The US is a hotbed for technological innovation, leading the world in areas like space travel, military advancements, and artificial intelligence. This requires heavy investment from government and the private sector so the resulting intellectual property (IP) should be protected as a reward.
But some countries are trying to shortcut this process by stealing US innovation. Vying to expand their influence and strengthen their position as leaders on the world stage, the tactics used by these countries range from human intelligence collection and surveillance, to information warfare and practices like “ratting”–where foreign intelligence agencies utilize malware to access sensitive information.
The techniques range from intelligence agencies using graduate students to gain access to sensitive materials by studying at research universities, to pressuring scientists, business executives, or government employees that work on sensitive technologies to participate in acts like IP Theft.
Recent reports allege that a Chinese balloon did in fact gather sensitive intelligence from US military sites, despite efforts to block it. Getting early insights and taking faster, more proactive steps in counterintelligence are dependent on an ability to identify behavior or activities across agencies as well as the threat actors involved.
Addressing these threats through data and decision intelligence is critical for the US government. But one of the biggest obstacles for public sector agencies to mitigate this threat is fragmented and siloed data, which prevents them from seeing the full picture of their risk landscape. These pressures—coupled with the increasing pace of organizational decision-making, and the rapid availability and volume of data—are making it harder than ever to run an efficient and resilient agency.
Data is the Lock and Key
New research further underscores this, revealing that on average, IT decision leaders say 12% of all data records across their organization are duplicated. The duplicated data sits lurking in data lakes, warehouses and databases and prevents data/IT leaders from maximizing the value of data across their organization. As a result, the top priorities for leaders in 2023 are to improve data quality (46%), to drive operational efficiency (47%), and to strengthen analytics processes (47%). This is a change from 2021 when improving data quality was a top priority for only 26% of organizations.
What’s more, the primary issues with these duplicates are that data reconciliation and remediation is time-consuming (46%), leads to an increased exposure to risk (42%), and an inability to make timely and accurate decisions that will positively impact customers / citizens (31%).
There are several steps organizations can take to protect themselves against these potential threats.
AI and Advanced Analytics Can Mitigate These Risks
One trend government agencies are looking to in particular to stop fraud, waste, and abuse is Decision Intelligence (DI). The ability to bring data together so patterns or anomalies can be identified that may be indicative of the kind of behavior that may probe an investigation. It uses advanced analytics and AI to provide a closer look into specific people and organizations and monitor exposure to risks posed by sanctioned or risky entities that threaten intellectual property.
To achieve this, techniques like graph analytics and entity resolution need to be incorporated into the broader Decision Intelligence strategy.
Organizations have all the data, they just need the right technology to harness its value. Recent predictions from Gartner identified that 60% of government AI and data analytics investments are estimated to have a direct impact on real-time operational decisions and outcomes by 2024, driving home just how impactful DI will be for future disruption-ready and resilient organizations. One example of where this impact can come from is entity resolution.
A key underpinning to DI, entity resolution allows organizations’ to connect and resolve tens of billions of internal and external data points in one place. DI also enables organizations to leverage low-code data fusion to unify data, build single views of entities, and use graph analytics to generate networks, and scoring and alerting frameworks that help identify risk and opportunities at a massive scale.
Data as a Reusable Resource
When government agencies have a strong data foundation, they have created a trusted and reusable resource that they can utilize to automate and improve decision-making across the organization to solve many challenges – not just identifying IP theft. One classic use case commonly seen is reducing fraud in the public sector. In Europe, the Belgian Tax Authority has been able to reduce tax losses from VAT carousel fraud by an estimated 98% through the use of Decision Intelligence technology.
Having a robust, effective data management strategy is critical for companies to track nefarious and illegal activity, maintaining a competitive edge and protecting themselves against major losses of valuable intellectual property. There needs to be visibility around what’s going on in networks in different environments – whether the situation unfolding is an advanced persistent threat, a cyber threat, or something going on in the supply chain, it all comes down to connecting data to truly understand how to deal with those difficult problems.
Addressing IP theft is a complex and ongoing challenge that will require continued efforts from governments, businesses, and stakeholders alike. As the US continues to drive global technology innovation, Decision Intelligence will need to be a guiding light to help circumvent some of the manual work and help make quick and informed decisions to keep the IP safe.
About the author: Clark Frogley is the Head of Financial Crime Solutions at Quantexa. He began his career with the FBI investigating organized and financial crime and served as the Assistant Legal Attaché in the US Embassy in Japan. Previously, Frogley worked as an executive at IBM in positions as the global head of AML and Counter Fraud Services in Banking, the Financial Crime Practice Leader for IBM in Japan, and the Financial Crime Solution leader for AML, Sanctions and KYC.
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