May 23, 2022
By Victor Diloreto, CEO Blackmarker
At Blackmarker, the name of which is intended to convey how redaction has been done for decades, manually, and literally with a black marker, we set out to introduce AI/ML to the task of redaction compliance, and in a sense provide a new age black marker. Using artificial intelligence/machine learning (AI/ML) to automate redaction compliance dramatically increases the accuracy of redaction compliance and reduces expenses. The AI models target information within documents that are required for redaction when submitted to the courts. The information can include personal identifiable information, like names and social security numbers, but can also include loan numbers, stamps, and bar codes that could be traced back to an individual. As you can see from the graphic below, the introduction of AI/ML to redaction compliance can dramatically improve time/labor and accuracy.
We have seen how AI/ML solutions can impact law firms specializing in foreclosure & bankruptcy case preparation, and from this we have derived some best practices. This article highlights the benefits of automation and reveals how to realize the full potential of automated redaction compliance.
WORKFLOW / PROCESS CHALLENGES
Introducing this technology to an enterprise, and the process automation it provides, could require a re-think of the roles and responsibilities of those tasked with redaction compliance. It is like the scene in Hidden Figures, when Dorothy Vaughn (played by Octavia Spencer), sees the new IBM mainframe for the first time, and realizes that the current processes for factoring are going to change, and adaptation will be necessary. She picks up a Fortran computer programming book, as she quickly realizes that knowing how to run the machine is a better route than ignoring (or fighting) it.
BENEFITS OF ACCURATE REDACTION COMPLIANCE AUTOMATION
By creating a highly accurate and automated redaction compliance capability in software, an enterprise can relegate the function to a batch, or centralized process. A defining characteristic of batch processing is a lack of human intervention, with few, if any, manual processes.
This was a goal we sought for Blackmarker - offloading redaction to a machine, saving money and time.
“We piloted Blackmarker to test the claim and were pleasantly surprised to find the performance and accuracy of the service translates to an 80-90% labor cost savings." - Mike Zevitz, Managing Attorney of South Law, P.C.
Saving time and money will always be a worthwhile goal, but there is an additional benefit in that automated redaction compliance makes an enterprise more compliant. In sampling public court records, we found a 25% error rate for documents prepared manually. Our automated process now approaches a 0% error rate.
This is where the Dorothy Vaughn effect is applied, as an AI/ML-based system must be trained. In the context of redaction, this means having the ability to mark documents, typically PDFs, by experienced people aware of the compliance rules/policies of the enterprise. In other words, the system must be “programmed” – not with rules but with examples. This does not require someone to learn Fortran -- or any other software programming language -- but to work within the system to mark the information for compliance against a finite sample of documents for the AI/ML to learn what targets are required. Targets in this context can be personal identifiable information, personal health information, or other sensitive information as defined by the policy being followed. Once that finite sample of documents is marked, and the performance of the system on new documents is at a level that is equal to, or exceeds that of an experienced human, the system can process similar documents unattended. It should be noted that AI/ML systems, like Blackmarker, maintain multiple models which are pre-trained for certain types of personal information specific to the foreclosure/bankruptcy field.
Another benefit of automating redaction compliance is that while the number of people involved in physical redaction is reduced, the smaller team tasked with training or “programming” the machine reduces the chance of misinterpreting the policies, which can lead to compliance escapes. In the end, the system has fewer moving parts, which translates to fewer mistakes.
Lastly, in our current times, we have seen a lot of churn in the job markets, induced by the pandemic and the other factors it brought on – remote work, tighter job markets, etc. Introducing this type of automation removes a task that nobody, by survey, liked in the first place. Thus, enterprises can market higher satisfaction roles to the job marketplace with a better chance of landing long-term employees.
DISTRIBUTED VERSUS CENTRALIZED REDACTION COMPLIANCE WORKFLOWS
Organizationally, we see workflows that have a compliance redaction function within them falling into one of two camps.
Redaction compliance, among other duties, is distributed to a group of individuals. Each person owns a set of cases and all the tasks required to prepare the files for case submission. The task list includes redaction compliance, and tasks like unbundling large title search documents, adding motions, adding stamps, etc. The various steps are executed serially, one after the other, by each person, case by case.
In the other setup, certain parts of case preparation, like redaction compliance, are carried out by a single group. They redact the files to be used by others for case preparation.
OPTIMAL WORKFLOWS USING AI / ML
Given AI/ML’s automation power, it naturally facilitates the ability to batch process, which creates the greatest efficiency. A centralized workflow more closely aligns with batch processing; thus, it is the recommended type of workflow when using AI/ML. In this fashion files can be presented to the AI/ML system by those responsible for redaction compliance or via case tools/document management systems overnight or early mornings, and then the balance of the workforce can access the redacted files as they prepare their cases for the day/week.
The centralized role for redaction compliance sees all the benefits laid out previously in this article:
If a firm has deployed a distributed workflow for redaction compliance an operational decision can be made to move toward a centralized function for this task. Change is hard, but there are very real, tangible reasons to enact this type of change. A potential blueprint for this type of change is outlined below:
Redaction compliance has been a manual exercise for a long time, but AI/ML based solutions, like Blackmarker, offer real benefits. These benefits are best realized when the organization is prepared to adopt it. Identifying the core team to “program” the AI/ML and allowing others to benefit from the prepared documents is the best practice and is achievable regardless of how you are organized today.
FOR IMMEDIATE RELEASE
October 15, 2021, 08:40 ET
Blackmarker announces integration with CaseMax
CHARLOTTESVILLE, VIRGINIA — Blackmarker, an AI-powered redaction solution that enables scalable, affordable, and efficient compliance with ever-expanding privacy regulations, has completed an integration with CaseMax, a case management tool for improving efficiencies in default loan management. In addition, CaseMax client, SouthLaw, P.C., has adopted the use of Blackmarker within their CaseMax workflow.
“CaseMax provides a powerful and intuitive solution to overcome default loan management complexities by allowing firms to leverage their resources for greater efficiency and productivity”, said Victor Diloreto, CEO of Blackmarker. “We really saw the integration with Blackmarker as a good fit for CaseMax, as we alleviate a majority of the physical redaction work since our system has been trained on a wide array of default loan document types. These document types are held to a high standard for accuracy, so we are confident that not only will CaseMax clients see decreased operational expenses but compliance improvements as well.”
“We’re excited to offer Blackmarker’s automated redaction integration with the newest release of CaseMax,” said Sarah Holland, Business Analyst, CaseMax. “We knew that coming out of the pandemic firms would need to implement new automations to better manage already strained internal resources, but we had to ensure that the automation saved time versus adding processing time. After seeing Blackmarker in action, we knew they could help firms rebound post-moratoria with greater efficiency and enhanced productivity.”
“CaseMax asked if we were interested in adopting a new redaction integration they were considering that touted a savings of 50-70% in labor,” said Mike Zevitz, Managing Attorney of SouthLaw, P.C. “We piloted Blackmarker to test the claim and were pleasantly surprised to find the performance and accuracy of the service translates to an 80-90% labor cost savings."