eDiscovery has changed how law firms work. Verified Financial Intelligence technology will do the same for fraud investigations.
The data deluge is reshaping financial investigations. Attorneys, forensic accountants and government investigators grapple with an ever-growing tide of increasingly complex financial documents and systems. While the plethora of information can illuminate critical details, it also creates data management challenges.
Investigative teams can no longer rely on traditional financial data gathering and analysis methods. With these manual processes, our research shows professionals spend 90% of their time on painstaking reviews and data cleanup to just get to the point of being able to analyze and strategize when, instead, they should be leveraging their high-level skills and using the bulk of their time to interpret the results and formulate their narrative based on the entire financial history.
Technology exists to improve accuracy and efficiency in investigations and other financial analyses. Legal professionals can use software to eliminate sample risk and accelerate outcomes.
The shortcomings of traditional approaches
Manual processes are tedious and only allow sampling of a subset of transactions, often resulting in rushed timelines and an incomplete picture. Technology helps at each step.
- Loading and extracting data
Professionals often receive financial documents as PDFs with multiple accounts spanning months or years. These records could come from the financial institution or result from digitizing hard copies. Traditionally, someone must thoroughly review these records to divide the information into the various accounts and time periods. That person may also be responsible for manually entering data.
PDF or image editors can separate the files by account, while specialized OCR tools extract critical data points. However, users must be cognizant of the technology’s capabilities. Most OCR tools require a defined template per statement format, which necessitates significant setup, creates delays and leaves room for error. In the case of lower-quality scanned statements, these tools will simply fail.
More modern solutions use machine learning to recognize text strings without templates, allowing them to capture data from even unconventional formats. However, there is still the chance an OCR might misread something, for example, recording a “6” instead of an “8.” Legal teams should equip themselves with auto-reconciliation tools to expedite the verification process.
- Reconciliation and cleanup
Most investigative teams know the pain of manually integrating and reconciling thousands of financial transactions.
Fortunately, technology automates data reconciliation and cleaning. Software can extract period balances and dates in addition to transactions, allowing reviewers to merge data from disparate sources accurately and efficiently. This feature is particularly helpful in matching bank statement transactions to deposit slips and checks.
Specialized software can analyze data for inconsistencies, duplicates, missing information and other errors, identifying potential problems that might escape manual review. The result is a clean dataset ready in a fraction of the time.
Technology makes integration easy by creating a central repository of all financial transactions. When new data enters the database, the software reconciles it with existing information. Reviewers don’t need to manage multiple spreadsheets or manually review each new line item.
- Analysis
While analysis constitutes the most high-impact aspect of evaluation, teams struggle to devote adequate time due to tight deadlines and time-intensive data gathering and review. Automation accelerates the entire process and provides additional support to the reviewers.
AI automatically categorizes transactions — eliminating manual classification — and links related transactions across accounts and entities accurately and efficiently. Need to find specific transactions? Search and filter capabilities return the information in seconds, whereas a human might need minutes or hours. AI can identify a normalized name for the counterparty, a suggested category, addresses and phone numbers associated with a given transaction.
Example statement description: TRADER JOES # 140 SEATTLE
AI categorization:
Visualization tools deliver a comprehensive financial picture by allowing reviewers to visually track the money’s flow. A solution’s algorithm flags inconsistencies, outliers and other unusual patterns. Then, reviewers can spend their time examining those instances more granularly rather than uncovering them. The result is a more in-depth and faster analysis.
Verified Financial Intelligence solutions enable robust reporting. Teams can create customized reports with compelling, visual narratives to effectively communicate findings to executives, courtrooms, banks or other stakeholders. Software also generates a clear chain of custody for data, maintaining evidence integrity and enhancing its credibility.
Lighter workloads
Legal professionals and accountants are overburdened with administrative tasks and high caseloads, which technology alleviates. By automating tedious processes like data entry, cleaning, and transaction reconciliation, experts can work on more fulfilling and higher-value tasks, such as gathering additional information on suspicious activities, analyzing the evidence and making conclusions.
Many professionals fear that technology will take their jobs. That’s not the case — especially in complex financial matters like fraud investigations. These cases require human critical thinking and ingenuity. Algorithms can’t make conclusions or deliver comprehensive analyses to stakeholders.
By leveraging the strengths of both humans and technology, the latest financial analysis advancements bolster the quality and speed of investigation outcomes while also reducing costs.
The future of financial investigations
As the volume and complexity of financial data and fraud accelerate, the “way we’ve always done things” is unsustainable. eDiscovery has changed how law firms work. Verified Financial Intelligence technology will do the same for fraud investigations.
Skilled professionals no longer need to waste time and resources gathering limited information. They can use their expertise for specialized analysis based on the entire financial picture, not just a small sample. The future lies in a cooperative relationship between automation and human expertise, ensuring comprehensive and transparent analysis at previously unmatched speeds.
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