A better way of getting to the heart of the matter

18 October 2017


 E-discovery tools are reinventing the art of the possible in complex investigations, and even pointing the way towards ‘self-policing’ enterprises 

The power of e-discovery tools has grown enormously. Enabled by the breakneck pace of technological change new capabilities draw on artificial intelligence (AI), advanced analytics and big data technologies to put unprecedented power into the hands of investigators.

It’s a timely development. Although complex investigations are a feature of the business and financial world, when one strikes boards tend to panic. There is seldom a response plan and the location within the corporate network of critical structured data (such as an accounting system) and unstructured data (such as emails) is usually unknown. Location and mapping of this information is hugely challenging.

E-discovery processes have long been used to move from large pools of information to more focused, manageable content. They fulfil the same purpose in investigations. But whereas much of this information used to be evidence (spoken and written) sourced from witnesses, experts, and connected parties, digital has changed the game, upping the scale of challenge but also offering extraordinary new solutions.

Nowadays, 90 per cent of information is created electronically. And quantities are surging: 90 per cent of the world’s data has been created in the past two years, which is why innovations in the investigations space are so essential. After all, getting the investigation process wrong can be costly. Regulators penalise poor practice and reputational losses can be hugely damaging.

Self-serve and analytics

As an electronic investigations expert I get a great view of the latest advances. Besides the ability to bring together structured and unstructured evidence, two developments stand out for their forensic impact: selfserve and sophisticated analytics powered by AI. The former empowers investigators and litigation lawyers to do more analysis themselves. PwC’s Gateway is an example. Overlaid on a data analytics platform, this data visualisation and reporting tool graphically represents complex findings from structured and unstructured data sources in a way that is easy to understand.

Users can instantly see who has had access to what information when, by simply analysing email traffic to produce visual maps of relationships. The other development, analytics, draws on the latest innovations in AI and machine learning to rapidly (and automatically) get to the heart of the most relevant information in an investigation. Whereas investigators used to develop hypotheses and then use key terms to search for in-scope data they can now avoid the keyword challenge and zero in on what matters with unprecedented effectiveness.

Taken together, self-serve and analytics provide a unified platform through which investigators can assemble and interrogate all evidence much more quickly, and with far greater accuracy, than anyone imagined possible just a short time ago.

Take an expenses fraud, for example. As well as interviewing individuals and witnesses investigators will need to review expenses records and, in parallel, people’s calendars, emails and mobile phone records (including GPS co-ordinates). Analysed with the right tools this patchwork can deliver a picture of core patterns and relationships: who was where when, and whether their claims were legitimate or not.

Dynamic learning

With their arms around large quantities of structured and unstructured data like this investigators ‘simply’ ask the system to prove or disprove their hypotheses. Learning dynamically, digital investigations software such as Brainspace Discovery offers interactive visualisations and search tools that reveal stories that could otherwise often remain hidden in the data. Thanks to solutions like this, investigators have everything they need to create networks of evidence, ultimately revealing what happened and who was involved. Previously, it would have taken weeks or months to get to the answers. Now it can take just days.

Today, AI is being used to build a picture of historical events but soon we will see it applied to picking up anomalous behaviours within organisations, predicting crimes and stopping them before they occur. Of course, big issues around data privacy will need to be addressed before this can happen but over time it is highly likely that we will see the arrival of the truly adaptive, selfpolicing enterprise.

This was blog was originally posted here. 

Umang Paw| Partner, Forensic Technology
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