In the second episode of A&M Disputes and Investigations Asia ‘The Lighthouse’ podcast, Eden Chen, Jay Kim and Matt Lan in A&M’s Forensic Technology Asia practice discuss the increased prevalence of short message chat data and how they developed ChatView, A&M’s unique proprietary solution that makes chat data easy to search, analyse and review.

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To learn more about ChatView, click here.

Transcript

Matt: Hello everyone, and welcome to the second episode of ‘The Lighthouse’ podcast. Following on from our previous podcast on short seller reports, we are here to discuss short message data from chat platforms such as WeChat and WhatsApp in an investigation. My name is Matt Lan, I’m a Director in the Forensic Technology practice in Asia. I’m joined today by Eden Chen and Jay Kim who are Senior Director and Director in the same practice. 

In the past five years, we have seen constant growth in the short message format, from established platforms such as WeChat growing from 700 million users in 2015 to over 1.2 billion users in 2020 to the emergence of Slack and Teams as alternate corporate communication platforms beyond emails. 
 
The usage of these platforms further exploded upon the onset of the pandemic with many shifting to working from home. The number of users on Microsoft Teams have grown more than six times from the end of 2019 to 2020. With the new means of communication comes additional complexity for legal teams, compliance teams and IT teams. 

Eden – How has this impacted our clients and their ability to collect and review this data for investigations, litigation, or regulatory response? 

Eden: Thanks Matt. In the past five years, we have seen an increase in relevant communications contained in chat data. Specifically, in the past 12-18 months, nearly every engagement we worked on had a short message component that was highly sensitive and relevant. These platforms range from WeChat, DingTalk, WhatsApp and Microsoft Teams to various other applications, as employees and companies work from home more often.

In some instances, official corporate communication and business decisions were conducted on personal devices with personal accounts. We normally require consent from custodians, which further complicates the client’s ability to access and collect these types of data.

Matt: So, what are some of the challenges that our clients face in forensic collections due to the shift toward remote work with mobile chat and other collaboration platforms? 

Eden: The past year has provided some interesting challenges in collection. With our own team sometimes working from home or remotely, access to clients’ physical offices are restricted. Therefore, we have adjusted our data collection approaches accordingly.

In the Chinese mainland and Hong Kong, WeChat collection remains highly relevant in most of our cases. A&M has a unique methodology that allows us to not only remotely collect data from custodians, but also meet their privacy concerns and requirements.

Other emerging trends that we have observed are around the use of applications such as Signal and Telegram, whose functions include disappearing messages. Although the technology used for communication is constantly changing, we continue to stay current and adapt to these changing landscapes.

Matt: Great. And does the new data that we are able to collect present additional challenges for the investigation and legal team?

Eden: One of the challenges is that while we might be able to collect short message data from mobile phones and other platforms, the data is often in raw format – meaning only text messages are reviewable. This often involved messy database structures, which is not particularly useful for lawyers or investigators to review. Previously, we did not get an output that looks like what it would be on a phone. This is why we decided to create a solution that provides a short message output that looks and feels easier to read and review. We call this ChatView. I’ll now hand it over to Jay, whose specialty is data analytics, to explain a bit more. 

Jay: Thanks Eden. ChatView is a toolset that takes raw chat data that has been collected from mobile devices which is able to reproduce an output that looks very similar to what it would like look like within a chat application on a mobile phone. The results can then be exported into PDF or other required formats. We have reverse engineered the chat data to make it much more reader friendly, as it might look like within a chat program. What you will see is a layout with the actual chat bubbles, and next to them you will have profile pictures identifying the users. This will provide a rich view that reproduces key features from chat programs like emojis, video, audio, and various third-party apps. This provides a more visually and media-rich view that makes document review much more palatable. Eden, could you elaborate on the support we have for WeChat’s other features?

Eden: Sure. For users who are not familiar with WeChat, it includes built-in features like WeChat Pay. For example, if we use WeChat Pay to transfer money or send a red packet, the notification can be displayed within the conversation which might be important to an investigation. In addition, WeChat has a rich third-party application environment called mini programs. Some of that content can also be shared and displayed within the rendered ChatView results for review.

Jay: Thanks Eden. So ChatView can support many of these features and give a reviewer or an investigator a more complete perspective of what the sender or receiver of messages would have seen. For our listeners, you can take a look at what the output looks like here.

Matt: What chat programs are currently supported? 

Jay: Currently it’s WeChat, WhatsApp, DingTalk, and Bloomberg. But if you have raw data collected from any chat application, we can customise ChatView to support that application. 

Matt: That sounds great. For the benefit of our listeners, once all data has been processed using ChatView, how does it integrate with Review Platforms such as Relativity? 

Eden: As a leading E-Discovery platform, Relativity can support traditional document types like email and electronic files very smoothly. However, reviewing chat documents is a different story. By using ChatView within Relativity, users will be able to see the chat output and within the same view they can easily navigate to play various rich format attachments like audio and video files within Relativity. It’s also easy to scroll through and switch between the chat messages and attachments during the review. That’s how we enhance the reviewer’s performance while making the review readable and smooth. 

Matt: That’s great. No doubt our clients appreciate the easy to review output. Are there any other challenges from this point Eden? 

Eden: The last major challenge we encountered at this point is the number of messages that can be sent between custodians. We had instances where a collected conversation from WeChat contained chat history of over 2 years. This presented a huge burden on the reviewer to identify, review, redact and produce any relevant content. At that point, we leveraged Jay and his team again to come up with a solution. Jay, would you like to talk a little bit more about how we addressed this challenge?

Jay: We leveraged our in-house data processing team and used automation tools to split up the large of amounts of chat data into individual chats, such as by individual or by day, week or by a custom timeframe. This provided more targeted information for reviewers. So rather than getting keyword hits on a year’s worth of chat data within, say, one PDF or Excel file—which is not very useful, we will provide more targeted results that our clients can review more easily. 

Matt: Just to add, it can also improve the use of advanced analytics to provide further insight into a large volume of chat data. Eden, any final thoughts or future predictions on where we are headed and what we’ll likely see? 

Eden: I think we are only starting to see the shift in how we work and communicate with each other. Our clients have certainly appreciated what we have been able to produce with ChatView and have indicated this is a game changer when compared with reviewing chat data in Excel tables. In the next two years, the growth of email usage will be greatly outpaced by these platforms. Smaller companies in less regulated industries may look to use these platforms as their primary method of engagement with their clients. Therefore, introducing additional information governance will ultimately lead to challenges when an investigation or litigation comes knocking.

Matt: Thanks Eden. Thank you both for taking the time today to explore the forensic technology landscape around chat data and thank you all for listening to this podcast episode of ‘The Lighthouse’. For more information from Alvarez and Marsal, and to stay up to date with all our insights and advice, subscribe to our Lighthouse newsletter here. I’m Matt Lan, and until next time, take care.

More From The Lighthouse Podcast Series:

The Lighthouse Podcast: Episode 1 - Short Seller Reports