Let ReviewAI Handle the Pre-signature Phase
ReviewAI provides a review of any contract and automatically redlines, annotates, and provides a risk rating based on your company’s…
When it comes to legal billing, corporate legal departments often have a baseline expectation: Charge my company the correct amount.
What sounds like a simple premise (and one that should be easy to meet) comes with serious challenges. Invoice review is a rigorous process. Due to the work they represent, law firm bills are often long and complex and contain entries from numerous timekeepers. With hundreds of thousands of line items, vague descriptions or block billing may be missed by busy in-house reviewers. Violations of outside counsel guidelines, such as copy charges or work, may be hard to pinpoint. To top it off, in-house counsel and other professionals usually count invoice review as one of their many responsibilities – a list that has grown as work increases and resources remain stagnant or decrease.
Technology, such as enterprise legal management, has helped to alleviate some of the challenges. Paper invoices have moved to electronic billing. Billing rules, built to scour for specific terms in invoices, flag charges for review. Legal spend analytics identify trends and help to frame performance.
However, even with these additions, many reviewers often default to hitting approve. Who has time in the department to dig deeply into every questionable charge? Is there another approach to invoice review that will ensure companies aren’t overcharged?
We dug into these questions in a recent webinar. Jonathan Weber, Chubb’s Vice President, Claim Optimization and Legal and Operations Lead, Marci Waterman, President of Sterling Analytics (and the newest member of Onit’s strategic alliance program), and Matt DenOuden, Onit’s SVP of Global Sales, explored the ideal approach that adds efficiency and expertise to invoice review while still honoring the company’s relationship with law firms.
Potential violations during invoice review often fall into three categories.
First, you have basic facts. For example, is the math correct? As Weber illustrated in the webinar, this is along the lines of getting a bill at a restaurant that is added correctly. Does your bill for two $25 entrees show $50?
Next, you have black and white decisions. For example, is the bill consistent with litigation management guidelines? Going back to the restaurant analogy, were you charged with what you ordered? Or did charges from another table end up on your tab?
Finally, you have gray areas. Are the charges reasonable? When we return to the restaurant idea, one way this might look is being charged for food that was ordered but was served cold. Generally, in a situation like that, the restaurant will comp the meal or replace it with another at no charge. Or perhaps you have three servers working your table. For a party of two, that makes no sense. But for a party of 25, it fits perfectly.
How can corporate legal ensure they’re billed properly in each of these categories? By combining AI and human review.
Webber provided his insight on combining AI and third-party bill review. The company pays hundreds of invoices every day and has a sizeable legal spend. Meeting their goal of always being sure they’re paying the correct amount is a difficult task. They’ve defined strict processes for the flow of invoice review that allows them to look at their data in an organized way.
Part of that process is relying on AI and third-party legal billing review.
AI identifies non-compliance for things like wrong math, improper descriptions and block billing. These are the kinds of basic or black-and-white decisions that machines handle well. As a bonus, the AI continues to learn so it will get more adept each day at identifying these types of issues.
For the gray areas, the human element comes in. This is where judgment is required. Sometimes the AI might flag things for a valid reason, but humans (such as the lawyers at Sterling) can understand the context and circumstances that make certain charges acceptable or unacceptable.
The result? Chubb is better able to accomplish its goal of always paying the right amount. You can hear the entire discussion, which goes more in-depth into this topic and its benefits.
Combining AI-powered invoice review with human third-party review decreases the burden of invoice review while offering:
Here are resources for those who would like to learn more about this:
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