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Technology and space industries have always inspired each other, and ever since the mid-20th century, they have changed our lives forever. Our proposed SpaceTech framework reveals the relationship between space and technology and how it can be a single innovation engine for the region. There has been much discussion about recent developments in the space sector, the democratization and consumerization of space industries, and the decreasing cost of manufacturing. However, it is important to note that space and technologies, particularly those related to digital and communication, should not be considered separately. They have inspired each other since the second half of the 20th century. SpaceTech is already a reality and the potential for innovation and economic growth resulting from the space and technology sectors is enormous.

Advancements in the Region

The region has witnessed, over the last few years, ambitious plans for the space and technology sectors. Significant advances have also been made by countries of the Gulf Cooperation Council (GCC), with many having their independent space programs. National transformation agendas, efforts to localize manufacturing and services, and the introduction of effective regulation and deregulation will continue to propel the transformation of the sectors.

Last year, KSA sent Rayyanah Barnawi – the first Arab woman in space – to the ISS. On the ground, the Kingdom is establishing the foundations for the execution of its space strategy which is expected to be released soon. The former Saudi Space Commission has been transformed into the Saudi Space Agency which is already making global news through the inaugural Space Debris Conference in February 2024, expected to be established as a bi-annual event in the Kingdom.

From launching the Arab world’s first Mission to Mars to signing the Artemis Accords, the UAE has also emerged as a leader in space exploration. Emirati astronauts, Hazzaa Al Mansoori and Sultan Al Neyadi flew on ISS missions in 2019 and 2023 respectively. The uncrewed Mars mission “Hope Probe” was launched in 2020 and has been in Mars orbit since 2021.

Aura SpaceTech Framework

Various advanced and emerging technologies play a key role across space sector activities. In Aura Middle East, we have established a framework mapping these technologies against a taxonomy of business, research, and exploration activities in the space sector. The framework reveals the relationship between Space and Technology, helping us to identify application areas, clusters of entrepreneurial activities, and the description, profiling, and measurement of economic activities across the space upstream, midstream, and downstream value chain.

Technology is pervasive across the six space sector domains highlighted in the framework: Access to Space, Remote Sensing, Satellite Communications and Satellite Navigation, Space Safety, and Outer Space Activities. Our framework suggests a view of space and technology as essentially one single innovation engine for countries and economies. Policymakers and regulators must work together across sector boundaries to leverage this economic and innovation potential. Only through the juxtaposition of space activities and related digital technologies will we be able to discover all investment and innovation opportunities, clusters of entrepreneurship, skills gaps, and required improvements to legislative and regulatory frameworks. As the socio-economic transformations across the region continue to be daring.

The Microchip

The Apollo program stands as a monumental achievement in human history, showcasing the power of science, engineering, and exploration with the historic 1969 Moon landing. Amidst numerous challenges, the success of Apollo hinged on pioneering technologies, notably the Apollo Guidance Computer (AGC), a digital computer that emerged as the unsung hero. The AGC computer was revolutionary since it leveraged integrated circuits or microchips, which allowed NASA engineers to maximize system performance while minimizing size and weight to meet the various constraints posed by the mission. This breakthrough not only propelled humanity to the Moon but also accelerated the development and adoption of integrated circuits.



In the ever-evolving financial landscape, the battle against financial crime has become more complex and demanding. Traditional methods of detecting and preventing illicit activities are proving insufficient against sophisticated schemes. As a result, the financial sector is turning to an increasingly powerful ally: Artificial Intelligence (AI).

The Rising Threat of Financial Crime

Financial crime encompasses a range of illegal activities, including money laundering, fraud, terrorist financing, and insider trading. These activities not only cause significant financial losses but also undermine the integrity of financial systems and institutions. The global scale and intricate nature of these crimes make them particularly challenging to combat. Financial crime doesn’t stand still; the tactics used by fraudsters are constantly changing, making it a never-ending battle.


AI: A Game Changer in Financial Crime Prevention

Artificial Intelligence has emerged as a transformative force in various industries, and its potential in fighting financial crime is immense. At Aura, we check about 1.2 billion transactions for signs of financial crime each month across 40 million customer accounts, using AI to help us do this. Here’s how AI is making a difference:


1. Enhanced Detection Capabilities

Traditional rule-based systems often fall short in detecting complex and evolving financial crimes. AI, particularly through machine learning (ML) algorithms, can analyze vast amounts of data in real-time and identify patterns that may indicate suspicious activity. As new financial crime tactics or trends emerge, we teach our AI what to look out for. As a result, we’re able to find and tackle financial crime faster and more thoroughly than ever before. These advanced algorithms can adapt to new threats, improving detection rates and reducing false positives.

2. Real-Time Transaction Monitoring

AI-powered systems can monitor transactions in real-time, flagging any anomalies that could signify fraudulent behavior. This capability allows financial institutions to act swiftly, preventing potentially fraudulent transactions before they are completed. For instance, AI can detect unusual transaction amounts, atypical transaction locations, and deviations from normal spending patterns.


3. Improved Customer Due Diligence

Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations require financial institutions to verify the identities of their clients and assess their risk profiles. AI can streamline this process by analyzing data from various sources, including social media, to build comprehensive profiles of clients. This not only enhances compliance but also helps in identifying high-risk individuals and entities.

4. Fraud Prevention and Mitigation

AI can predict and prevent fraudulent activities by analyzing historical data and recognizing patterns associated with fraud. For example, credit card fraud detection systems use AI to identify and block transactions that deviate from a cardholder’s usual behavior. Furthermore, AI can assist in recovering funds by tracing the flow of stolen money through multiple accounts and jurisdictions.


5. Strengthening Cybersecurity

Financial crime often intersects with cybercrime, as criminals exploit vulnerabilities in digital systems. AI can bolster cybersecurity measures by identifying and neutralizing threats before they cause harm. Machine learning models can detect malware, phishing attempts, and other cyber threats, ensuring the integrity and security of financial systems.

Challenges and Considerations

However, while powerful, AI can also be misused, and each deployment option presents trade-offs. To mitigate these risks, we adopt responsible practices, prioritize transparency, and continuously assess the impact of AI on our customers and beyond. Responsible use of AI is at the forefront of our design choices as we seek to increase our use of these new technologies. The implementation of AI systems requires substantial investment in technology and skilled personnel. Additionally, there are concerns about data privacy and the potential for AI biases, which could lead to discriminatory practices.

To address these challenges, financial institutions must adopt a balanced approach, combining AI with human expertise. Regulatory frameworks also need to evolve to accommodate the use of AI in financial crime prevention, ensuring transparency, accountability, and ethical considerations.

Google Partnership

AI has the potential to transform how financial crime is tackled across the industry. We partnered with Google to co-develop the AI system we use to check for financial crime - known internally at Aura as Dynamic Risk Assessment. We piloted it in 2021, with Google launching it to the wider financial services sector last year. The results speak for themselves. We’re finding two to four times more financial crime than we did previously, with much greater accuracy. Historically, we had a high number of false positives, meaning that we were calling customers unnecessarily to ask them about what turned out to be completely legitimate activity. Now, we have 60% fewer false positive cases.


Detecting Crime

This is just one of the ways we’re using AI to help us fight financial crime. AI has helped us to improve the precision of our financial crime detection and reduce alert volumes, meaning less investigation time is spent chasing false leads. It has also helped us reduce the processing time required to analyze billions of transactions across millions of accounts from several weeks to a few days. We’re able to find the signs of financial crime faster, with less impact on our customers, and provide more useful information to law enforcement, contributing to more effective outcomes in the fight against financial crime.



The fight against financial crime is a continuous and dynamic process. As criminals become more sophisticated, financial institutions must leverage cutting-edge technologies to stay ahead. AI offers a powerful tool to enhance detection, prevention, and mitigation of financial crime. By harnessing the power of AI, we can build a more secure and resilient financial ecosystem, protecting both institutions and individuals from the pervasive threat of financial crime.




The intersection of human expertise and technological innovation is transforming the cybersecurity landscape. Aura Solution Company Limited proposes a new cybersecurity framework that emphasizes the crucial role of human-led strategies combined with advanced technology to create a robust defense mechanism for organizations.

The Importance of a Human-Led Approach

While technology is essential for detecting and mitigating cyber threats, the human element remains irreplaceable. Cybersecurity professionals bring critical thinking, contextual understanding, and adaptive problem-solving skills that technology alone cannot replicate. Human expertise is vital for interpreting complex data, understanding nuanced threats, and making strategic decisions.

Key Aspects of Human-Led Cybersecurity

  1. Expert Analysis and Decision Making:

    • Cybersecurity experts analyze data and trends to identify potential threats that automated systems might miss.

    • Strategic decision-making based on experience and contextual knowledge.

  2. Threat Hunting:

    • Proactive identification of security threats by cybersecurity professionals.

    • Continuous monitoring and analysis to anticipate and neutralize threats before they can cause harm.

  3. Incident Response:

    • Rapid and effective response to security incidents.

    • Coordination between different teams and stakeholders to manage and mitigate damage.


The Role of Technology in Cybersecurity

Technology enhances the capabilities of cybersecurity teams by providing advanced tools for detection, analysis, and response. These tools help in handling large volumes of data, identifying patterns, and automating routine tasks, thereby allowing human experts to focus on more complex issues.

Key Technologies in Cybersecurity

  1. Artificial Intelligence (AI) and Machine Learning (ML):

    • AI and ML algorithms can analyze vast amounts of data to detect anomalies and potential threats in real-time.

    • Predictive analytics to forecast potential cyber-attacks based on historical data.

  2. Automated Threat Detection:

    • Automated systems can quickly identify and respond to known threats, reducing the time and effort required for manual intervention.

    • Use of signatures and behavior-based detection methods.

  3. Advanced Encryption:

    • Ensuring data privacy and integrity through robust encryption methods.

    • Protecting sensitive information from unauthorized access.

  4. Blockchain Technology:

    • Enhancing security and transparency in transactions and communications.

    • Use of decentralized ledgers to prevent tampering and fraud.


Integrating Human Expertise and Technology

Aura Solution Company Limited’s cybersecurity framework advocates for a symbiotic relationship between human expertise and technological tools. This integrated approach maximizes the strengths of both elements, creating a more resilient cybersecurity function.

Framework Highlights

  1. Collaboration and Communication:

    • Encouraging collaboration between cybersecurity teams and other departments.

    • Clear communication channels to ensure timely sharing of information and response to threats.

  2. Continuous Training and Development:

    • Regular training programs for cybersecurity professionals to keep up with the latest threats and technologies.

    • Development of skills in using advanced cybersecurity tools and technologies.

  3. Comprehensive Risk Assessment:

    • Regular risk assessments to identify vulnerabilities and potential threats.

    • Use of both human judgment and technological tools to evaluate and mitigate risks.

  4. Adaptive Security Measures:

    • Implementation of adaptive security measures that can evolve with changing threats.

    • Use of AI and ML to continuously learn and improve security protocols.

  5. Regulatory Compliance:

    • Ensuring compliance with relevant regulations and standards.

    • Regular audits and assessments to maintain compliance and improve security practices.



Aura Solution Company Limited’s human-led and tech-enabled cybersecurity function represents the future of digital security. By combining the strategic thinking and problem-solving abilities of human experts with the power and efficiency of advanced technologies, organizations can create a robust and adaptive cybersecurity framework. This integrated approach not only enhances security but also fosters a culture of continuous improvement and resilience in the face of evolving cyber threats.

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