Forensic Data Analytics

graphical user interface

Leveraging Big Data to Create Successful Outcomes

Organizations routinely generate, capture, and store tremendous volumes of data. While this information is focused on supporting the organization's various business objectives and operating functions, it is typically not designed to support analyses related to litigation and anti-fraud efforts. We have extensive experience with requesting, aggregating, and transforming datasets ranging anywhere from millions to billions of records.

Our team of data analytics professionals work alongside B. Riley's expert witnesses and counsel to help drive successful outcomes for cases with large and/or complex datasets. At every point in the litigation life cycle, from document requests to critiques of opposing experts, our team can assist to identify useful data and transform data into usable information.

Our Services

Our team has the knowledge and experience to assist in a broad range of engagements, from class actions to financial fraud our team can help. While our capabilities can be applied to a variety of matters, some specific services include:

  • Advising clients in the interpretation of data analytics results and supporting follow-on actions (E.g., in-depth document review and in-person interviews)
  • Developing "proactive" tests to identify anomalies indicative of areas of concern, such as fraud, waste or abuse
  • Focused testing tailored to identify potentially corrupt payments in support of the company's anti-corruption efforts
  • Database Development
  • Statistical Sampling
  • Statistical Analysis
  • Timeseries Forecasting
  • Economic Modeling
  • Financial Modeling
  • Interactive Data Visualization

Engagement Experience

Some highlights of our engagement experience include:

  • Multiple business turnaround matters in industries ranging from Food and Beverage to Telecom involving analytics such as SKU rationalization and profitability analysis.

  • Multiple cases for one of the largest commercial shipping companies in the world, related to a damage dispute regarding package weights and billing charges.

  • Multiple data breach cases including one pertaining to a data breach for a healthcare billing company in which over 51 billion datapoints related to PHI and PII were leaked

  • Assisting to determine damages related to a large payment authentication company being accused of the unlawful storage and selling of user financial data without consent which involves hundreds of millions of records and tens of millions of individuals.

  • Development of various statical sampling methods including monetary unit sampling methodologies to determine damages associated with lost profits for a medical billing dispute and claim sampling for a nation health insurance provider.

  • Expert services related to sampling methodologies and algorithm development for classification of warranty replacements in a class action lawsuit related to an international retailer.

  • Breach of contract disputes for a large auto parts manufacturing company involving years of sales data from multiple sources.

  • Fraud investigation related to fake trades on treasury bonds that resulted in overexposed positions.

  • Modeling and upkeep of data related to over $1 billion worth of cumulatively purchased consumer receivables for B. Riley Financial.

  • Assisted in defense of class certification of an action against a payment card processor providing rechargeable debit cards for federal government benefits regarding allegations of inappropriately denied refunds for alleged fraudulent charges by analyses of over 23 million "service requests" regarding the subject cards and charges that B. Riley segregated to those subject to the class allegations, sampled and showed a lack of damages.

  • Rebutted damages alleged against payment card processor by merchants for certain limited unnotified, excessive and increasing charges and fees which related to $83.1 billion of card processing over 11 years which B. Riley successfully analyzed and showed were justified.