25 - 26 OCTOBER '23
PAVILION HOTEL KUALA LUMPUR

In the rapidly evolving landscape of financial technology, one of the most transformative forces at play is undoubtedly Artificial Intelligence (AI). Its potential to reshape the future of intelligent financial services is nothing short of awe-inspiring. As part of the 3rd Annual Islamic FinTech Leaders Summit, we were privileged to host Prof. Nazri, who delivered a captivating keynote presentation on “The Future of Intelligent Financial Services: Unlocking the Potential with Artificial Intelligence.” In a riveting conversation with him, we embarked on an exploration of the enthralling opportunities that AI presents within the realm of Islamic Fintech.

Emnes Events: One of the VC panelist yesterday suggested not to invest into AI companies because of it being the current market hype. How would you counter this narrative?

Prof. Nazri:  I appreciate the concern raised by the VC panelist regarding AI companies being seen as a market hype.

It’s a valid point, but I believe it’s essential to take a more nuanced approach when considering investments in this space. Investing in AI companies is fundamentally similar to any other investment strategy, and the key lies in distinguishing hype from fundamentals. Blanket avoidance of AI investments seems shortsighted, as it doesn’t account for the diversity within this sector. Hype, to some extent, is present in many industries, including over 40,000 shariah-compliant companies worldwide. Should we then completely dismiss all investment opportunities?

To counter this narrative, we should apply standard investment principles:

1. Business Model: Assess the AI company’s business model. Who are their clients? What are the real-world use cases? Are there success stories that demonstrate the technology’s impact?

2. Management Quality: Examine the leadership and management quality. Are they experienced and capable of executing their vision effectively?

3. Differentiation: What sets the company apart from competitors? Are they pioneering a unique approach or technology?

4. Impact: Evaluate the impact of AI on the companies being considered for investment. Does the technology genuinely enhance operations and competitiveness?

For example, a venture into an AI company that uses machine learning to optimize supply chains for e-commerce businesses, resulting in cost savings and increased efficiency, demonstrates a clear and valuable use case. This is a situation where AI fundamentals align with real-world impact.

While there is hype surrounding AI, a prudent investor can navigate the market by focusing on the core principles of sound investing and by carefully evaluating the AI companies’ potential based on their specific business models, use cases, management quality, differentiation, and impact.

"While there is hype surrounding AI, a prudent investor can navigate the market by focusing on the core principles of sound investing and by carefully evaluating the AI companies’ potential based on their specific business models, use cases, management quality, differentiation, and impact."

Emnes Events: How do you visualise the amalgamation of AI with underlying technologies like Blockchain?especially when the muslim world is divided on the shariah issues?

Prof. Nazri: When envisioning the amalgamation of AI with underlying technologies like Blockchain, especially in the context of varying opinions on Shariah issues within the Muslim world, it’s crucial to focus on commonalities rather than differences. I see six key areas where this convergence can have a substantial positive impact:

a: Medical and Healthcare
– AI and Blockchain can work together to enhance healthcare services, ensure patient data security, and enable efficient telemedicine solutions in compliance with Islamic principles.

b. Financial and Risk Assessment
– AI-driven risk assessment models can be integrated with Blockchain to create transparent and Shariah-compliant financial systems, ensuring ethical and fair financial practices.

c. Disaster Risk Management
– AI can analyze data for early disaster detection and response, while Blockchain can ensure transparent distribution of aid and assistance to affected communities in accordance with Islamic principles.

d. Social Finance (e.g., Zakat, Welfare Financing, Grants)
– Combining AI and Blockchain can streamline the distribution of charitable funds, such as Zakat, ensuring they reach the disadvantaged and those in need efficiently and transparently.

e. Legal Contracting
– AI and Blockchain can facilitate secure, tamper-proof smart contracts, reducing the need for intermediaries in legal agreements and ensuring their compliance with Shariah law.

f. Education
– AI-powered personalized learning and Blockchain-based credential verification can improve education access and quality, aligning with Islamic values of knowledge and learning.

These areas are not only conducive to the convergence of AI and Blockchain but also essential drivers for the Islamic economy. By focusing on these shared goals and potential impact, we can harness the potential of these technologies to benefit users and beneficiaries in the Muslim world.

Emnes Events: How do you visualise the amalgamation of AI with underlying technologies like Blockchain?especially when the muslim world is divided on the shariah issues?

Prof. Nazri: When envisioning the amalgamation of AI with underlying technologies like Blockchain, especially in the context of varying opinions on Shariah issues within the Muslim world, it’s crucial to focus on commonalities rather than differences. I see six key areas where this convergence can have a substantial positive impact:

a: Medical and Healthcare
– AI and Blockchain can work together to enhance healthcare services, ensure patient data security, and enable efficient telemedicine solutions in compliance with Islamic principles.

b. Financial and Risk Assessment
– AI-driven risk assessment models can be integrated with Blockchain to create transparent and Shariah-compliant financial systems, ensuring ethical and fair financial practices.

c. Disaster Risk Management
– AI can analyze data for early disaster detection and response, while Blockchain can ensure transparent distribution of aid and assistance to affected communities in accordance with Islamic principles.

d. Social Finance (e.g., Zakat, Welfare Financing, Grants)
– Combining AI and Blockchain can streamline the distribution of charitable funds, such as Zakat, ensuring they reach the disadvantaged and those in need efficiently and transparently.

e. Legal Contracting
– AI and Blockchain can facilitate secure, tamper-proof smart contracts, reducing the need for intermediaries in legal agreements and ensuring their compliance with Shariah law.

f. Education
– AI-powered personalized learning and Blockchain-based credential verification can improve education access and quality, aligning with Islamic values of knowledge and learning.

These areas are not only conducive to the convergence of AI and Blockchain but also essential drivers for the Islamic economy. By focusing on these shared goals and potential impact, we can harness the potential of these technologies to benefit users and beneficiaries in the Muslim world.

"While a central AI faculty is a good starting point, it’s vital to recognize that every university has its unique strengths and focus areas. Therefore, each institution should aim to establish its own AI center that aligns with its specific strengths and goals."

Emnes Events: What are your thoughts on the establishment of an AI faculty in UTM as announced during Budget 2024? How can educators fully utilise its potential?

Prof. Nazri:  The establishment of an AI faculty in UTM, as announced during Budget 2024, is undoubtedly a positive development and can serve as a model for other institutions. However, it’s essential to view this initiative critically and consider the following points:

1. Tailoring to Individual Universities: While a central AI faculty is a good starting point, it’s vital to recognize that every university has its unique strengths and focus areas. Therefore, each institution should aim to establish its own AI center that aligns with its specific strengths and goals.

Example: If a university has a strong background in healthcare, its AI center could prioritize research and development in AI-driven healthcare solutions, setting it apart from others.

2. Public and Private Sector Support: The sustainability of AI initiatives in academia heavily relies on support from both the public and private sectors. It’s essential to foster strong partnerships that facilitate funding, collaborative research, and industry involvement.

Example: Collaboration with private healthcare providers can ensure that AI solutions developed in the academic setting can seamlessly transition into real-world healthcare applications.

3. Uni-Industry Partnership: To fully harness the potential of an AI faculty, it’s imperative to establish robust uni-industry partnerships. This collaboration ensures that research and development efforts lead to industry adoption in a systematic and impactful manner.

Example: A university partnering with a leading technology company can jointly develop AI solutions, giving students hands-on experience while also contributing to real-world innovation.

4. Autonomous Management: An AI center within a university should have a degree of autonomy in its management. This independence allows for agile decision-making and the ability to adapt to rapidly evolving AI technologies and industry needs.

Example: An autonomously managed AI center can quickly adjust its curriculum and research focus based on emerging AI trends, ensuring that students are always at the cutting edge of technology.

My view is that the establishment of an AI faculty in UTM is a commendable step, the full utilization of its potential lies in the ability to tailor AI initiatives to individual university strengths, foster strong public and private sector support, establish uni-industry partnerships, and ensure autonomous management. By doing so, educators can ensure that AI initiatives are not just theoretical but practical, impactful, and sustainable.

"I am highly optimistic that the potential in Islamic banking through APIs is vast, but it comes with challenges. Careful design, continuous monitoring, and compliance with evolving Shariah interpretations are essential."

Emnes Events: How can AI contribute to Islamic banking through APIs?

Prof. Nazri: In my view, the integration of AI through APIs in Islamic banking is a remarkable opportunity. It can enhance efficiency, deliver personalized services, and ensure Shariah compliance. However, it’s crucial to navigate this path with care, addressing challenges such as training AI to respect Shariah nuances, continuously adapting to evolving interpretations, ensuring data privacy and consent, and eliminating bias in credit scoring. In doing so, Islamic banks can leverage AI’s potential while upholding their ethical principles and building trust with customers.

AI’s role in Islamic banking, particularly through Application Programming Interfaces (APIs), holds immense promise. Here’s a critical perspective on how AI can contribute to Islamic banking through APIs, along with a practical example:

1. Automated Customer Services: AI-driven chatbots and virtual assistants, accessible via APIs, do provide round-the-clock support, but they need to be meticulously trained to understand and respect the nuanced queries related to Shariah compliance. For instance, a customer might inquire about the Shariah compliance of a specific investment product. The AI should not only provide an answer but also explain the basis for its compliance to build trust.

2. Risk Management: While AI APIs can assess investment risk, they must ensure that the algorithms align with the latest interpretations of Shariah principles. For example, an AI system could assist in managing an Islamic bank’s investments by continuously evaluating the compliance of various investment options against evolving Shariah guidelines.

3. Fraud Detection: To effectively combat fraud, AI APIs must stay vigilant and adapt to new fraud patterns. For instance, if a customer’s spending pattern changes, the AI should promptly detect and verify if it aligns with their financial behavior, helping to minimize false alarms.

4. Personalized Financial Products: The customization of financial products requires AI to draw from a rich pool of data, which brings up issues of data privacy and consent. For instance, if an AI API recommends a Shariah-compliant investment to a customer, it should be able to transparently explain the data sources and factors considered in making that recommendation.

5. Credit Scoring: AI’s credit scoring capabilities can be transformational for Islamic banking, but ensuring that these algorithms don’t inadvertently introduce bias is crucial. For instance, an AI API assessing a customer’s creditworthiness should be monitored and tested to eliminate any potential biases that could lead to discrimination.

6. Operational Efficiency: While AI-driven APIs can enhance efficiency, they should be developed with a clear understanding of Islamic banking processes. For example, automating the compliance checks for Zakat deductions should be precise and in line with Shariah law.

I am highly optimistic that the potential in Islamic banking through APIs is vast, but it comes with challenges. Careful design, continuous monitoring, and compliance with evolving Shariah interpretations are essential. The example of an AI API providing explanations for its Shariah-compliant product recommendations illustrates the need for trust and transparency in this critical sector.

Emnes Events: How AI differentiate between Islamic Financial Sectors and Conventional Sectors?

Prof. Nazri: From my viewpoint, AI’s differentiation lies in its adaptability to unique parameters, data sources, and guidelines specific to each sector.

1. Data Sources and Features: AI can be tailored to analyze distinct data sources and features that characterize Islamic and conventional finance. For instance, in Islamic finance, AI may consider data related to Shariah-compliant investments, while in conventional finance, it might focus on a broader range of investment options.

2. Compliance and Ethical Guidelines: AI can be programmed to evaluate financial products and transactions for compliance with Islamic principles, ensuring no interest (Riba) or forbidden (Haram) elements are present. In the conventional sector, AI would not apply these specific ethical filters.

3. Risk Assessment Models: AI can create risk assessment models that align with the principles of Mudarabah (profit-and-loss sharing) and Musharakah (partnership) in Islamic finance. In contrast, for conventional sectors, AI may use different risk assessment models to address interest rates and other conventional risk factors.

4. Language Processing: AI can differentiate by processing financial documents in different languages. For Islamic sectors, it can process Arabic terms and understand the nuances of Shariah compliance. In conventional sectors, AI may focus on English or other languages with different terminology.

5. Customer Preferences: AI can personalize recommendations based on customer preferences related to Shariah-compliant investments. For instance, if a customer prefers Halal investments, AI can tailor investment suggestions accordingly. In the conventional sector, preferences would be based on different factors.

6. Market Behavior and Sentiment Analysis: AI can analyze market behavior and sentiment differently for Islamic and conventional sectors. For example, it can assess how specific news or events impact Shariah-compliant stocks versus conventional ones.

7. Product Development: In the Islamic sector, AI may be employed to develop innovative Shariah-compliant financial products, ensuring they adhere to ethical guidelines. In the conventional sector, it may focus on a wider range of product offerings.

In my view, AI’s differentiation between Islamic and conventional financial sectors is driven by its adaptability to the unique parameters and ethical considerations of each. AI customizes its algorithms and analysis based on specific factors, allowing it to serve these sectors effectively while upholding their distinct principles.

Emnes Events: What are the proactive steps financial incumbents can do in order to adopt AI despite legacy issues?

Prof. Nazri: From my viewpoint, the integration of AI in financial institutions with legacy systems is a complex challenge.

Here are the issues and solutions I see:

Issues:

1. Legacy Systems: Financial incumbents often grapple with outdated legacy systems that are not easily compatible with AI technologies.

2. Resistance to Change: Resistance to change from employees who are accustomed to traditional processes can hinder AI adoption.

3. Data Quality: Ensuring data accuracy and quality for AI models can be problematic when dealing with decades-old data.

Solutions:

A. Step-by-Step Approach: Financial incumbents should adopt a gradual approach. Start with internal AI training to upskill employees and build AI literacy.

Example: Conduct workshops and training sessions to familiarize staff with AI concepts and tools.

B. Design Thinking: Implement design thinking approaches that systematically address fundamental issues. Encourage cross-functional teams to brainstorm and come up with innovative AI solutions.

Example: Use design thinking workshops to identify pain points in existing processes and explore AI-driven solutions.

C. Modular Implementation: Break down AI adoption into modular components that can be tested and integrated without disrupting the entire system.

Example: Implement AI solutions in segments, focusing on areas where quick wins and proof of value can be achieved.

D. Sandbox Approaches: Create sandbox environments where AI solutions can be trialed every 8 weeks. This iterative approach allows for experimentation and learning.

Example: Develop a controlled environment to test AI applications, gathering insights and fine-tuning solutions before full-scale implementation.

I would recommend that the financial players can adopt AI despite legacy issues by taking a step-by-step approach, embracing design thinking, working on a modular basis, and regularly testing solutions in sandbox environments. This systematic and agile approach allows for AI adoption while addressing legacy system challenges.

"AI can never replace educators. Every human needs another human expert, but the backend is driven by AI to do the heavy lifting. The way forward is to design an optimal human-machine working model in every organization. How to ensure we get the best of technology and make it work for us."

Emnes Events: With the potential of learning personalization, do you think AI can replace educators without jeopardizing students’ involvement in their learning process?

Prof. Nazri: AI can never replace educators. Every human needs another human expert, but the backend is driven by AI to do the heavy lifting. The way forward is to design an optimal human-machine working model in every organization. How to ensure we get the best of technology and make it work for us.

Examples:

1. AI in Personalized Learning: Take the example of a student struggling with mathematics. AI can identify the specific areas where the student is having trouble through continuous assessment and tailor lessons to address those weaknesses. This personalization empowers educators to provide targeted assistance and ultimately helps the student grasp mathematical concepts more effectively.

2. AI in Language Learning: AI-driven language learning platforms, like Duolingo, employ machine learning to personalize lessons. These platforms adapt to the learner’s proficiency level, focusing more on areas where the learner struggles and less on mastered content. However, human educators remain indispensable for speaking practice, cultural context, and nuanced feedback.

3. AI in Higher Education: In higher education, AI can help students choose suitable courses based on their academic history, career goals, and personal interests. While AI can efficiently process vast amounts of data to make recommendations, students often require guidance from academic advisors to make well-informed decisions. This collaborative approach harnesses AI’s analytical power and human wisdom.

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25 - 26 OCTOBER '23
PAVILION HOTEL KUALA LUMPUR