ML and Legal Analytics: A Computational Approach to Case Outcome Prediction in Legal Management

The legal industry has undergone a transformation through the combination of machine learning and artificial intelligence techniques. This work focuses the application of such approaches in legal management and also explores how these techniques are useful in various aspects of legal service. With this work, there is an analysis done using case studies from leading organisations such as Lex Machina, JP Morgan, Deloitte, IBM Watson, All State insurance and others. We show that the potential of machine learning is useful in improving the efficiency and decision making in these processes applied to critical legal domains such as contract intelligence, IPR analysis, litigation risk assessment and other our work. The potential of ML to combine with traditional legal practices offer a lot of advantages in the field of data analytics, and pattern recognition.

Authors

Publication Details

Journal
Communications on Applied Nonlinear Analysis
Published
2024-12-23
DOI
https://doi.org/10.52783/cana.v32.2945
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ML and Legal Analytics: A Computational Approach to Case Outcome Prediction in Legal Management

Bhanu Pratap Singh
Communications on Applied Nonlinear Analysis
Artificial Intelligence in Law
article

ML and Legal Analytics: A Computational Approach to Case Outcome Prediction in Legal Management

Bhanu Pratap Singh
article en

Abstract

The legal industry has undergone a transformation through the combination of machine learning and artificial intelligence techniques. This work focuses the application of such approaches in legal management and also explores how these techniques are useful in various aspects of legal service. With this work, there is an analysis done using case studies from leading organisations such as Lex Machina, JP Morgan, Deloitte, IBM Watson, All State insurance and others. We show that the potential of machine learning is useful in improving the efficiency and decision making in these processes applied to critical legal domains such as contract intelligence, IPR analysis, litigation risk assessment and other our work. The potential of ML to combine with traditional legal practices offer a lot of advantages in the field of data analytics, and pattern recognition.

Communications on Applied Nonlinear AnalysisVol. 32(5s)
Openalex Percentile: Top 56%
Artificial Intelligence in Law
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ML and Legal Analytics: A Computational Approach to Case Outcome Prediction in Legal Management — Bhanu Pratap Singh · Communications on Applied Nonlinear Analysis (2024) | TGRS Research Map | TGRS