Leverage Your Data for
Better Litigation Outcomes

The need for in-house legal departments to adopt and use data analytics has never been more urgent. Leveraging data to improve settlement offers and litigation strategy results in significant savings.

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Why is Data Analytics + AI valuable for
Legal Departments?

Optimize Resources
Provides visibility and insights
Increase Visibility
Creates actionable intelligence to aid improved analytics
Increase Collaboration
Legal departments using Analytics + AI exhibit higher quality work, reduced litigation costs, and lower spending
Create Value
Data analytics helps legal departments effectively communicate to their business teams with higher levels of accuracy
Drive Legal Transformation
Predictive analytics helps lawyers make educated guesses including how long a case will take to reach a decision, or what a case may settle for at various stages of litigation
Although opportunities to automate present themselves to GCs, and the intent to implement automation is apparent, most legal departments simply do not have the staff for legal analytics. Just 1 in 5 GCs report having a technology or innovation counsel, or access to a data analyst.

LegalEase Approach

Requirements Gathering

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Data Collection and understanding key factors

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Data Cleansing

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Data Analysis

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Data Visualization

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Data Modelling

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Predictive Analytics

Key Factors

Sufficient data upon which the data model can be built & trained

Access to SMEs, to understand the process during requirements gathering, and detailed feedback after initial outputs so that the engine can be further trained (supervised learning)

Smooth access to data, environment for sandbox installation, and other technical assistance, as required

Analytics Application

  • Judge’s case history (volume, type, industries, & more) 
  • Judge’s motion analysis by type, party, & vs. average denial rates
  • Judicial rulings and briefs available by jurisdiction 
  • Law firm case history (volume, type, industries, & more) & case length analysis 
  • Motion analysis by type, party, & vs. average 
  • Litigant case history (volume, type, industries, & more) & case length analysis 
  • Litigant litigation histories
  • Case law preferred by judges
  • Language found persuasive by judges
  • How new statutes and cases are actually used by judges and parties
  • If you need to settle a matter or pursue litigation
  • An estimated settle amount
  • Success rate of your motions
  • Valuation of entities
  • Estimated cost of litigation

Get Started Today

Find out how LegalEase built a predictive analytics engine for a large OEM and helped them save over $ 2.5 Million in litigation costs!
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Problem
Solution
Result

A large global automotive OEM aims to significantly decrease legal fees and costs in California by leveraging data and predictive analytics to provide for more accurate settlement valuation and shorten the time to resolution.

LegalEase Solutions and its predictive analytics partner committed to providing a highly accurate model to the OEM within 60 days, and set off to understand the problem statement and collect all data points readily available to the legal department. Over 5 years of historical litigation data was collected and cleansed from the OEM’s matter management and billing platform. LegalEase Solutions attorneys and data scientists had several working sessions with the OEM legal and technology staff to discuss the relationship between the various data factors and potential outcomes in litigation.

Ultimately, LegalEase Solutions and its partner, built out a working model for the OEM which provided objective and consistent settlement valuation of breach of warranty cases and a predictive model which alerts the OEM to potentially problematic cases. This proof of concept was achieved in 60 days.