PG&E Bankruptcy Case Study - Innovating Fee Examination for Broader Application
PG&E's Chapter 11 bankruptcy was the largest and one of the most complex utility bankruptcy cases in U.S. history. In 2018, PG&E filed its Chapter 11 petition after incurring an estimated $30 billion in liability for wildfires it caused. As with all Chapter 11 bankruptcies, professional fees payable by the PG&E estate to attorneys, accountants, financial advisors, consultants, and other court-appointed professionals had to be court-approved, in PG&E’s case by Judge Dennis Montali, under the procedures set out in Section 330 of the Bankruptcy Code (11 U.S.C. § 330). Judge Montali, however, was not the only person scrutinizing professional fees in the PG&E case. Indeed, Professor Bruce A. Markell, who was the court-appointed fee examiner, the U.S. Trustee, and other professionals/counterparties involved in the case also voiced views and objections as to the reasonableness of fees charged by PG&E’s professionals.
When evaluating the (un)reasonableness of fees under Section 330, these parties often look to the “Guidelines for Reviewing Applications for Compensation and Reimbursement of Expenses filed under 11 U.S.C. § 330 for Attorneys in Larger Chapter 11 Cases” published by the U.S. Trustees’ Office for guidance on billing standards and different types of problematic billing practices.
In today’s tech-enabled environment, parties also regularly use AI and legal spend data analytics technology to assess the reasonableness of the professional fees under scrutiny.
The Challenge
Before Legal Decoder, traditional fee examination in a large Chapter 11 bankruptcy case was labor-intensive, time-consuming, and prone to human error. Fee examiners had to manually review and analyze billing statements from attorneys, consultants, and other professionals involved in bankruptcy cases. The risk of overbilling or inaccurate fee charges posed a significant challenge given the volume of data in the PG&E case, and the time spent on fee review was likely to be enormous.
To address these challenges, Professor Markell sought a solution to support his expert fee review, realizing that a manual review would require thousands of hours of analysis and carry a significant margin for error. The challenge was compounded by the condensed time to review the initial backlog of invoices before the first fee hearing.
When evaluating technology to assist him, Professor Markell wanted not only to highlight problematic billing behaviors, but also to surface good behaviors as a training tool. Professor Markell's most important criteria were processing speed, capacity, accuracy, reliability, objectivity, and industry-wide benchmarks. He also wanted technology that was easy to use, closely aligned with the 2013 Guidelines, and offered access to industry-wide data and benchmarks. Professor Markell consulted with other fee experts who, based on Legal Decoder’s success in other large Chapter 11 bankruptcy cases, recommended that he evaluate Legal Decoder’s capabilities.
Legal Decoder’s Solution
Professor Markell shared with Legal Decoder his projections as to the volume of professional fees requiring analysis and his review timeline and approach. Each individual line item in every single invoice had to be reviewed for compliance with his standards. Legal Decoder correctly concluded that it could satisfy Professor Markell’s needs.
Professor Markell selected Legal Decoder as it met his requirements and more. Over almost 18 months, 30+ professional firms billed 800 lawyers’ and other professionals’ time for review and approval. Professor Markell’s fee examination team used the LD Compliance Decoder to analyze large sets of invoice data to meet all deadlines.
The Compliance Decoder programmatically analyzes about 25,000 invoice line items (about $15.0 million in professional fees) in under 10 minutes without human fatigue, variability, or subjectivity. An expert analysis of the same data set would have taken weeks to thoroughly review, with a high probability of human error. The Compliance Decoder has forty-seven different flags (approx. 5000 rules) which collectively cover all problematic billing behaviors and practices arising in the USTP 2013 Fee Guidelines, outside counsel billing guidelines, and industry best practices. The flags are classified into three categories (staffing efficiency, workflow efficiency, and billing hygiene).
The Result
Legal Decoder analyzed over $492 million in fees (excluding fixed fees and expenses). Legal Decoder programmatically analyzed the invoices underlying these applications and provided the Fee Examiner with analysis for approval or further review.
The results were:
Total Analyzed Amount: $492M
Total Recommended Reduction Amount: $54M
Average Reduction: 9%
Largest Reduction: 21.44%
Legal Decoder’s staffing efficiency flags highlighted an overstaffing concern for the fee examination team. One issue was firms not using staffing in local and lower-cost offices, which drove up travel costs. Through fee analysis of all activity associated with travel and local court rules, Professor Markell and the U.S. Trustee objectively communicated which fees and expenses could be authorized.
Using the Compliance Decoder’s analysis, the Fee Examiner’s team identified hundreds of occasions where multiple participants from the same firm billed for attending the same meeting, including 26 instances in which a meeting was attended by 12 or more legal professionals from the same firm. The Compliance Decoder flagged line items that were not obviously apparent to the human eye. Overall, $47M of billed work across the board was flagged as multi-staffed meetings. The Compliance Decoder analysis also helped unearth other billing issues such as inter-office communications, vague entries, and excessive time on routine tasks. LD’s unique bottom-up analysis allowed Professor Markell’s fee examination team to drill down into the data for other potential billing problems.
The greatest benefit of the Compliance Decoder analysis was providing objective information to firms and timekeepers about billing practices that did not align with billing guidelines. This opened dialogue between Professor Markell and firms while managing expectations from both sides. Firms better understood billing boundaries, and Professor Markell could better predict firms' billing behavior.
Conclusion
As large bankruptcies continue to accelerate, fees will be scrutinized for reasonableness and billing within bankruptcy guidelines. Conveying objective information about billing compliance or non-compliance can open meaningful dialogue between fee examiners, firms, creditors (secured and unsecured), and other interested parties. Using technology to analyze billing data helps ensure the reasonableness of fees. Legal Decoder’s technology has evaluated fee applications for high-profile bankruptcy cases in recent years, including Purdue Pharma, Endo Pharmaceuticals, and Toys R Us. Outside of bankruptcies, law departments and firms have also used Legal Decoder's technology for fee analysis, write-off detection, and legal pricing.