Economic and financial analysis based upon large-scale datasets is a core requirement in complex litigation. Brattle has the infrastructure and expertise that enables us to get these datasets up and running on high performance big-data platforms. We provide data services for clients, testifying experts, courts, and regulators in connection with litigation matters and complex commercial disputes. The breadth and depth of our experience enables us to offer exceptional data processing and analytics capabilities.
Big data may exceed or strain the memory and hard disk capacity of traditional computing platforms, requiring more advanced techniques for storing, manipulating, visualizing, and summarizing such large datasets. Even if the data can fit within the capacity limits of a traditional computing platform, the processing time needed to perform analysis may limit the scope of feasible analysis and the productivity of experts. Using a specialized big data platform, such as a Hadoop cluster, makes complex analysis of large datasets feasible, timely, and more efficient.
We have experience deploying our own Hadoop clusters and other terabyte-scale data storage solutions, and working with third party hosting companies to provide secure remote access. The programming languages we most commonly use in conjunction with the Hadoop platform are Python, R, SQL, and Pig. We use these languages to transform, extract, and sample low-level transactional data to produce datasets more suitable for traditional analysis tools such as Excel or Stata. Our expertise and experience in deploying Hadoop clusters provides Brattle with a competitive advantage in extracting from raw data the economic insights of critical importance to each case.
Datasets often requiring “Big Data” tools
- Bid/offer and executed trade records for stock market, foreign exchange, commodity, and other financial markets
- Payment card transaction records
- Mortgage-backed security due diligence and performance records
- Airline and air cargo industry records
- Railroad freight system cargo manifests
- Pharmaceutical and healthcare records
- Auto parts inventory and sale records
- Life insurance policy and claim records
- Pension and annuities recordkeeping
- Hedge fund, bond fund, and mutual fund portfolio and trading analysis
- Geographic tracking of customers, product shipments
- Retail point-of-sale scanner data
In investigations with document-intensive discovery, Brattle experts work to assist clients with document analytics to target the most valuable documents quickly and to deliver answers to key questions. Our approach is rooted in our substantive expertise in data analytics, which draw on the latest techniques from data science, such as predictive coding, topic modeling, and email network mapping. We coordinate closely with investigative and trial teams, and our approach is customized to each case. Our hallmark is a clear, detailed work product that is targeted to our client’s focus and dovetailed with the key aspects of the case.
A challenge in high-stakes financial investigations, such as money laundering cases, fraud, and white-collar crime, is identifying questionable transactions and information flows within large volumes of ordinary, but typically fragmented, financial and email records with limited time and resources. We apply “big data” techniques in financial investigations to identify patterns and linkages potentially indicative of illicit activities that would be hidden or difficult to detect with traditional methods.
We add analytic capabilities to litigation and investigative teams, making it possible to extract more information from the available documents and metadata, and to do so more efficiently. Extracting data using algorithms from across multiple documents, native files, or routine corporate reports can provide key empirical support for important findings not otherwise evident from individual documents. We bridge the technology gap that can separate useful lines of investigation and the technology platforms available to access documents, as well as the challenges posed by large-scale cases. We do this by writing custom algorithms with the flexibility to analyze information in ways best suited to the specifics of the case rather than constrained by the off-the-shelf analytic tools available to the investigative teams.
Making the Most of Document Analytics
December 1, 2015
Published in Law360
Big Data’s Big Impact In Financial Investigations
May 28, 2015
Published on Law360
How to Excel in Complex Cases Involving a Large Number of Documents and Multiple Experts
Presented at the SEAK 22nd Annual National Expert Witness Conference