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Our blog is about all things data: data analytics, data management, data governance, data quality, data visualisation. Gain insights from our data and analytics professionals working across all industries.

18 October 2017

A better way of getting to the heart of the matter

By Umang Paw 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...

28 September 2017

Big data, big deal?

By Maaike Platenburg, Freddy Bob-Jones and Friso Wiegman Benefits and challenges associated with Big Data for results measurements In our last blog, we explored the use of big data for monitoring and evaluation (M&E) purposes in international development. We concluded that big data can provide us with great insights into aid effectiveness; it can show whether development projects have been successful and facilitate a more adaptive process toward designing programmes that deliver better outcomes for disadvantaged people. However, current projects are still in the pilot phase and much still remains to mainstream the use of these techniques. With this blog we would like to build on our first blog by exploring the potential benefits and practical challenges associated with applying big data.

15 August 2017

Deploying Machine Learning in claims reserving

By Paul Delbridge Many insurers are investigating how Machine Learning can be best deployed to both improve risk segmentation and enhance pricing models. Many insurers have already acknowledged the speed at which both supervised or unsupervised Machine Learning can be used to build new types of high-quality models, leverage Big Data, and identify new relationships between variables. Relatively little has been made to date of the capabilities of Machine Learning or Artificial Intelligence to dramatically increase both the speed at which claims reserving can be undertaken, and the extent to which highly sophisticated automation can be introduced.

31 July 2017

Simplifying Fraud Analytics

By Neil Houston ‘Big Data’. Personally, I view the term as a bit of a misnomer, it is after all just data. Though I’ll grant that there it is more of it being created, and more importantly, organisations are holding on to it for longer. There appears to be a view in some organisations that the more data you have access to then the better chance you will have at deriving value or insight from it. Over the last 10 years I’ve seen that it is becoming more challenging for those responsible for detecting or investigating fraud

17 May 2017

Overwhelmed by complex data?

By Jonathan Watters Businesses have never had more access to data – and that brings enormous problems as well as benefits. The more data you have, the more difficult it can be to organise. Fortunately, there’s technology available to help. Managing big, data-heavy projects can be daunting. To give just two examples, we’ve worked recently with a company that needed to review its data for thousands of counterparties for compliance with anti-money laundering legislation. The company was given six months to complete the review, which would mean processing, checking and (if necessary) remediating 5,000 case files, each one of which had many supporting documents. In another, we worked with a national government that needed to review more than 1,000 capital projects and decide on a case-by-case basis

03 May 2017

The future of AI through our children

By Rob McCargow It’s becoming increasingly clear that the recent flood of technological breakthroughs, principally the growing maturity of AI, are going to fundamentally reshape our world and how we live and work in the future. And how we collectively respond will have profound implications for future generations.

26 April 2017

Reviewed your bank’s chat metadata lately? Maybe you should – before the whistle blows

By Amjid Mahmood Imagine this scenario. You’re the head of compliance at a leading bank, and an employee who works on the trading floor comes forward with some very serious allegations about a senior trader. According to this whistleblower, the trader has been disclosing confidential information about clients to external parties and sharing information on their trading positions. You know you have an obligation to conduct a thorough internal investigation and report any significant findings to the regulator. But you also know that the sheer volume and diversity of data that you’ll need to comb through will present challenges if you use in-house resources to do it.

19 April 2017

Deploying machine learning in insurance pricing

By Paul Delbridge Insurers have been investigating the deployment of machine learning techniques in the pricing arena, seeking to exploit the speed at which models can be built and refreshed compared to the use of more traditional generalised linear modelling techniques. Machine learning techniques offer significant advantages over these traditional models, including the availability of various types of non-linear models which can lead to a wide range of new insights. However, these new models are more difficult to explain to both brokers and to customers (especially when these more sophisticated models suggest significant changes compared to the expiring prices), and there is a degree of resistance to what might be viewed as a black box technology by management and marketing teams.

10 April 2017

What can your phone say about you?

By Kavitha Chandrasekaran Our phones have become an essential part of our lives – and that means that every day, we leave a data trail behind us. From emails and social media messages, to pictures and videos, we leave a digital footprint wherever we go. Mostly, this is entirely intentional; it’s rare to find someone who owns a phone that doesn’t have any saved messages and images. But when something goes wrong, information is everything – which is why, in the world of forensic investigations, mobile data can be a valuable goldmine. ‘Mobile forensics’ is becoming an important part of the work of our Forensics Data and Analytics teams – we are increasingly asked to collect and analyse mobile data during investigations. It’s possible to collect an amazing array of information from the average smartphone, from SMS messages and emails, to calendar events, internet history and bookmarks and even your social media history. It’s even possible to recreate deleted messages, social media, pictures and documents from a phone.

04 April 2017

How businesses are transforming revenue models by monetizing and protecting customer data

By Paul Blase Information has become a primary form of capital - to businesses that know how to monetize their data, that is. Organisations that embrace the art of the possible in data monetization stand to create new capital from data sources and ultimately transform their business models. In doing so, however, they must maintain a sharp focus on data privacy. Capturing and monetizing data will require intelligent, connected systems and processes that help ensure that data and privacy are managed with the same rigour as traditional assets. The good news is that, as the volume of data has multiplied, the technologies for capturing, analysing and storing information have become more powerful - and less costly.

30 March 2017

Needed: Trustworthy frameworks for monetizing data

By Grant Waterfall and Jay Cline The private sector’s rush to collect and monetize consumer data has led many companies to create vast information stockpiles without careful planning. That trend is continuing as developers of the Internet of Things produce countless devices without basic security and privacy features. For many companies, unfortunately, emerging risks tied to data usage have been an afterthought.

02 March 2017

The price is right – with Data and Analytics

By David Geere Pricing is of key importance for any business. Setting the right price for your products and services can play a big part in your success or failure (even if you’re a not-for-profit) and it’s incredibly sensitive. Research suggests that a small increase in price can bring a...

20 February 2017

The data world needs more women

By Cathy Wilks A recent survey predicted that by the end of 2016, fewer than 25% of technology jobs in developed countries will be held by women, slightly down on the proportion for 2015. The study suggested a number of reasons for the low take-up of technology jobs by women,...

16 February 2017

Our Lives in Data vlog: facing up to your data

By Tom Middleton In the fourth vlog in our series from the 'Our Lives in Data' exhibition at the Science Museum, we've experimented with the data mirror which is one of the most fun elements of the exhibition. Tom Middleton, from our Risk Assurance team, talks about the different technologies...

10 February 2017

Part II Data Governance banana skins: Enterprise data governance – the final step must be the first

If you read the first part of this series you’ll undoubtedly have been on the lookout for Data Governance banana skins and with any luck, will have avoided a few slips! In this blog I’ll talk about the silver bullet that will (apparently) resolve all data-related issues in one go – the Enterprise-wide Data Governance initiative. This subject deserves all the airtime it can get – it’s where most programs fail before they even begin.

02 February 2017

Using Personal Data to Build Customer Trust and Competitive Advantage

Every time you use a search engine, land on a website, buy a product or download an app, you generate and share personal data via a sophisticated and sometimes covert combination of tracking tools like cookies, beacons and e-tags. This expansion in personal data collection is creating enormous visibility into individual lives, preferences and behaviors, a trend that will escalate as technology continues to evolve with breakthroughs such as wearable devices, autonomous automobiles and the Internet of Things. The proliferation of data also represents a potential treasure trove of opportunity for companies seeking new sources of revenue and competitive advantages. In fact, 64% of respondents to PwC’s 20th Annual Global CEO Survey

19 January 2017

The Bot, the whole bot and nothing but the bot

By Triin Sober Bots have been getting a bad rep in the news recently. You may have seen articles on ticket touts using botnets to buy up tickets to concerts and events only to sell them on to fans at extortionate prices or smart devices connected to the internet of things being used in cyber attacks. But do we really know what bots are and can they be put to a better use?

09 January 2017

Can big data revolutionise the way we measure results in international development?

By Maaike Platenburg We hear a whole lot about big data these days. For many people, “big data” means a flood of data, but what exactly is it? According to UN Global Pulse, information can be defined as “big data” when the data volume can no longer be managed with normal database tools. Big data is typically characterised by the 3Vs: volume of data, variety of types of data and the velocity at which the data is processed. Big data comes in different ways and can be divided in structured data and unstructured data.

21 December 2016

10 ways financial services organisations are preparing for the GDPR

By Rav Hayer and James Drury-Smith The General Data Protection Regulation (GDPR) will put individuals in control of their personal data, empowering them to choose how (and whether) businesses use their data. Where personal data is not treated correctly, individuals will have increased rights to legal recourse and can, in some instances, claim compensation. Regulators across the EU will have unprecedented power to enforce the legislation and impose hefty fines in instances of non-compliance.

13 December 2016

Data lakes #2: Should I dive in?

By Jon Cooke Data lakes, as I said in my previous blog, are the latest buzz word in analytics. While I warned about jumping into the world of data lakes without thinking carefully about what you want to achieve, I do believe that these data depositories are the long-term future. They have a clear advantage over data warehousing because they offer a non-relational way of looking at your data

06 December 2016

Our Lives in Data vlog: analysing transport data

By Ben Whittingham and David Doyle Transport generates multiple sources of data, and it’s often being used real time. In the third vlog in our series from the 'Our Lives in Data' exhibition at the Science Museum, we've focused on the transport section which displays the inside an Oyster Card reader and a 3D model of Bond Street station.

01 December 2016

Data Governance banana skins - My top ten tips on avoiding a slip up

By Kiran Gill Data Governance banana skins - n sudden, unexpected and sometimes creates embarrassing Data Governance situation, often causing difficulty in realising long-term governance success. Data Governance banana skins can be easily side-stepped or comprehensively planned for if you know what to look out for in advance.

21 November 2016

Data lakes: Look before you leap

By Jon Cooke It’s a feature of developing technology that buzz words tend to appear all of a sudden – everyone is talking about it. At the moment it’s ‘data lakes’, a method of storing Big Data – for which Apache Hadoop is the best-known platform.

16 November 2016

How insurers can make still make use of “personality” data

By Paul Delbridge In early November, a leading UK personal lines insurer announced the launch of an app that would use Facebook data to “better understand first time drivers and more accurately predict risk”. This was intended to award discounted premium rates to safer drivers, who would be identified on the basis of specific personality profiles. Shortly afterwards, Facebook announced that this contravened its privacy policies, triggering a change of plan for the insurer.

09 November 2016

Our Lives in Data vlog: drawing on our personal data

By Cathy Wilks and Matt Gosnell Data visualisation is effective when we can trust the data we’re looking at. It has to be easily understood, and it has to be easy to read and decipher. It enables businesses to make quicker decisions and helps them to communicate with others in a relatable way.