At a basic level, eDiscovery describes the process of discovery, updated to address the challenges and complications of collecting, reviewing, and producing evidence in the modern, digital world.
Electronic information is usually accompanied by metadata that is not found in paper documents and that can play an important part as evidence (e.g. the date and time a document was written). The preservation of metadata from electronic documents creates special challenges to prevent spoliation.
What are the three types of discovery?
That disclosure is accomplished through a methodical process called “discovery.”
Discovery takes three basic forms:
written discovery
document production
depositions
Stages of process of eDiscovery
Identification
Processing
Preservation
Review
Collection
Production
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Three important issues
that decision makers should consider
- eDiscovery is an important issue and is becoming more serious over time, but most corporate decision makers believe they are not as well prepared for it as they should be.
- Most organizations have at least partially addressed eDiscovery issues focused on email, but a growing number of data types and venues are complicating the problems of eDiscovery and content management in general.
- eDiscovery rules and requirements continue to evolve and are placing additional demands on decision makers to manage eDiscovery properly.
When choosing the best eDiscovery platform for institutions,
look for these five benefits
Prioritized review with continuous machine learning
Gone are the days when legal teams would review all documents one by one to respond to a regulatory demand, litigation request, or conduct an internal investigation. Instead, modern legal professionals leverage machine learning and AI technology known as predictive coding to prioritize the identification of relevant documents buried in mountains of big data. Predictive coding with continuous machine learning utilizes human coding decisions (i.e., relevant / not relevant) to actively learn the kinds of document and language patterns that the lawyers are looking for.
Applying predictive coding saves time and money, helps identify the most relevant documents earlier and lowers costs by reviewing far less irrelevant data. After just a few example documents, the AI can begin searching for similar content and identifying documents for human review. Throughout the review process, the system continuously learns more about what is relevant and adjusts its suggested documents for review accordingly, with most likely relevant documents at the top of the queue. Plus, the machine learning model doubles as a quality control, and at the end of a project it can be used to verify human review decisions, analyze related data sets, and correct errors before production.
Applying predictive coding saves time and money, helps identify the most relevant documents earlier and lowers costs by reviewing far less irrelevant data. After just a few example documents, the AI can begin searching for similar content and identifying documents for human review. Throughout the review process, the system continuously learns more about what is relevant and adjusts its suggested documents for review accordingly, with most likely relevant documents at the top of the queue. Plus, the machine learning model doubles as a quality control, and at the end of a project it can be used to verify human review decisions, analyze related data sets, and correct errors before production.
Automated pattern detection and redaction
In the financial services sector, firms deal with exorbitant amounts of sensitive and private data and thereby must comply with customer data privacy regulations. Many documents contain Personally Identifiable Information (PII) like social security numbers, street addresses, phone numbers, and email addresses. In addition, financial enterprises must comply with a host of specialized financial privacy regulations necessitating the redaction of Payment Card Information (PCI) like credit card and account numbers. Having the proper automated pattern detection and redaction tools integrated with eDiscovery software helps prevent inadvertent disclosure of PII that could lead to costly sanctions.
Basic eDiscovery technology anticipates manual redaction of documents, whereas the best eDiscovery software is able to recognize patterns and redact sensitive information automatically. For instance, information found in banking statements, financial records, and mortgages documents tend to follow a regular expression pattern. eDiscovery software can detect and filter on those patterns and then redact the references directly- automatically redacting PII, PHI, and PCI across thousands of documents at a time.
Basic eDiscovery technology anticipates manual redaction of documents, whereas the best eDiscovery software is able to recognize patterns and redact sensitive information automatically. For instance, information found in banking statements, financial records, and mortgages documents tend to follow a regular expression pattern. eDiscovery software can detect and filter on those patterns and then redact the references directly- automatically redacting PII, PHI, and PCI across thousands of documents at a time.
Flexibility and scalability
Firms handle cases varying in size and scope; smaller cases may contain tens of thousands of documents while larger projects hold terabytes of data. The best eDiscovery software will offer the ability to scale up securely and flexibly to meet a project’s growing needs or archive when a project slows down or ends. Flexible deployment models in the cloud or on-premise offer the right mix of scale and security. Some clients prefer a hybrid configuration, conducting early case assessment (ECA) on-premise behind their own firewall to cull the data for review and then hosting that data in a managed cloud environment accessible by outside counsel and monitored by corporate legal operations.
Additionally, taking eDiscovery in-house enables internal teams to investigate whenever they want to—moving data in and out of the review platform as desired. The best eDiscovery solution for services will enable self-service collection, processing, and case creation so that lawyers can rapidly investigate a matter at a moment’s notice.
Additionally, taking eDiscovery in-house enables internal teams to investigate whenever they want to—moving data in and out of the review platform as desired. The best eDiscovery solution for services will enable self-service collection, processing, and case creation so that lawyers can rapidly investigate a matter at a moment’s notice.
Integrate with existing systems for standardized, defensible workflows
Unifying eDiscovery with enterprise information management is more relevant than ever, particularly for financial services firms with a multitude of enterprise content management systems (ECM). Integration enables eDiscovery systems to crawl, index, search, and collect the data where it lives. Internal employees can search across all the key data repositories simultaneously using the same, standardized set of keywords and metadata filters.
Integrations further allow for development of standardized workflows and processes by leveraging internal knowledge and expertise. Over time, IT or technical personnel will be invaluable in helping develop standardized eDiscovery policies on data mapping, collection, record management, storage and retention. Having well-established policies enables the creation of repeatable and defensible processes. With an integrated system, the internal investigations team need not rely on IT personnel for each legal matter and can focus instead on building subject-matter expertise.
Integrations further allow for development of standardized workflows and processes by leveraging internal knowledge and expertise. Over time, IT or technical personnel will be invaluable in helping develop standardized eDiscovery policies on data mapping, collection, record management, storage and retention. Having well-established policies enables the creation of repeatable and defensible processes. With an integrated system, the internal investigations team need not rely on IT personnel for each legal matter and can focus instead on building subject-matter expertise.
Meet Compliance and regulatory obligations around the world
Such compliance may require the fast analysis of a wide range of communication data, ranging from text messages to social media messages to emails. Delivering such a quick turnaround on communication data requests is only feasible by utilizing sophisticated eDiscovery solutions.
In addition, the best eDiscovery software enables an enterprise-wide view of eDiscovery projects via a central platform for all discovery activities. Overlapping projects can be identified and documents relevant in one jurisdiction can be set aside for use in another. This is particularly valuable for financial service firms in that a production to one financial regulator often begets a similar production to another regulator.
In addition, the best eDiscovery software enables an enterprise-wide view of eDiscovery projects via a central platform for all discovery activities. Overlapping projects can be identified and documents relevant in one jurisdiction can be set aside for use in another. This is particularly valuable for financial service firms in that a production to one financial regulator often begets a similar production to another regulator.