Still searching vast communication archives simply using keywords?
For the legal and financial businesses that have always depended upon quick and definitive discovery, it has been an essential, albeit imperfect technology.
However, increased complexity of unified communication channels; nuanced language and tone; and a relentless growth in the sheer volume of voice calls, emails and messages have all helped to render keyword searching as outdated and flawed.
Indeed, it’s easy to see why e-discovery classification – a game-changing method of data search and capture – is fast-becoming an essential technological tool.
It enables faster, richer, more pertinent searching that not only saves valuable time when responding to a complaint or building a client’s case, but also improves the quality of captured communications.
No more reams of irrelevant, superfluous results – just a sharp, AI-powered focus on the words, sentences, and meanings that really matter.
The benefits are there in abundance – all organisations and their technology partners must do is seek out a provider with a solution that delivers.
“Organisations generate far too much communication data now for it to be effectively searched using keywords or for it to be reviewed manually – that’s why technology must be leveraged as much as possible,” says Chris Stapenhurst, Senior Principal Product Manager at leading data management and protection experts Veritas, all of whose discovery, surveillance, and file analysis products come with a free, in-built e-classification micro-service as standard.
“There’s more to it than just time saving, too. When looking for communications associated with a particular event or issue, it’s impossible to think of all the different words and phrases someone might have used.
By leveraging an AI-powered model-based approach, searching goes way beyond just keywords. It maximises recall of items that are truly relevant, and minimises the unwanted noise.”
The key to the Veritas solution is that it proactively and automatically classifies all communications as they enter an archive. It attaches a metadata tag based on a limitless number of classifications that are either baked-in to the product or customized by the user organization. Examples of classifications include attorney-client privilege, credit card information, money laundering, bribery, criminal history, medical record information, ransomware, offensive terms, and hundreds of others.
In addition, superfluous ‘junk’ communications are automatically tagged, such as out of office email responses, subscription marketing messages, ‘all-hands’ employee bulletins, and daily newsletters.
“There is huge value in classifying data the moment it enters a system because it will help downstream when searches or reviews are required,” says Stapenhurst.
“Often, paralegals or even lawyers must manually review searched information when working on a complaint or a case, and that can be a time-consuming and expensive process. By minimising the amount of junk or irrelevant material, that time and those costs are reduced.
“Also, critical communications that may have remained unfound if they had not been classified according to particular preferences, policies and patterns can have a significant impact on a case. Users can customise their own classifications as well as leverage more than 300 policies and 1,000 patterns that currently exist in our system and which are growing in number and sophistication all of the time. For example, we just released ‘market abuse’ and ‘secrecy’ classifications, and we are currently working on ‘gifts and entertainment’. The functionality is present in all of our discovery, surveillance, and analysis products, whether on-prem or cloud-based, and can be turned on or off free-of-charge.”
There are other uses cases too.
AI and Natural Language Understanding can identify positive or negative sentiment within a communication, and organise omnichannel communications into separate buckets based on language, such as English, French, Spanish etc.
However, although genuinely game-changing, it is new technology that is not yet being adopted at pace.
The legal and financial sectors – where the value of e-discovery classification is arguably most-felt – are often conservative and slow to embrace change.
“It’s often hard to shift mindsets around the adoption of new technologies but, in the case of e-discovery classification, there is a huge opportunity for our Managed Service Provider partners to add value to a customer relationship by doing just that,” says Stapenhurst.
“End user organizations need to be shown the benefits and they need to understand that the functionality is already in our solutions and can be deployed for free. If those organizations are not leveraging this technology, they risk falling behind.
“A perfect time for an organization to classify its data is at the point of migrating its archive from on-premise to the cloud. However, the best time to classify is today. Every day spent not doing so is a wasted opportunity to work smarter, better and more efficiently.”
To learn more about how Veritas can help your and your customers’ businesses protect and manage data more effectively, click here.
