happening daily.
Moreover, as fraudsters continually evolve their tactics to circumvent detection, what might be a red flag today could change tomorrow. This constant evolution, coupled with the variety of channels through which fraud can occur (online, in-person, over the phone), adds to the complexity.
Addressing this concern requires a dynamic, technology-driven approach. Advanced data analytics, artificial intelligence, and machine learning are key, offering flexible and sophisticated detection capabilities to combat evolving fraud tactics effectively.
#2. Volume and Velocity of Data
The sheer number and pace of daily transaction processing make it difficult to identify fraudulent activities in real time.
Take a look at the Federal Reserve Payments Study(FRPS) on Developments in Noncash Payments for 2015, 2018, and 2021:
Source: Federal Reserve
This data shows that the value of core noncash payments in the United States grew faster from 2018 to 2021 than in any previous FRPS measurement period since 2000 — highlighting an increase in online payments, which opens the doors to more fraudulent transactions.
To make it easy, although the Dark Web does not directly process online payments in the same way that conventional e-commerce platforms do, it does function as a marketplace for stolen details ranging from $10 to $1000. The usage of cryptocurrency and other untraceable payment methods on the Dark Web complicates law enforcement and cybersecurity professionals’ efforts to detect and prevent illicit financial transactions. For instance, in June 2023, U.S. Attorney Gary M. Restaino and other federal law enforcement partners formalized the Darknet Marketplace and Digital Currency Crimes Task Force (DNMDCC Task Force).
To tackle such complexity, only building a task force is not enough, but they might need modern technology that can quickly scan enormous datasets and find anomalies.
Otherwise, the everyday verification process will potentially lead to human errors and divert employees’ attention away from their core goals — reducing productivity.
#3. Lack of Advanced Tools
Look at the growth of phishing attacks by year:
The scenario above, along with the data on growing phishing attacks, demonstrates the critical need for improved technology. As the number of such frauds grows each year, identifying and combating fraud becomes more difficult.
#4. Lack of Resources at Law Enforcement Agencies
The latest Federal Trade Commission data shows that consumers reported losing nearly $8.8 billion to fraud in 2022, an increase of more than 30 percent over the previous year.
As the number of transactional fraud cases is increasing, law enforcement agencies combating transaction fraud are dealing with massive backlogs due to limited resources, including a limited workforce and outdated technology.
Advanced technological tools, such as AI and data analytics, provide an efficient way to reduce these backlogs in fraud investigation processes without the need to hire additional resources. These solutions allow for rapid data analysis, prioritizing high-risk cases, and streamlining document review, resulting in a more agile and cost-effective strategy to manage higher caseloads.
#5. Sophistication of Fraudulent Schemes
The ever-evolving sophistication of fraudulent schemes, such as identity theft, of which FTC has received 1.4 million cases, necessitates ongoing adaptation in advanced investigation tools.
Criminals steal important personal data, such as Social Security Number, home address, and sensitive financial information, in order to assume the identity of the victim and commit fraudulent acts for financial gain.
Detecting synthetic identity fraud is problematic because it uses authentic aspects that make inconsistencies difficult to detect. Extended credit buildup, high-value investments, organized rings, multinational operations, and the use of deep fakes and AI all add to the complexity.
In this case, the investigation process becomes time-consuming and technically complex, necessitating investigators to keep technologically updated and use highly accurate tools like ScanWriter, which offer 100% accuracy and high speed in data processing.
How can ScanWriter Help in Transaction Fraud Investigations?
In financial fraud investigations, where time is crucial, investigators and accountants often struggle with the time-consuming task of manual data entry. Hiring extra staff to manage this workload can lead to increased human errors and additional financial burdens due to taxes and benefits.
However, there is a solution. ScanWriter, a technologically advanced tool tailored for district attorneys, forensic accountants, and fraud investigators, streamlines the laborious data entry process, providing accuracy and efficiency in handling financial data. By integrating ScanWriter into their workflow, anti-fraud professionals can focus on the more crucial aspects of their investigations, bypassing the need for an additional workforce.
Here’s what you’ll get:
1. Automation in Data Capture
While investigating transactional fraud, the challenge of managing large volumes of transactional data is a major hurdle. The traditional method of manual data entry is not only slow but also prone to errors and inconsistencies.
To address this, investigators can turn to ScanWriter, a specialized tool that employs advanced optical character recognition (OCR) technology. This technology facilitates swift, smooth, and automated data capture, greatly enhancing the efficiency of fraud investigations.
ScanWriter stands out due to several key features like:
- Capability of extracting data automatically from over 1,000 checks per hour, greatly reducing the need for manual input.
- Supporting more than 40,000 data formats from various sources, such as bank statements and invoices, and easily adapts to new formats.
- Investigators can create specific rules for data formatting(normalization), ensuring consistency and accuracy.
- Assures total accuracy in data capture, including the ability to read handwritten checks. It also includes a zoom-in feature for deciphering challenging handwriting.
2. Automated Audit Trail
Fraud investigators face a tremendous challenge in creating an accurate and detailed audit trail for financial documents and data in transactions. The lack of a thorough audit trail mandates time-consuming efforts to trace data origins, validate information accuracy, and assure accountability for every step done in an investigation.
ScanWriter tackles this issue with a smoothly integrated audit trail tool within Excel files. It precisely monitors and documents all financial document operations and transactions. It keeps a chronological log of what was done, when it happened, and by whom. This thorough record adds an important element of transparency and accountability, easing the review and verification processes.
The integration of ScanWriter with Excel provides a thorough audit trail, allowing investigators to discover relevant PDFs easily — streamlining the investigation process.
3. Automated Data Visualization
Navigating the complexities of transactional fraud investigation requires more than just data collection; it demands an insightful interpretation of that data. ScanWriter, in its partnership with Microsoft Power BI, has elevated this process through its advanced data visualization capabilities.
This state-of-the-art feature set goes beyond mere graphical representation. It brings data to life, transforming raw numbers into a vivid, interactive tapestry of financial interactions. The suite includes meticulously designed models such as “All Transactions,” “Flow of Funds,” “Benford’s Law,” and “Suspicious Activity Report (SAR) Analysis,” each tailored to unveil different aspects of transactional data.
For example, the ‘Flow of Funds’ model is a testament to the software’s analytical prowess. It doesn’t just show transactions; it narrates the story of money as it travels across accounts and borders. This model illustrates the intricate web of financial transfers, detailing where funds originate, their journey, and ultimate destinations, along with the profiles of involved entities.
Accounts are represented as nodes, each with distinct graphical identifiers, while unidentified entities — often crucial in fraud detection — are marked with a question mark, prompting further investigation.
The brilliance of ScanWriter lies in its automation capabilities. It effortlessly converts complex datasets into the ‘Flow of Funds’ visualization, enabling investigators to trace financial trails, apply diverse filters for deeper analysis, and identify irregularities with unprecedented ease and accuracy. By marrying the technological sophistication of Microsoft Power BI with intuitive design, ScanWriter turns data visualization into a powerful ally in the fight against transactional fraud.
4. Asset Tracing
Recovering funds from financial scams, sophisticated embezzlement, or major crimes such as human trafficking relies on investigative efforts to locate hidden assets. These assets are frequently concealed by sophisticated fund transfers involving many individuals and fake corporations across multiple jurisdictions throughout the world.
ScanWriter provides an asset-tracing tool to help investigators follow the money trails, uncovering the full extent of the fraud and recovery of stolen funds.
The asset tracing tool from ScanWriter streamlines investigations by collecting important information and allowing exact data filtering based on names and transaction descriptions. This user-friendly tool enables investigators to quickly focus on specified criteria, removing small transactions and highlighting significant money moves in a streamlined flowchart.
With each transaction given a unique name and number, investigators can easily cross-reference spreadsheets, enabling instant access to evidence as they follow and connect the movement of assets to criminal actions.
You can refer to this video to learn more about how investigators can use advanced technology to trace assets in financial investigations.
5. Team Collaboration with Case Management Capabilities
While investigating transactional frauds, handling extensive paperwork and data provides difficulty for fraud investigators, resulting in inefficiencies in information retrieval, hampered team communication, and challenges in proper case tracking.
ScanWriter’s integrated case management system provides a valuable set of features that help streamline the investigation process by:
- Automated Document Sorting and Categorization: ScanWriter automates manual processes such as sorting and categorizing documents based on type, owner, and status. Investigators can personalize categories, ensuring simple access to critical information and saving time on administrative procedures.
- Seamless File and Data Sharing: To address the collaborative nature of complex fraud investigations, ScanWriter supports the smooth sharing of files and data among investigators. This collaboration solution centralizes communication, allowing for the quick exchange of case-related papers, comments, and changes among team members.
- Visual Representation of Inquiry Progress: ScanWriter includes a visual representation tool in the form of a bar graph to simplify the monitoring of inquiry progress. This feature provides information about the status of papers at various stages, ensuring that no crucial elements are overlooked and that deadlines are met.
By enabling teams to work efficiently and effectively in detecting fraudulent actions, ScanWriter stands out as an excellent tool for overcoming the challenges associated with investigating transactional fraud.
Watch this video to learn how ScanWriter’s case management tools improve the efficiency of fraud investigations for investigators.
6. Trusted by Government Agencies Across the USA
ScanWriter has earned the trust of federal and state government agencies across the United States as the go-to solution for automated data entry and visualizations during financial investigations.
Its robust features make it a preferred choice for government use:
- Security Assurance: ScanWriter stands out for its high level of security, which aligns with the severe security needs of government agencies. Its on-premise deployment adds an extra degree of privacy and protection, distinguishing it from cloud-based options.
- Compliance Commitment: ScanWriter goes above and beyond to ensure compliance with numerous government regulations, including HIPAA, FERPA, and ITAR. This commitment to meeting regulatory standards makes it a dependable alternative for agencies with strict compliance needs.
- Strategic Locations: The ScanWriter team operates from offices in the United States, one in Fountain Valley and one in Washington, DC. This geographic presence demonstrates their dedication to offering personalized support and solutions to government agencies across the country.
Undertaking the task of investigating transaction fraud is both extensive and laborious. To avoid complicating this already challenging process, it’s crucial to use secure and strategically effective advanced tools. Choosing ScanWriter for your transaction fraud investigations could significantly transform your approach. It offers a user-friendly interface and top-tier customer support, enhancing your investigative efficiency.
Furthermore, ScanWriter’s reliability is evidenced by its widespread use among government agencies across the USA and its commendable 4.4 out of 5 rating on Capterra.
Rather than just taking our word for it, we invite you to explore the case study demonstrating how ScanWriter’s analytics played a pivotal role in investigating and resolving an embezzlement case.
If you’re prepared to harness the capabilities of ScanWriter to streamline your investigation process, we encourage you to request a demo and experience its benefits firsthand.
1. What is a Transaction Fraud?
Transaction fraud is defined as any fraudulent conduct intended to get money, products, or services during a financial transaction. It entails methods or tactics that deceive or harm others for personal benefit. Transaction fraud can occur in a variety of scenarios, including online transactions, credit card purchases, banking transactions, investment scams, and others.
2. What are types of Transaction Fraud?
There are various types of transaction fraud, including phishing, account takeover, identity theft, credit card fraud, refund fraud, online payment fraud, check fraud, and Wire fraud.
3. How do Banks Conduct Transaction Fraud Investigations?
Banks usually begin transaction fraud investigations by delving into transaction data and evaluating variables such as time stamps, location details, and IP addresses to determine the cardholder’s involvement in the transaction. When cardholders report merchant-related fraud, banks may request extra information, advising merchants to keep detailed purchase records and be on the lookout for such queries. Providing a suitable response might assist merchants in avoiding friendly fraud chargebacks.
Ideally, bank investigators are trained to detect instances of friendly fraud, whether intentional or unintentional, such as customers allowing a free trial to transition into a paid billing period, unsupervised in-app purchases by children, forgotten recurring subscription charges, or cases of buyer’s remorse. However, merchants are frequently confronted with difficulties since friendly fraud chargebacks persist, necessitating the presentation of compelling proof against these claims.
When banks are confident that fraud happened and believe that the situation is serious, they may alert law enforcement agencies such as the FBI. The decision to begin an inquiry is ultimately made by the law enforcement agency concerned.
You can refer to this blog to understand how banks conduct check fraud schemes and why they prefer ScanWriter for automated check image processing
4. How can Automation Help Investigate Transaction Fraud?
Automation speeds up transaction fraud investigations by rapidly analyzing large datasets, finding irregularities in real time, and triggering warnings. It improves pattern recognition efficiency, reduces response times, and enables rapid verification of customer information.
Through constant learning and modification, automated systems help to proactive fraud prevention and allow financial institutions to remain ahead of developing fraud strategies.
5. How do you analyze credit card fraud?
Credit card fraud detection is the practice of detecting and blocking fraudulent transactions before they cause financial harm. This entails employing complex algorithms and machine learning approaches to examine transaction data in real time and find patterns that may suggest fraudulent behavior.