Whether it’s making payments faster, more secure, or more personalized, AI is reshaping the consumer payments landscape. AI applications could include payment fraud detection and prevention, tailored payment solutions, customer support, biometric authentication, enhanced security, and accelerated payment processing and clearing.

Offering a new level of convenience, efficiency, and personalization. From simple account balance checks to complex personalized financial advice and other tailored financial products and services, AI chatbots can also enable seamless onboarding and detect and prevent fraud by analyzing customer behavior, verify customer identity and authenticate transactions.

AI enhances customer experiences by providing tailored advice, proactive alerts, customized financial advice, enhanced customer support and innovative financial products and services.

By leveraging advanced algorithms and machine learning techniques, AI-powered tools can provide tailored financial advice, enabling individuals to make informed decisions about their financial situation. AI provides data-driven insights, personalized recommendations, proactive financial guidance and continuous learning and adaptation.

AI enables financial institutions to deliver highly personalized, efficient, and secure services to their high-net-worth clients. It can facilitate personalized wealth management, including investment advice, enhanced client experience, risk management, fraud prevention and regulatory compliance.

AI is a powerful tool in the fight against financial fraud in consumer banking. By analyzing vast amounts of data in real-time, AI algorithms can identify suspicious patterns and prevent fraudulent activities. It provides real-time transaction monitoring, behavioral biometrics, network analysis, predictive analytics and enhanced customer authentication.

By analyzing vast amounts of data and identifying complex patterns, AI-powered tools can provide more accurate and efficient credit decisions. AI provides enhanced credit scoring, fraud detection, and assesses the risk associated with lending to specific borrowers. AI can also analyze customer behavior and preferences to provide tailored loan products and terms.

By leveraging advanced algorithms and machine learning techniques, AI can identify and address potential risks proactively. Key applications include fraud detection and prevention, credit risk assessment, operational risk management and market risk management.

By integrating AI into their products and services, fintech companies are transforming the way we bank, making it more efficient, accessible, and personalized. Collaborations between fintechs and traditional banks are becoming increasingly common, as they work together to leverage the power of AI to provide a more personalized, efficient, and secure experience. Award submissions will be accepted from both banks and non-banks.

Covering any AI-based trade finance platforms and solutions offered by both banks and non-banks to help streamline operations, reduce costs, mitigate risks, and improve customer satisfaction.

To include AI solutions bringing new levels of automation, speed, and accuracy in managing supply chain finance operations.

From algorithmic trading to predictive analytics to include ways that AI is assisting banks, hedge funds, and individual traders to streamline operations, reduce costs, mitigate risks, and improve bottom lines.

To include AI-powered data analysis, risk assessment, and impact measurement solutions that enable better assessment of ESG factors, identify sustainable investment opportunities, and mitigate risks associated with climate change and social inequality.

Covering solutions where AI is reshaping the payments and cash management landscape, such as improvements to payment processing, fraud detection, cash forecasting and optimization, real-time payments, and reconciliation.

To include ways that AI is enabling better trade confirmation and settlement, streamline operations, reduce costs, mitigate risks, and improve client satisfaction.

From AI-powered credit scoring models, machine learning algorithms that analyze market data, predictive analytics and stress testing tools and other ways AI is enhancing risk management capabilities.

Through advanced algorithms and machine learning techniques, AI can effectively detect and prevent fraudulent activities, safeguarding financial institutions and their clients.

AI is enabling financial institutions to offer more innovative, efficient, and personalized services. To include submissions from banks and non-banks.

By leveraging advanced algorithms and machine learning techniques, AI can enhance decision-making, improve risk management, and optimize investment strategies. AI provides enhanced due diligence, predictive analytics and stress testing for advanced risk management. AI can provide data-driven investment insights and extract insights from news articles, research reports, and other textual data. Algorithmic trading can be employed for both high-frequency trading and statistical arbitrage.

AI helps make M&A deals faster, smarter, and more efficient. AI applications enable enhanced due diligence, improved deal sourcing, target identification and streamlined deal execution.

AI is a powerful tool for modern markets as it allows traders to gain a competitive edge, improve decision-making, and enhance overall performance. Key AI applications include HFT, statistical arbitrage, mean reversion and momentum trading, while predictive analytics, automated trade execution and personalized trading strategies can improve efficiency and portfolio optimization.

AI enables financial institutions to make more informed decisions, streamline operations, and mitigate risks. Document analysis and data room analysis lead to enhanced due diligence. Credit risk modeling and market risk assessment improve overall risk assessment. Automated trade execution and smart contract technology help optimize deal execution. AI also aids regulatory compliance and provides advanced analytics and insights.

By leveraging AI, investment banks can improve the accuracy of valuations, enhance deal execution, and mitigate risks. AI can quickly analyze vast amounts of legal, financial, and operational documents to identify key information and potential risks and efficiently sift through virtual data rooms, identifying crucial information and potential red flags. AI is used for predictive analytics, such as market trend analysis and valuation modeling. AI can monitor regulatory compliance checks, reduce the risk of errors and penalties, and monitor regulatory changes and their impact on IPOs and equity capital markets in real time.

AI-powered credit scoring models, real time analysis of market data and monitoring of operational processes to identify potential weaknesses and inefficiencies, alongside improved fraud detection and enhanced stress detection help investment banks to strengthen their risk management capabilities and protect client interests.

By leveraging advanced algorithms and machine learning techniques, AI can effectively detect and prevent fraudulent activities, safeguarding financial institutions and their clients. Key AI applications include real-time transaction monitoring, behavioral biometrics, network analysis, predictive analytics and AI-powered authentication methods, which help investment banks strengthen their security posture, protect their clients, and maintain their reputation.

AI provides enhanced due diligence, automated trade execution, and real-time trade confirmation and settlement, automated compliance checks, real-time regulatory monitoring, personalized client services and predictive analytics to help securities firms to streamline operations, enhance risk management, and improve client service.

Fintech companies are playing a crucial role in driving innovation in investment banking by providing cutting-edge AI solutions. These solutions can be integrated into traditional investment banking processes to improve efficiency, accuracy, and decision-making. Key areas where fintechs are contributing include AI-powered data analytics, cloud-based solutions and cybersecurity. Award submissions will be accepted from both banks and non-banks.