Putting the crypt into encryption

Last week a group of intrepid lawyers joined us for a foray into the fascinating worlds of computer forensic investigations and fine wine.  Entitled the Gigabyte and the Grape, the event was designed to stimulate both the mind and the palate. However, the event proved to be so popular that we quickly outgrew the capacity of the original venue! We are always pleasantly surprised when our events exceed anticipated demand but given the growing importance of electronic evidence in legal proceedings, it is perhaps less surprising that brushing up on computer forensics knowledge is becoming a greater training priority for lawyers across practice areas.

Thankfully we were able to upgrade our venue to the historic St Andrew Holborn, dividing our time between the beautiful beamed Court House room for the presentation and the atmospheric crypts for the wine tasting segment of the evening.

The Gigabytes…

courthouseAfter a welcome drink, Lead Forensic Consultant  Tony Dearsley led our guests through our ‘Forensics for Lawyers’ presentation.

As the title might suggest, the purpose of the presentation is educating lawyers and although there is technical information and explanations, we focus on providing information that can be used in practice, covering key topics such as:

  • The types of data that can be extracted
  • The types of device which can contain evidence
  • Digital forensics methods
  • How digital forensic evidence can be used in cases

The Grapes…

cryptAfter the presentation, we entered the candle-lit crypts for the second part of this educational event; a wine tasting hosted by renowned sommelier Gilbert Winfield. Gilbert guided our guests through a flight of fine wines, starting with a Nicholas Feuillatte champagne and ending with a rare Madeira.

Accompanied by canapes specially-selected to match the wines on offer, it was a very convivial evening and one which we hope has given our guests useful insights on the power of computer forensics.

ProFile: Stephanie Painter (Associate Case Manager)

Stephanie Painter is one of our newest members of the Case Management team at Kroll Ontrack. Always popular with our clients and dedicated to her work (so much so that one of them accused her of being ‘too nice’ at our Christmas comedy evening! ), we decided to catch up with Stephanie to look back over her first year at Kroll Ontrack and find out a bit more about the woman behind the job. 

Ediscovery is still quite a specialist industry. What made you decide to pursue a career as a case manager?

I have always been interested in law, both in terms of legal practice and academically. I have an LLB  from Exeter University and went on to do an LLM in International Human Rights Law which was really fascinating and something I am still passionate about in my spare time (more on that later!-ed). After graduating I initially worked as a legal assistant in the residential conveyancing and litgation departments. It was here that I first became interested in and aware of ediscovery. Working in litigation gave me hands on experience of how technology can make or break a case and I found myself becoming more drawn to the ediscovery/investigative side of things. To cut a longer story short, I have now been at Kroll Ontrack for just over a year and I am fully immersed in the world of ediscovery!

Stephanie Painter. Kroll Ontrack. London.

Stephanie Painter. Kroll Ontrack. London

That sounds intense! How have you found it?

Although I had some relevant experience from my litigation days, it has been a steep learning curve!  I not only had to learn about ediscovery but also get up to speed with Computer Forensics  and Data Analytics, both of which were completely new areas for me.

Thankfully, Kroll Ontrack and the Case Management team have helped build my confidence. I started by learning on the job and assisting with smaller projects with just a few custodians and quickly progressed to working on a project with over 15 million documents!

What are you working on at the moment?

My current workload is a prime example of just how varied and busy the job can be. As I write this, I am managing a number of projects including a large multi-faceted project for a Silver Circle Law Firm, with Computer Forensics and Managed Review elements. This type of project presents unique challenges. I am not only responsible for educating our clients about the ediscovery process but also for overseeing the collection, processing and review of millions of documents which are spread across a number of data bases. A year later and I am building up my own contacts and taking on large, international projects independently.

What do you like best about being a case manager?

Ediscovery is very much a global industry and as someone interested in international law, I am really enjoying cases that have an international flavour. So far, I have been helping clients with cases spanning Europe, the US and Asia. Over the past year I have travelled to Barcelona, Amsterdam and Milan a number of times. Trips to Switzerland and Rome are also on the cards! I have always loved travelling, so it is great to now be able to do it as part of my role here at Kroll Ontrack. Being able to travel and meet clients at their own offices (in beautiful European cities!) has been a real highlight.

Well, that’s the work stuff out of the way! You’re obviously very busy but when you do have spare time how do you like to spend it?

Yes, I certainly do like to be busy, so I usually always have something planned for the weekend! I am a Qualified Mountain Leader and teach the Duke of Edinburgh award, so can often be found half way up a mountain teaching teenagers navigation. I also share a horse with my friend at home in the Cotswolds and like to ride as often as I can. I have volunteered with the Red Cross for the last 3 years and go across to the Refugee Destitution Centre in Hackney a few times a month at lunchtimes or in the evenings.  We have been delivering English writing classes that encourage creativity and the poems that the refugees have been writing are truly inspiring. I am a keen advocate of volunteering and like to encourage everyone to find some time in our busy lives to give something back to the community!

Our German Document Review Centre is now open

Review Room Pic 3 edited

Following the continued success of our London document review centre and unprecedented demand from European clients, we have now opened our purpose-built document review facility in Germany, located just outside of Stuttgart.

Stuttgart is a city renowned for being home to leading high-tech corporations, financial services providers and law firms, making it a natural location for our services. As Stuttgart boasts excellent transport links, clients from cities inside and outside of Germany are only a train ride away.

Key facts

German-qualified lawyers with a global outlook

Our pool of review lawyers are primarily from Germany and qualified at German law schools, meaning they are experts on German law and are often native German speakers. However, many of our review lawyers speak second or third languages and have extensive experience working at leading global firms.  At the moment, our document review centre is a little like a condensed version of Europe with current reviewers speaking and reviewing documents in  German, English, Spanish, French, Romanian and many other languages!

Designed with reviewers in mind

Our success in London has partly been down to the reviewer-focused way in which our facility is managed and designed and we have followed the same principles in Germany. Our document review centre provides lawyers with comfortable, ergonomic workstations as well as dedicated kitchens and break areas where it is possible to relax and make personal phone calls (mobile phones are not allowed in the review rooms).

As well as the facilities, our document reviewers receive a warm welcome and are invited to take part in socials and networking events alongside our permanent ediscovery team.

Details such as these have proven very popular with review lawyers and have enabled us to attract and retain the best review lawyers in the business, which in turn retains old clients and attracts new ones.

 

The ‘Go’-ahead for Artificial Intelligence

Go and artificial intelligence

In 1996 chess master Garry Kasparov was beaten by Deep Blue, a supercomputer developed by IBM. Before Kasparov was defeated, many commentators thought that it would be impossible for a computer to beat a human at the game. Chess is a sophisticated game, lauded for its complexity and often used as a measure of human intelligence and human success at the game depends on reading one’s opponent and planning. However, unlike a human, a chess computer is able to analyse all potential moves, a tactic that ultimately led DeepBlue to beat Kasparov.

Fast forward 20 years and there has been another surprise victory for artificial intelligence; this time with a Google-developed program called AlphaGo beating Lee Sedol, a 9thdan champion of the strategy game Go.

Go has long fascinated mathematicians and computer scientists. Back in 1965, the cryptologist I. J. Good described the difficulties involved in a computer beating a human Go player:

“Go on a computer? – In order to programme a computer to play a reasonable game of Go, rather than merely a legal game – it is necessary to formalise the principles of good strategy, or to design a learning programme. The principles are more qualitative and mysterious than in chess, and depend more on judgment. So I think it will be even more difficult to programme a computer to play a reasonable game of Go than of chess.”

Unlike chess, which is played on a board consisting of a twelve by twelve grid with only twenty-four pieces, Go is played on a 19×19 grid and uses counters known as stones. A standard Go set contains a whopping 181 black stones and 180 white stones. In order to win, a player must capture an opponent’s stones. Unlike chess, this is achieved by surrounding a stone with multiple stones which in turn makes mapping the number of potential moves much more difficult if not mathematically impossible. In other words Go is like chess on steroids.

Even as recently as 2015, the best Go programs only managed to reach amateur level and prompted prominent investors such as Elon Musk to comment that we were still 10 years away from a victory against a top ranking professional player.

So how did the computer finally beat a human?

Put simply, by being more human.  AlphaGo’s algorithm uses machine learning, neural networks and tree search techniques to make decisions. The program’s neural networks were initially trained to mimic expert human gameplay using data from historical games played by experts. This data consisted of around 30 million moves from around 160,000 games.  After this period of learning, the program was trained further by playing large numbers of games against other versions of itself. Once it had reached a certain degree of proficiency, it was trained further by being set to play large numbers of games against other instances of itself. Unlike chess programs, AlphaGo doesn’t use a ‘database’ of moves to play.

Because of this, the outcome of the game against Sedol was a complete surprise to AlphaGo’s creators. One of the developers commented:

“Although we have programmed this machine to play, we have no idea what moves it will come up with. Its moves are an emergent phenomenon from the training. We just create the data sets and the training algorithms. But the moves it then comes up with are out of our hands—and much better than we, as Go players, could come up with.”

Predictive coding: science fact not science fiction

The story of AlphaGo gives a fascinating insight how artificial intelligence is developing and  uses similar techniques to  our own predictive coding technology. In the same way AlphaGo uses machine learning to learn from past games, expert human reviewers train our platform to identify which documents are relevant and make legal document reviews more efficient.

For AlphaGo, this has resulted in a victory against one of the finest human players whereas predictive coding technology has received judicial approval stating that it is as efficient as traditional document review using keyword searches also uses machine learning techniques to mimic a human reviewer.

Many people still have doubts about using predictive coding technology but we hope intelligence victories such as AlphaGo’s will lead to greater public awareness about the capabilities of machine learning technology. After all, if a computer can beat a human in a game as complex as Go, suddenly believing in the capabilities predictive coding seems less of a leap of faith.

 

Kroll Ontrack’s Canine Forensics Team: Sniffing out the evidence and cutting costs

guide dogs

Kroll Ontrack is pleased to announce our latest weapon against data theft; our Canine Data Defenders. This new service, believed to be the first of its kind in the UK, will enable clients to reduce initial data forensics costs and speed up computer forensics investigations.

How does it work?

A dog’s sense of smell is unbelievably powerful, between 10,000 and 100,000 times as acute as humans, depending on the breed. A useful way of imagining this is to think of the difference in terms of vision; if a human can see an object one third of a mile away, a dog can see the same object 3,000 miles away. It is because of this ability that the dog’s sense of smell has long been utilised in the medical, military and law enforcement fields to detect cancer cells, explosives and drugs.

What do Kroll Ontrack’s dogs look for?

cf dogThe human endocrine system is extremely complex and to a trained nose, compounds found in sweat can reveal much about the human in question’s behaviour and mental state. Someone using a device for illegal activity, for example, is likely to release a greater amount of stress hormone into their sweat which in turn is transferred onto the device via touch. Kroll Ontrack’s canine team has been trained to pick up on these scents and lead handlers to devices that have been used for nefarious purposes. The process is simple and a team of two dogs can check 100 devices within an hour, which is a marked improvement on a human team handling and scanning each device.

After a successful pilot study, the Canine Data Defenders will be available to clients from 31st June 2016.

Kroll Ontrack Head of Computer Forensics , John Perro, commented “This is not about substituting human knowledge but about saving our clients’ time and money. Our dogs can pinpoint a machine used for suspect activity within seconds, allowing our human team to get straight into a type 2 data analysis.  We can also see applications in internal compliance investigations.  A quick sweep of an office using our dogs will provide compliance officers with a quick and accurate spot check of the company’s activities.”

A second team of dogs is currently in the final stage of training to provide early-evidence services for our ediscovery team, further cementing the role of dogs at Kroll Ontrack.

How can banks reduce litigation and investigation-related legal costs?

How can banks reduce legal costs?

Last week over 50 corporate in-house counsel and lawyers working in the financial sector gathered in the rather glamorous surroundings of the Banking Hall to join Kroll Ontrack  for our breakfast seminar, ‘Banks or Law Firms: Who holds the purse strings’

After a delicious breakfast, our illustrious panel tackled the complex and often, controversial topic of managing legal costs for banking-related investigations and litigations. The key themes up for debate were:

  • How recent ‘big ticket’ regulatory investigations have affected the banking world
  • Using the latest predictive coding technology to reduce legal costs
  • Leveraging corporate buying power when using law firms and other professional service providers
  • Discussing alternative pricing structures
  • Examining the pros and cons of unbundling legal services

The debate was moderated by Ben Fielding of Kroll Ontrack and our speakers included Elizabeth Meekison a Senior Lawyer in Commercial Litigation atLloyds Banking Group,  Mark Humphries – Senior Partner at Humphries Kerstetter, Thomas Leyland, Partner at Dentons and,  Orion Wisness, Discovery Consultant at Kroll Ontrack. With representation from in-house counsel from banks, senior partners from top law firms and a technology provider, each brought their own experiences and opinions to what was an eloquent, wide-ranging, and informative discussion.

The key points that emerged were:

Priorities for banks:

  • Banks value accuracy, defensibility of process and not necessarily lower costs when it comes to ediscovery
  • Working collaboratively with law firms and technology providers and ensuring regular and effective communication

The benefits of proactivity:

  • The importance of involving an ediscovery provider from the beginning of the disclosure process or investigation.
  • How implementing information governance strategies and managing the quantity and location of your data can reduce costs.
  • How fixed fee modelling could be implemented (and why this might not be a possibility in certain cases.)

Legislative concerns:

  • Are the standard disclosure rules too broad?
  • In light of spiralling data volumes, should the disclosure rules be modified so they are closer to the arbitration model?

The importance of predictive coding technology

With the recent judgement (Pyrrho Investments v MWB Property [2016] EWHC 256 (Ch)) approving the use of predictive coding still hot news, much of the debate and audience’s questions were focused on:

  • How technology such as predictive coding can be used to reduce the burden of big data in litigation and investigations
  • The implications of the recent judgement approving use of predictive coding technology in the UK
  • The need for both corporations and law firms to fully understand exactly what predictive coding entails in terms of both its capabilities and its limitations

We would like to thank speakers for taking the time out of their busy schedules to take part in the debate and share their expertise. We’d also like to thank our guests for joining us and further enlivening the discussion with their considered questions.

 

UK High Court approves use of Predictive Coding in litigation

male hands working with laptop computer

Last week legal technology providers in the UK had a lot to celebrate as the English High Court approved the use of predictive coding for disclosure in litigation.

The judgement, handed down by Master Matthews, gave official judicial authorisation for the use of predictive coding in High Court proceedings. Summing up his decision, Master Matthews stated that predictive coding is just as accurate, if not more so than a manual review using keyword searches. He also estimated that predictive coding would offer significant cost savings in this particular case and that the possible disclosure of over 3 million documents done via traditional manual review would be disproportionate and ‘unreasonable’.

To read the judgement in full, please click here.

How does predictive coding work?

Predictive coding is an advanced machine-learning technology which allows computers to predict how documents should be coded (i.e., should a document be tagged ‘responsive’ or ‘privileged’) based on decisions made by human subject matter experts. Put simply, an experienced lawyer trains the computer by coding a sample set of documents, and the computer then learns what to look for based on this training. In the context of edisclosure and other investigative exercises involving electronic evidence, this technology can find key documents faster and with fewer human reviewers, thereby saving on cost and review time.

Who uses predictive coding?

Other jurisdictions, such as the USA and Ireland, have led the way in giving judicial approval to predictive coding, and the UK judgement references these cases in detail. Despite these cases as well as the ever-increasing sophistication of the technology itself, the UK law community has been somewhat reluctant to make use of the technology, as explored in this study by Kroll Ontrack Legal Consultant and former litigation lawyer, Hitesh Chowdhry.

In Chowdhry’s white paper, ‘Rage Against the Machine; Attitudes to Predictive Coding Amongst UK Lawyers’, he notes that his study revealed that the main barriers to adopting predictive coding technology were:

  • Risk aversion and mistrust of the technology’s accuracy
  • Belief that predictive coding would have a negative effect on revenue
  • Satisfaction with existing methods and a belief that existing practices offered more accuracy than studies have suggested
  • Insufficient understanding and knowledge of the complex predictive coding process
  • Diffusion amongst professionals

The UK judgement counters much of the fears uncovered in Chowdhry’s study by stating that the technology is accurate and offers cost savings.

Predictive coding and the Civil Procedure Rules

As data volumes continue to grow and traditional manual reviews using keyword searches become less feasible, predictive coding may be the best path toward complying with the Civil Procedure Rules.

Jeff Shapiro, a lawyer who has written frequently on costs in edisclosure, offered this comment:  “The judgementapproving predictive coding for the disclosure of documents highlights the judiciary’s continued march to proportionate costs in litigation via application of the overriding objective. Review amounts to approximately 70% of total disclosure costs. With the ubiquity of electronic document creation and storage, litigators have an ever-increasing costs’ burden in order to fulfil their CPR disclosure obligations. The judiciary, recognising the realities of modern disclosure where millions upon millions of documents may need ‘to be considered for relevance and possible disclosure’, has proclaimed that predictive coding may be used as a substitute for manual review.”

The cost savings offered by predictive coding will undoubtedly be popular with clients and potentially will give a competitive edge in winning work.

We hope that this judgement will encourage more UK firms to take advantage of the benefits offered by predictive coding.

For more information about this technology, please click here.

Is it time for banks to take greater control of their legal spend?

Banking event

Legal fees incurred by banks can have a huge impact on profits. Deutsche Bank provides a prime example of this; according to data from Bloomberg, they have spent more than any other European financial institution due to a combination of regulatory fines and litigation costs.  Around 1.2 billion euros were earmarked for litigation. These legal costs have, in part, led to the bank reporting a  2.1 billion euro loss in the fourth quarter with the bank’s stock falling to the lowest value since 2009. In contrast, Bank of America’s profits rose by 10%, in part due to a reduction in spending on legal fees.

This leaves in-house lawyers in an awkward position when regulatory scrutiny and in-progress litigation cases are unavoidable but they are facing more pressure to cut cost.

The first port of call for any in-house counsel managing regulatory investigations is usually a trusted law firm, Yet, with the culture of billable hours being so prevalent, are law firms in the best position to provide the improved efficiencies and reduced costs in-house counsel are seeking?

Indeed, such is the concern about spiralling legal costs that the Competitions and Markets Authority, an organisation more associated with causing legal fees, recently announced that plans to investigate law firms in light the following concerns:

  • Whether clients can drive effective competition by making informed purchasing decisions;
  • Whether clients are adequately protected from potential harm or can obtain satisfactory redress if legal services go wrong;
  • How regulation and the regulatory framework impact on competition for the supply of legal services.

Kroll Ontrack is hosting a seminar discussing this difficult topic, with speakers from leading banks (Lloyds, Barclays) and top law firms (Dentons and Humphries Kerstetter). In what will no doubt be a fiery debate, the panel will discuss:

  • How recent ‘big ticket’ regulatory investigations have affected the banking world
  • Using new technology to reduce expenditure
  • Leveraging buying power when using law firms and other professional service providers
  • Discussing the relative merits of fixed fee vs billable hour pricing structures
  • Examining the pros and cons of unbundling legal services

To register for the event, please click here.

 

 

 

Happy Birthday, Document Review Centre

doc review 2

Can you believe it’s been a whole year since we launched our fabulous Document Review Centre in London? So much has changed since we first opened; we’ve doubled in size, we’ve launched a dedicated website for our review lawyers and we’ve even started to uncover trends in document review.

To celebrate this milestone, we held a party for our team of document review lawyers. Over 60 lawyers from current and past projects joined the managed review team at 1920 Bar in Clerkenwell for drinks and a few ‘friendly’ games of pool.

Below are a couple of photographs from the night.
doc review 3

 

 

 

 

 

 

doc review 4

 

 

 

 

 

We’d like to thank our lawyers for their hard work over the past year; they are often the unsung heroes of a case, working countless weekends, missing Bank Christmas, and generally putting in the hours to make sure clients’ deadlines are met. We hope you enjoyed the party and look forward to another busy year!

 

5 data analytics myths debunked

Data Analytics

Perplexed by Data Analytics? Stuck on statistics? Then fear not, Philip O’Donnell, Forensic Data Analytics Consultant is here to guide you through the fascinating world of analytics, explaining complex concepts, tackling technical terms and showing the power of data in a series of business scenarios.
In his first blog, Philip will debunk some of the most prevalent myths surrounding data analytics. Over to you, Philip!

1) Once you have an analytics tool, anyone can be a data analyst

Father of Data Analytics, John Tukey, summed up the aim of analytics in typically succinct manner by stating,

“The greatest value of a picture is when it forces us to notice what we never expected to see.”

Put broadly, data analytics is a process to uncover hidden patterns, unknown correlations, market trends, customer preferences using mathematical and statistical techniques.

However, many people think data analytics is just a tool that turns data into graphs and that once you have this tool, anyone can analyse data. This is a little like saying that by owning a saw, you are a master carpenter!
To get the most out of data analytics, it is imperative that the right techniques as well the steps in the process must be understood and used in the right context to be truly effective in any investigation and if performed incorrectly can have misleading discoveries.

2) Data analytics is just for auditors

Where there are people, there is data and this data can be analysed and used to improve the way we operate. Music industry moguls use data analytics to measure listener responses to new music. This then helps them work out which genres, and new artists, are likely to bring them a hit.
Analytics is used by all spheres of society, from medical research and environmental studies to more obvious financial applications. Even Hollywood screenwriters have discovered that analytics can produce great success stories. In the Oscar-winning film Moneyball, a poorly performing baseball team hired a statistics expert to help them change their drafting procedures. By using statistics to help select players rather than traditional scouting methods, the team went onto have the longest winning streak in baseball history.

Analytics helps people in all industries make better, more informed decisions and deliver new innovative ways of thinking and doing business.

3) Data context doesn’t matter

The key component to performing any analytics is to understand the environment in which the client operates. Interpreting and advising on findings is a key aspect of the analytics process, so to really add value for clients, sector knowledge is vastly important. The most experienced data analysts need to understand the context of the data, especially in high profile legal investigations, banking cases, corporate compliance, financial analysis, and government projects. Clients looking to get the most out of their data will need to choose a provider who is able to harness industry knowledge and take a pragmatic approach to data science and analytics methodologies.

4) Analysing data can compromise the security and integrity of data estates

This myth does have some truth in that many inexperienced analysts do not understand the importance of a proper data extraction exercise. Direct extraction of raw data from core system is a key step in the analytics process and in the past, I have seen where incomplete and incorrect data extraction has caused data analytics investigation to be invalidated.
However, an experienced data analytics provider is rigorous in ensuring data extraction is performed correctly and is accountable in the chain of custody. Done properly, performing extraction ensures that the complete dataset and minimises the risk of an incomplete investigation. Extraction is performed in such a way that it does not compromise existing security of the data as well preserving the integrity of the system. Extraction can be performed on multiple data sources. These include relational databases, data warehouses as well legacy flat files and dynamic xml formats.

5) Analytics techniques don’t change

Data analytics is an incredibly dynamic discipline and new techniques are being developed all the time. A good analytics provider will always stay abreast of the latest trends and methods. So what is in store for 2016?

According to the International Analytics Institute the number one trend for analytics in 2016 will be that the distinction between cognitive analytics and automated analytics becomes blurred. Automated analytics is the changing of an airplane price or stock price based on the real-time analysis of factors such as customer demand or other market forces. Cognitive analytics is the inspired by how the human brain processes information, draws conclusions, and codifies instincts and experience into learning. Cognitive analytics uses machine learning techniques such as Neural Networks, Logistic Regression and historic data. By understanding the human decision making and learning process, data scientists can incorporate this knowledge into their models and achieve even more accurate and in-depth insights.

Click here to find out more information about our Data Analytics service.