Data Blog

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

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16 April 2018

Personalised Policies

By Sam Jones The insurance sector has always been known for being data-driven, in fact, some of the most early data analytics was with actuaries and insurance underwriters. The new challenges we face today is the sheer volume and variety of data which is increasing exponentially; a wealth of data is being generated by the increasing number of devices we interact with on a daily basis – from our mobile phones to the Internet of Things (IoT) - all of which provide high volume, mix-structured information on a real-time basis.

29 March 2018

Outperforming the human: How can machine learning help your business?

By Matthew Tomlinson Every week, it seems someone produces a new estimate for how much data we produce. According to the research company IDC, by 2025 we will have created 163 zettabytes. That’s the equivalent of 40 trillion DVDs, or the entire Netflix catalogue 489 million times over. Technology allows us to gather, organise and analyse these vast volumes of data – but a potential weakness remains, and that stems from human involvement.

12 March 2018

Unlocking the power of data to track and manage business traveller risks

By Arjun Kumar and Sarah Mullen In an increasingly connected world, business travel is essential for companies to maintain and expand their global footprint. So it's no surprise that according to the Global Business Travel Association, in 2016 worldwide organisations spent US$1.3 trillion (approx £1 trillion) on business travel. However, together with great opportunities, this can equally be problematic for companies, as authorities are increasingly scrutinising the activities of mobile workers.

01 March 2018

Stop. Think. Automate. Repeat.

By Peter Chastin  People are amazing. They can perform incredibly complex tasks, and achieve astounding goals, especially when working together. They are an organisation’s most valuable asset, and often considered to be irreplaceable in their role. Despite this, there are daily tasks that are performed by people in their jobs that are, quite frankly, not worth their time. Time is valuable as well as finite, and can be better spent on innovation than on the same task every day.

26 February 2018

Chatbots - Let’s talk about them

There are three things you should know about me - I’ll tell you two of them now. Firstly, I like talking. I’ll talk to strangers, to colleagues, to clients; I’ll talk to the radio even though I’m reasonably sure they can’t hear me. Secondly, I hate filling out forms. I hate that once you’ve filled out one form you have to fill it out again twenty minutes later. I hate having to navigate to section 27b if I don’t own my own home or have a pet with arthritis. Wouldn’t it be good if we could use technology to get rid of this, whilst increasing the data integrity? This is why I believe chatbots are so appealing.

29 November 2017

Data and analytics: Protecting us against financial crime part 1

By Jeremy Davey and Scott Samme The Chicago mobster Al Capone is famously (and perhaps erroneously) credited as the source of the phrase ‘money laundering’ in the 1940s, after his laundromat businesses were used to legitimise cash he gained through less salubrious means. Even Capone might have been surprised at how the money laundering business has boomed since his days. Our Global Economic Crime Survey shows the scale of the problem: global money laundering transactions worldwide are estimated at between $1 and $2 trillion – that’s 2% to 5% of the world’s total GDP. Less than 1% of this money is ever recovered by the authorities.

16 November 2017

The Gender Big Data Gap

By Harjinder Kaur - PwC, Navin Haram - UN Women and Fiona Bayat-Renoux - UN Women “To achieve gender equality and empower all women and girls” is the fifth of the 17 Sustainable Development Goals (SDGs) set out in the United Nation’s plan, Transforming our world: the 2030 Agenda for Sustainable Development. In our previous blogs we’ve discussed how big data can be used to monitor and evaluate international development. Big data can give us great insights into aid effectiveness and development projects, but it also comes with its own challenges.

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

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.

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