BIG DATA T CRIME WATCH NANETTE HOOGSLAG / GETTY IMAGES Law enforcement is one area that is already benefiting from big data solutions. Paul Stokes explores the role of advanced crime analytics in tackling criminal activity and terrorism here is no question that the world contains an unimaginably vast amount of digital information that is increasing ever more rapidly. This makes it possible to do many things that previously could not be done: capitalise on business trends, manage disasters, aggregate complex scientific data, and so on. Certainly big data analytics is having a disruptive impact across countless industries, as they harness the mass of information available to them. One sector law enforcement understands that the amount of big data presents both an opportunity and a challenge. On the one hand, the wealth of information available includes the digital fingerprints of criminals and the digital footprints of their movements and activities. On the other, the sheer volume of data and information means that organising, analysing and making sense of it is a complex and daunting task. Today, an increasing number of specialised analytics software tools are available to help law enforcement agencies and their investigators address serious crime, by following and understanding those digital footprints. Information that could hold clues vital to a case may lie hidden in emails, phone records, public social media posts or financial data lawfully gathered as a part of criminal investigations. The ability to analyse and make sense of large volumes of data quickly is crucial. Advanced analytics software helps investigators quickly manage, integrate and analyse these large and complex sets of structured and unstructured data and intelligence, to highlight suspicious activities, find unusual relationships, and identify persons of interest. By increasing the odds of identifying and disrupting criminal activity, analytics technology is helping to revolutionise the way serious crime is prevented and solved. Stopping organised crime Advanced crime analytics can be used to disrupt this activity by processing public social media data and looking for relationships between those at risk and known recruiters As with the rest of the global economy, technology plays a huge role in connecting and facilitating criminal networks, and analytics is increasingly being used to tackle this scourge. For example, drug traffickers are constantly adapting their tactics and seeking out new distribution opportunities, methods and technologies. To avoid detection, they use complex methods such as professional facilitators to handle some business activities from performing financial transactions for laundering purposes and creating secure networks in order to hide their activities, to using registered companies for delivering the goods. With timely access to different data sets, analytics tools are increasing the efficiency of investigations by providing new insights faster. This guides decisionmaking and informs operational activities at a faster rate. Using crime analytics, data can be shared and used by different government agencies with an interest in the same data. Agencies can significantly reduce manual data-checking, dramatically increase their ability to share critical information and collaborate on workflow-dependent tasks. In addition, by allowing information to be shared across departments and agencies, law enforcement departments can coordinate efforts and respond more efficiently to alerts about changes in the status of an offender or victim. By analysing information gathered lawfully as part of an investigation, investigators can quickly connect the dots to find, monitor, track, risk assess and disrupt criminal networks. Countering terrorism Data analytics software also has a vital role to play in counter-terrorism operations and the battle against foreign fighters travelling to or from areas of conflict. The news that increasing numbers of teenagers are trying to travel to Syria to take part in terrorist activity seems to be coming with alarming regularity as socalled Islamic State (IS) extends its reach globally. Social media has a large part to play in this recruitment drive, as terrorist groups seek to reach individuals and influence them to join up. It even uses digital specialists to maximise its gains. IS is making expert use of social media and creating a new generation of digital native extremists, with many nations having underestimated the speed at which the recruiters have been able to reach out to individuals. To give a sense of scale, it is estimated that jihadis are sending up to 100,000 Twitter messages a day plotting terrorism. In response to the threat, Rob Wainwright, the director of Europol and a former MI5 officer, recently told the BBC that encrypted communications often via social media were, in fact, the most significant challenge in tackling terrorism. Scotland Yard assistant commissioner Mark Rowley, head of specialist operations at the Metropolitan Police, said he had witnessed the aggressive targeting of potential IS recruits through social media, specifically the vulnerable, people with violent backgrounds, very young people and those with mental health issues. Advanced crime analytics can be used to disrupt this activity by processing public social media data and looking for relationships between those at risk and known recruiters. By the same token, the software can help investigating agencies eliminate those who are not persons of interest, and focus on actual likely troublespots. Big data and risk management For todays risk professional, analysing data in real time and leveraging big data analytics as part of a resilient risk management strategy is no longer a niceto-have it is a must-have. It is a competitive differentiator, with analysts estimating that spending on big data for risk management will grow by 55 per cent, from US$470m in 2014 to US$0.75bn in 2016, as analytics tools mature and firms deploy more enterprise-wide solutions. For risk managers, data analytics tools and technologies have been particularly effective, especially for combating risk and fraud. Data analytics has been a part of risk and fraud management systems for some time, via transaction risk-assessment solutions or through internally developed big data platforms. These systems aggregate information from multiple sources so it can be analysed in new, more effective ways. These solutions allow teams to assess the potential for risk better. The information from these systems can provide fraud teams with real-time risk intelligence, which enables them to make better decisions based on hundreds or even thousands of risk variables. Another advancement is connecting disparate data sources to bring together insights from all customer channels instantaneously, to give much broader and deeper visibility into customer relationships and to target fraud prevention efforts better, by leveraging this integrated data view. Data and analytics tools will undoubtedly create new opportunities for improving risk detection and prevention, so its never been more critical for risk professionals to continue their leadership in adopting these technologies to stay a step ahead of criminals. Encrypted communications often via social media are the most significant challenge in tackling terrorism Evaluating data analytics alternatives As risk professionals look more closely at data analytics software, they will encounter a range of solutions, each with differing approaches, levels of support, and price tags. In-depth review and evaluation of each platform will be essential. The key questions to ask and issues to address are: 1. Can the software draw data of various types from multiple sources and disparate geographies? Digital information and data knows no boundaries, and can be found anywhere. A good analytics tool should be able to help you find the dots before connecting them. Commercial off-the-shelf technology is available to connect different data types automatically, to discover links, and uncover people, entities, patterns, locations and relationships of interest. In addition, the best tools are those that can use unstructured data such as text documents and social media posts, and recognise words and phrases as entities that can be analysed and linked automatically. That is one of the key ways in which big data becomes far more useful. 2. Does the software produce information, data and reports in a form that is useful to multiple parties? Analytics software should certainly be useful to the owner to find the pieces of information important to them at the time. But it should also allow for a broader look at patterns, trends and anomalies, which can offer decision makers and policymakers insight into how best to deploy resources. It should also include simplicity of graphic interfaces and configurable workflows, customisable by each end-user to suit themselves, maximising the gains from investment in the systems. Its ease-of-use tends to belie the powerful platform supporting the interface. 3. Is the software intuitive and easy to use? An effective analytics software platform should not require comprehensive IT training or capability for its use. Personnel at all levels, with minimal training, should be able to access and use the software to produce actionable results, quickly and frequently. By analysing information gathered lawfully as part of an investigation, investigators can quickly connect the dots to find, monitor, track, risk assess and disrupt criminal networks 4. What is the level of ongoing support required? Waiting months for data sources to be added, and being charged hundreds of thousands of dollars for service teams to execute tasks, are common complaints of the customers of some analytic software firms. Analytics software users should be able to make changes without requiring specialised IT skills. The volume and variety of data long ago reached such complexity and scale that only technology can truly handle it and maximise its value. Data analytics software can help by revealing valuable intelligence hidden in masses of data, and by turning big data into smart data. Not turning big data into smart data with easily accessible, very usable technology, will have consequences for those professionals looking for a competitive advantage. Paul Stokes is COO of Wynyard Group