Predictive Analytics For Safer Travels

by Kamal Brar

Vice President and General Manager of Asia Pacific, Hortonworks

The holiday season is here and more Asians are travelling than ever before. In fact, Asia has become the world’s fastest growing travel market. In 2016, Asians spent US$600 billion on international travel, and Southeast Asia posted the highest growth among Asian sub-regions, with 9% more arrivals, largely due to continued strong intra-regional demand. Our dynamic economies are strengthening in and outbound travel throughout the region.

This growth spells valuable opportunities for Asia’s economies. With travel in the region set to increase on both the leisure and business fronts, there will be more travellers, flights, jobs, revenue, and consumer needs – all creating new opportunities for those involved in the industry.

Looming Threats

Unfortunately, the picture is not entirely rosy. Acts of terrorism and insurgency continue to threaten public order in Southeast Asia and rates of violent crime are also increasing across the region, with regular reports of attacks on tourists.

The broad category of public safety must also include natural disasters, public health emergencies and financial crime. Quite apart from violence, fraud and personal data theft wreak a terrible cost on individuals and enterprises.

Globally, threats are increasing in frequency, complexity and their potential for extreme impact.

The intersection of increasing numbers of travellers with the growing potential for violent crime has rung alarm bells with the authorities and led to official warnings. In November 2017, Singapore’s Ministry of Foreign Affairs issued a travel notice advising Singaporeans to take a variety of precautions during the holiday travel season.  These include remaining vigilant and alert to local security developments, and avoiding locations known for demonstrations or disturbances.

Kamal Brar, Vice President and General Manager of Asia Pacific, Hortonworks

How can data play a part?

Can technology be brought to bear to improve the world of public safety? The answer is yes, and the solution lies in the application of big data analytics.

Authorities are becoming more skilled in the aggregation, analysis and curation of data related to citizen and traveller safety, pulling together evolving data sources such as transaction records, mobile phone data, social media chatter and telemetry.

In this vast volume of data, there exists evidence that can point to both persistent threats and immediate alerts. Discovering such indicators hidden in huge amounts of disparate data and turning them into actionable intelligence for mission critical decision-making, depends on the ability of public safety organisations to apply analytics to find the patterns that can lead to an interdiction before disaster strikes.

Intelligence services, national security organisations, law enforcement and disaster relief organisations are increasingly relying on the aggregation and accurate interpretation, in near real-time, of the endless flow of new data combined with legacy data that such agencies already hold in their own silos.

Integrating and analysing this constant stream of information from sources as diverse as body-worn cameras, CCTV feeds, 911 calls, map data and search histories helps identify and prevent criminal, terrorist and fraudulent activities, as well as deliver rapid assistance to areas hit by natural disasters or outbreaks of disease. Such deep insight to the worldwide threat environment also mitigates danger for travellers.

One of the pioneers of the use of big data analysis to detect crime and mitigate risk is the financial sector. Financial fraud is astonishingly widespread. The Association for Financial Professionals’ 2016 Payments Fraud and Control Survey found that 73% of finance professionals reported an attempted or actual payments fraud in 2015. The complexity, volume and speed of digital banking transactions, incomplete data and failure to share information among institutions are all factors in the spread of financial crime and the difficulty of preventing it.

According to a McKinsey report, the solution to fighting financial fraud lies in the application of artificial intelligence, machine learning and analytics to proprietary data sets, industry benchmarks and government information.

Here in Singapore, DBS Bank is showing the way. In a first for a Singapore bank, DBS last September established a ground-breaking programme that will enable it to leverage big data technology to detect abnormal transaction activities in the trade finance space.

Creating a safer environment with data

Maintaining safety for city residents and travellers alike is a critical responsibility for authorities, as well as being beneficial for economic sustainability.

From police departments to criminal investigative teams to disaster relief specialists, many public safety organisations are harnessing big data to strengthen their decision-making and efficiency. So far, they’re achieving impressive results.

Risk management specialist Prescient has developed Prescient Traveler, a mobile app that functions as a digital concierge for businesspeople, tourists, and students as they travel around the U.S. and the world. Conceptually similar to an application Prescient developed for the Defense Intelligence Agency, Prescient Traveler helps people stay aware of emerging and persistent threats as they venture to strange locales, both foreign and domestic.

Assuring that a specific individual with a unique profile will be safe in a specific location at a specific time requires analysing multiple data streams in real-time. To create a platform with the scale to deliver the sophisticated, commercial-grade service they envisioned, Prescient used some of the most advanced big data technologies.

Safety crucial to the success of the digital nation

The application of big data analysis to public safety is an important component of the much-heralded Smart City concept. It is well known that Singapore is committed to the Smart Nation initiative, but smart city endeavours in ASEAN nations like Indonesia, Malaysia, Vietnam, Thailand and the Philippines are also underway, with potentially significant impact on the local community. For many of these countries Smart City technology can help better utilise the existing resources (schools, hospitals, roads, public transportation) and extend its reach to the rural areas.

Digitalisation of government services can also help to provide greater transparency and accountability. Smart utility solutions can help better manage energy use, and IoT can even be integrated into natural disaster and risk management solutions.

Certainly, the application of Smart City technology can help ensure the safety of residents and visitors in Southeast Asia’s booming urban environments. As an example, Singapore’s authorities are making progress building an integrated national sensor network, designed to enhance security and incident response.

Indeed, big data aggregation and analysis promises to move policing from reactive to preventative. The UK’s West Midlands Police Force is already putting big data into practice to predict the locations of future crimes in order to more effectively deploy resources to prevent them.

Given that the world faces exponential growth in crime, terrorism and natural disasters, we can only be thankful that predictive analytics promises an effective solution.


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