Learn how you can leverage meta-data, machine learning, and master-reviewers throughout the Managed Bill Review to improve your billing compliance (without the headaches!).
Legal invoices (and their review process) can be tedious, time-consuming, and downright confusing. When you are tasked with reviewing and analyzing bills from multiple outside counsel firms, each with its own billing practices and invoicing systems, it’s easy to overlook nuanced line items and make mistakes — like assuming that your matter management solution’s billing guidelines will do the heavy lifting for you.
But perfect billing compliance is often the exception, not the rule. Only 36% of legal departments say they know who or what enforces their billing guidelines. Compliance is often “assumed,” but with costly results. Legal departments rely on their matter management solution to categorize their legal bills for them, but it’s uncommon for this to produce perfect accuracy or identify key patterns, like top-performing outside counsel. Billing compliance is too complicated for matter management systems to handle without AI and human intervention, and as a result, legal bill review becomes a source of fatigue rather than efficiency.
Until Managed Bill Review (MBR), that is.
A Quick Refresher: What is Managed Bill Review?
Managed bill review services automate the legal bill review process, using advanced algorithms, artificial intelligence, and human experts to analyze bills and identify potential errors or overcharges.
Beyond capturing and helping to reduce spend, managed bill review (when done correctly) can help drive more data-driven decisions, guarantee deadlines are met, and ensure your organization complies with best practices, policies, and legal standards.
The Challenge with MBR in Matter Management
Most blue-chip matter management solutions leverage rule-based billing guidelines in-app, helping your legal professionals save time and money. But many don’t offer meta-data to categorize the kinds of line items in a legal bill, and even those that do can miss out on context that ensures each category is correct.
When you invest in a platform that leverages machine learning to review legal bills, rule-based billing gets an extra layer of automated approval. Machine learning reviews are often implemented after the rule-based billing takes place. These machine learning reviews operate more finely than rule-based billing, and by using a code-based “tag” to categorize the findings, these reviews build atomized, structured data sets in a standardized, consistent format. This kind of high-level data drives business intelligence at a new level: departments with finely grained analysis that identifies best-performing outside counsel across regions, filtering on matter types, efficiency, DEI, and more. This means that with managed bill review, you can identify the best outside counsel and run a much tighter ship. With the money you save, legal teams can reinvest into other technologies that will push the legal department further into the future.
The Secret to Successful Managed Bill Review (MBR): Talent + Technology
Machine learning is an incredible tool that revolutionizes legal bill review, but it is always useful to have a final review by a human being – preferably an expert. Even matter management platforms that offer useful meta-data can generate errors if they do not have human experts who can leverage context and facility with legal bills. With managed bill review, however, this human being does not need to come from your department.
Some MBR solutions also provide expert compliance reviewers, whose job is to oversee the minutiae that even the best machine learning technology misses. These experts are trained to find invoice “bundles” so that when outside counsel includes too many different items in one line item, you can get clarification on what exactly they are billing you for. These experts are also trained to find typos and incorrect authorizations – like billing for travel time or expenses.
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