Big Four Consulting Firm Leverages NLP for Efficient Auditing with Snorkel Flow

A globally renowned consulting firm, with a history spanning over a century, was seeking to enhance its auditing capabilities by leveraging artificial intelligence. The firm's reputation hinged on its ability to conduct thorough audits, irrespective of their size, complexity, or location. The firm's experts were spending significant time manually reviewing various accounting, auditing, and industry information, a process that was both time-consuming and costly. The firm estimated that each auditor search lasted 10 minutes and cost $50-60 on average. The firm's data science team was tasked with streamlining news monitoring to anticipate changes in capital markets, regulatory trends, or technological innovation. They aimed to use custom NLP models to automatically analyze, categorize, and extract key client information from various sources. However, they faced challenges in labeling training data for the machine learning algorithms. It took three experts a week to label 500 training data points, and they found it nearly impossible to adapt to changes in data or business goals on the fly.

The customer is a global consulting firm, part of the 'big four', with a history of over 170 years. The firm has built its reputation on rigorous analysis and the ability to anticipate change. It strives to provide its diverse team of experts with the most current and relevant accounting, auditing, and industry information. The firm has over 300,000 experts spread across 150 countries who spend hours each day manually reviewing various accounting, auditing, and industry information. The firm's data science team was tasked with leveraging AI/ML to reduce this costly effort and to innovate by helping to identify which of their clients are most likely to be audited.