Innovation Challenges

ESG (Environmental, Social, and Governance) considerations present a significant opportunity for the insurance industry since ESG it covers all aspects of business including: (1) risk mitigation – taking into consideration environmental factors is increasingly becoming important for risk mitigation and modelling, (2) market demand – increasingly customers are looking for insurance-related products in line with ESG goals and commitments.

By leveraging technology to integrate ESG considerations into their operations, the insurance industry can address emerging environmental and social challenges, tap into new markets, and contribute to a more sustainable future.  Hence, QIC sees many different application areas and use cases for ESG service(s), solutions and products in the industries which include (but are certainly not limited to):

• Risk Assessment: Technology can analyse ESG factors such as climate change, social dynamics, and corporate governance to evaluate risks more comprehensively. This assists insurers in pricing policies accurately and mitigating potential losses.
• Green Insurance Policies such as environmental liability insurance, responsible underwriting and investment guidelines etc
• Data Analytics: Utilizing big data and AI, insurers can assess ESG data to inform underwriting and claims decisions. This data-driven approach enables insurers to promote sustainability and reduce environmental impact.
• Regulatory Compliance: Tech solutions can help insurers adhere to evolving ESG-related regulations and reporting requirements, ensuring transparency and adherence to industry standards.
• Sustainability Reporting: Advanced data analytics and reporting tools enable insurers to communicate their ESG efforts to stakeholders, enhancing transparency and corporate responsibility.

• Solutions that see ESG as a business opportunity. QIC is looking to bring new solutions to the market that drive business growth and can be incorporated into the core business functions.
• We are looking for startups that have domain expertise specifically in the insurance field.
• Besides startups, we can also consider more mature scaleups for this challenge statements.

Generative AI represents a transformative opportunity for the insurance industry as it has the potential to vastly improve and streamline all areas of the insurance value chain. QIC sees many different application areas and use cases for the insurance industries which include (but are certainly not limited to):

• Underwriting Efficiency: AI can analyse vast datasets to automate underwriting processes, quickly assessing risks, and streamlining the policy issuance process. This leads to faster decision-making and reduces operational costs.
• Claims Processing: Generative models can assist in claims validation by comparing historical data to current claims, helping to identify potentially fraudulent or inaccurate claims. This accelerates claims settlement and minimises losses.
• Risk Assessment: AI can generate synthetic data to simulate various risk scenarios, enabling insurers to refine their risk models. This allows for more accurate premium pricing and risk management.
• Customer Engagement: AI-driven chatbots and virtual assistants can enhance customer interactions by providing instant support and personalised policy recommendations, improving customer satisfaction and loyalty.
• Fraud Detection: Generative AI can identify anomalies and patterns in claims data to detect potential fraud, helping insurers proactively mitigate losses and maintain trust in the industry.
• Product Customization: AI can analyse customer data to create personalised insurance products that better meet individual needs, increasing policyholder retention.
• Predictive Analytics: Generative models can forecast future trends and events, enabling insurers to adapt their strategies and policies in response to changing market conditions and emerging risks.
• Compliance and Risk Management: AI can assist insurers in complying with regulatory requirements and maintaining a comprehensive view of risk exposures, ensuring sound governance.

What We Are Looking For

• Everything in Insurance needs validated data. The longitude of this data depends on the type of insurance. We are looking for partners that have a validated insurance use case with other insurers.
• We are looking for startups that have domain expertise specifically in the insurance field.
• Ideally, we are looking for startups that have done specific Gen Ai related projects with insurers in Asia.

Increasing global demand for clean water has led to a surge in sludge production, posing significant challenges for municipalities, industrial wastewater treatment firms, and private asset owners. MATAR acknowledges this challenge and seeks economically viable options for sludge recovery and recycling at its onsite Wastewater Treatment Plant.

• Solutions providers should have previous experience with developing similar solutions
• Solutions providers should have the ability to deliver and install working proto-type solution(s) comprising addressing any of the above innovations.
• Provision of reports demonstrating of efficiency/efficacy of solution(s) throughout trial period
• Provide recommendations on future solution designs incorporating lessons learn during trial
• Provision of detailed design and proposal for scaled-up solution(s)

In today's economy, transportation and logistics play a crucial role, leading to substantial investments in airport, seaport, and logistics capacity worldwide. These investments, costing billions and having long lead times, are essential to meet growing demand. Yet, there are alternative ways to increase capacity and economic growth. By utilising cutting-edge AI, particularly deep reinforcement learning, we can devise smarter allocation strategies to achieve an estimated 10% throughput increase.

This project aims to use deep reinforcement learning to address high-value resource allocation challenge for industries like seaports, airports, train terminals, and logistics centers.

These industries currently rely on a mix of human decision-making and traditional resource management systems (RMS), governed by simple rules and constraints. However, traditional RMS tools, struggle to consider trade-offs over different time frames, historical behavior patterns, or adapt to new information. This complexity surpasses human cognitive capacity and traditional RMS computational capabilities. Solving it requires quantum computing or reinforcement learning to devise novel strategies to balance trade-offs and navigate short-term and long-term scenarios.

• A user-configurable interface for adjusting reward/penalty levels for desirable and undesirable behaviors.
• A stochastic policy that introduces nonlinearity and randomness for solving complex real-world resource allocation problems.

Qatar's National Vision 2030 includes provisions for responsible management of the environment with harmony and balance between economic, social development and environmental protection.

In support of the National Vision, MATAR is keen to explore usage of sustainable energy sources for its asset operations. Solar energy is a renewable and clean source of energy that can help reduce greenhouse gas emissions and combat climate change. Floating solar panels at sea can offer a promising way to harness this energy without compromising land use.

• Durability: To protect the solar panels from salt corrosion and marine fouling, special coating materials and methods are needed to make the panels more durable and resistant
• Efficiency: Cleaning technologies are needed to remove the dirt and debris that may accumulate on the panels and reduce their efficiency; these may include self-cleaning coatings, robotic cleaners, or water jets to keep the panels clean.
• Adaptability Design: To cope with the shading and wave effects, solar panels on sea need to have adaptive and resilient designs that can optimize their performance and stability in different conditions; these may include using bifacial solar panels that can capture light from both sides, or tilting mechanisms that can adjust the orientation of the panels according to the sun position and wave direction
• Anchoring: To securely anchor the solar panels to the seabed or floating platforms, innovative anchoring solutions are needed to reduce the costs and engineering challenges; these may include using mooring systems, tension-leg platforms, or spar buoys to anchor the panels
• Maintenance: To access & maintain these panels at their optimum efficiency
• Grid Connection: To connect sea based solar panels to the grid or storage systems,  underwater cables need to be developed that can withstand the water pressure and currents, and minimise the technical difficulties
  

The Environmental and Social Impact Assessment (ESIA) is a comprehensive study conducted to determine the potential environmental and social effects resulting from a prospective new project. It ensures that the potential impacts (both positive and negative) on the environment and communities are assessed and considered in line with environmental and social laws and standards. Currently, the review and evaluation process for ESIA studies for new projects is lengthy, leading to prolonged wait times for the issuance of essential environmental permits. This delay stems from the vast amounts of data, information, and studies required for comprehensive assessments.

The end-goal for the solution is to be adopted by the Ministry of Environment and Climate Change as the end-user post POC. The developed solution can be used for forecasting new developmental cases as well as future environmental situations based on current data.

In-Scope:

• Improve the decision-making process to proceed with new project developments.
• Provide a more precise project assessment of environmental system analysis.
• Make predictions for different cases as well as future studies.
• Save time and manpower required.
• Expedite the ESIA review and environmental permit issuance process.

This challenge statement is jointly supported by the Ministry of Environment and Climate Change as well as its potential end-user Qatar Industrial Manufacturing Company (QIMC)(Q.S.C). The Ministry will utilize and supply the solution to end-user(s), and provide some of the funding for the initial POC/Pilot with the end-goal for the solution to be adopted by the end-user post POC.    

In-Scope:

• Data Collection and Input: relevant data from various stages of aluminium production, such as raw material extraction, energy consumption, transportation, etc.
• Calculation Algorithms: based on relevant standards and guidelines to accurately calculate carbon emissions at different stages of the aluminium production lifecycle.
• User Interface (UI) Development: a user-friendly interface that guides users through the data input process, parameter selection, and generating carbon footprint reports.
• Carbon Footprint Reporting: detailed reports that provide a breakdown of carbon emissions by process, source, and overall carbon footprint. The reports should be informative and easy to understand.
• Compliance with Standards: the software aligns with applicable international standards and guidelines for carbon accounting in the aluminium industry.
• Accuracy and Verification: mechanisms for accuracy and verification to ensure that the calculations and results are reliable. This might involve providing information about data sources, assumptions, and methods used.
• Customization for Qatar: Adapting the calculator to the specific context of Qatar's aluminium industry, considering factors like energy sources, local processes, and regulatory requirements.
• User Support and Training: resources and support to help users effectively use the calculator, interpret results, and address any questions or issues.
• Security and Data Privacy: appropriate security measures to protect user data and ensure data privacy

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