We are living in a world awash in data. Accelerated interconnectivity, driven by the proliferation of internet-connected devices, has led to an explosion of data—big data. A race is now underway to develop new technologies and implement innovative methods that can handle the volume, variety, velocity, and veracity of big data and apply it smartly to provide decisive advantage and help solve major challenges facing companies and governments.
For policy makers in government, big data and associated technologies like machine-learning and artificial Intelligence, have the potential to drastically improve their decision-making capabilities. How governments use big data may be a key factor in improved economic performance and national security. This publication looks at how big data can maximize the efficiency and effectiveness of government and business, while minimizing modern risks. Five authors explore big data across three cross-cutting issues: security, finance, and law.
In Chapter 1, “The Conflict Between Protecting Privacy and Securing Nations,” Els de Busser, a senior lecturer and senior researcher at The Hague University’s Centre of Expertise Cyber Security, explains the conflicts between the data privacy and protection laws that apply to law enforcement and intelligence agencies versus those that apply to commercial entities in the private sector. The increasing localization of privacy laws has placed strain on cross-border data flows, both for law enforcement and for economic monitors. Exacerbating the problem is the different legal approaches taken in Europe and the United States, with the former tending to adopt more holistic legal frameworks, while the latter adopts more sector-specific frameworks.
In Chapter 2, “Big Data: Exposing the Risks from Within,” Erica Briscoe, a senior research scientist and lab chief scientist at the Georgia Tech Research Institute, explores how institutions can leverage big data to decrease their risk from malicious human behavior, such as insider threats. Dr. Briscoe explores how organizations can use big data techniques, including behavior modeling and anomaly detection to identify, monitor, and prevent malicious behavior. In addition, she argues that building and maintaining trust between employers and employees is critical to discouraging malicious behavior and insider threats. To create such a trusting environment, Dr. Briscoe recommends: protecting personally identifiable information to assuage fears that data could be used to negatively affect employees; monitoring both known threats and user behavior concurrently; and fostering a cybersecurity mindset, attained through a leadership-driven effort, that is able to adapt to changing threats. A sidebar exploring the future of trust in an increasingly automated world is also included.
In Chapter 3, “Big Data: The Latest Tool in Fighting Crime,” Benjamin Dean, Fellow for Cyber Security and Internet Governance at Columbia University, focuses on how digital technologies and analysis of big data can be used to identify external threats, including the detection and prevention of fraud, money laundering, bribery, terrorism, and other criminal activities. There are a range of big data analytic techniques discussed, ranging from metadata collection and network analysis, to data fusion and predictive analytics. A key recommendation is the need to find and invest in people who have the right knowledge, skills, and abilities to effectively and correctly use these analytic techniques. Additionally, at the strategic level, organizations need to understand how big data analytics fit into a wider organizational strategy.
In Chapter 4, “Big Data: Tackling Illicit Financial Flows,” Tatiana Tropina, a senior researcher at the Max Planck Institute for Foreign and International Criminal Law, explores how big data can help tackle the spread of online cybercrime and illicit financial flows—money that is illegally earned, transferred, or used. Digital technologies are facilitating illicit financial flows and the rise of an underground economy where bad actors can finance terrorism, evade taxes, and launder money. Faced with the changing nature of crime, big data promises to provide law enforcement and intelligence agencies the tools needed to detect, trace, and investigate this crime. Additionally, addressing the proper legal frameworks for cross-border criminal investigations is important. To reap the benefits of big data, governments will need to implement appropriate laws and regulations that take into account new digital technologies.
In Chapter 5, “Big Data: Mitigating Financial Crime Risk,” Miren Aparicio, Big Data: Mitigating Financial Crime Risk reveals how to use big data to reduce financial crime threats. This chapter analyzes best practices and new trends in anti-money laundering laws in the United States and European Union, with a focus on identifying the current gaps exploited by bad actors. big data tools can be applied to existing risk mitigation efforts, including sanctions screening, customer profiling, and transaction monitoring to help close existing gaps. The rise of regulation technology (“RegTech”) solutions provide further opportunities for taking advantage of big data to mitigate financial risk. Blockchain ledger technologies and smart contracts are currently being explored by banks and financial institutions to enhance due diligence and compliance.