Introduction
Artificial Intelligence is revolutionizing the alternative investment industry by enhancing decision-making, improving efficiency, and uncovering new opportunities. AI-driven tools help investors analyze vast amounts of unstructured data to gain insights and make informed investment choices. Additionally, AI supports risk management and fraud detection, ensuring more secure and strategic investment practices. As the alternative investment landscape evolves, the following list of AI use cases is increasingly becoming a key driver of innovation and competitive advantage.
Use Cases
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1. Improve algorithmic trading and investment strategies
Banks and financial firms, such as hedge funds, are utilizing AI to refine algorithmic trading and investment strategies. Additionally, they employ AI to optimize their clients’ financial portfolios, ensuring better returns and risk management.
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2. Collect external data to assess market sentiments and key performance indicators
AI systems, especially large language models (LLMs) and Generative Pre-trained Transformers (GPTs) are employed to efficiently collect external data to gauge market sentiments and key performance indicators of individual companies. This real-time intelligence aids financial institutions in balancing their risk-reward systems more effectively, leading to more informed decision-making.
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3. Develop Decision Support Systems
AI systems are deployed to develop Decision Support Systems in areas like capital markets, brokerage, retirement, and wealth management. These systems predict ratings for small and medium-sized companies that analysts can’t cover due to time constraints and gather data from news media, 10Ks, 10Qs, equity research, and fixed income documents, providing comprehensive insights for better decision-making.
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4. Update equity research models with new data
AI can automatically update equity research models with new data from quarterly or annual earnings reports, eliminating the need for junior analysts to manually input this data. This reduces the risk of errors and significantly speeds up the process, allowing analysts to focus on more strategic tasks. For more information, visit www.scryai.com/Collatio.
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5. Create a unified and reliable source of information
AI can harmonize various financial databases, such as Bloomberg, Factset, CapitalIQ, Lexis Nexis, and DnB, along with articles, to create a unified and reliable source of information. This ensures consistency and accuracy across different data sources.
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6. Artificial Intelligence and Stock Trading
AI can automatically reconcile stock trades and related investments, which often come in diverse formats such as emails, Excel spreadsheets, and tables. This automation reduces the labor-intensive manual reconciliation process, saving time and minimizing errors.
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7. Investment decision support
AI-powered recommendation systems can provide insights on which alternative investment managers should be allocated funds and the appropriate amounts. This helps in making informed investment decisions and optimizing fund distribution.
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8. De-duplicate customer data
AI can de-duplicate data concerning customers, transactions, and recipients (such as wire transactions) to establish a single source of truth. This process aids in detecting money laundering activities and ensures that customers are not targeted with multiple marketing efforts.
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9. Analyze and interpret corporate actions
AI can analyze and interpret corporate actions and their significance, offering valuable insights to investment bankers and equity research analysts. Additionally, AI-driven decision support systems can predict potential corporate actions, aiding in strategic planning and investment decisions.
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10. Create a Single Source of Truth for regulatory requirements
AI and Data Science can be employed to create a Single Source of Truth for regulatory requirements such as CCAR, BCBS235, and other governmental regulations. This ensures compliance and simplifies regulatory reporting processes.
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11. Locate and understand information in contracts and other unstructured PDF documents
Banks often spend considerable time searching for and summarizing internal information and documents, which reduces the time they can spend with clients. Generative AI, particularly GPTs and LLMs, can assist bank employees in efficiently locating and understanding information in contracts and other unstructured PDF documents. For example, generative AI can help bank analysts accelerate report generation by summarizing extensive economic data and statistics from around the world. It can also aid corporate bankers in preparing for customer meetings by creating detailed and engaging pitch-books and presentation materials, enhancing client interactions.
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12. Assist investment analysts
To fully comprehend global markets and associated risks, investment firms must analyze a wide range of company filings, transcripts, reports, and complex data in multiple formats, and efficiently query this data to enhance their knowledge bases. In capital markets, generative AI tools can function as research assistants for investment analysts, aiding them in sifting through millions of event transcripts (such as earnings calls), company filings (like 10Ks/10Qs), consensus estimates, macroeconomic reports, regulatory filings, and other sources. These tools can quickly and intelligently identify and summarize key information, streamlining the research process. Watch this video to learn how to extract and summarize valuable information from complex documents, such as 10-K forms, research papers, third-party news services, and financial reports, with just a click of a button.
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13. Assist developers and automate code changes
In the alternative investment industry, new regulations are introduced globally every year, and existing rules frequently change, necessitating extensive manual or repetitive work to interpret new requirements and ensure compliance. Developers need to quickly grasp the regulatory or business changes that necessitate code modifications, assist in automating and cross-checking coding changes against a code repository, and provide documentation. Generative AI can offer developers context about regulatory or business changes by providing summarized answers with links to specific locations containing the relevant information. It can also assist in automating coding changes, with human oversight, helping to cross-check code against a code repository and providing necessary documentation.
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14. Anti-money laundering risk scoring
Apply anti-money laundering risk scoring using customer data, including past transactions and social media activity. Conduct automated data collection and cross-checking with databases related to terrorism financing and other financial crimes prevention, ensuring comprehensive risk assessment and compliance.
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15. Chatbots to aid clients
Support wealth management and investment banking by utilizing chatbots or “robo-advisors” to aid clients in their investment decision-making process. These AI-driven tools can suggest the most suitable products based on the client’s profile and objectives, enhancing personalized financial advice and service.
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16. Analyze and predict trends and sentiments
Collect real-time data from financial markets to analyze and predict trends and sentiments. This enables financial institutions to respond to various market research requests and make informed decisions based on current market conditions.
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17. Optimize portfolio management
Conduct portfolio analysis and monitor clients’ asset selection profiles and available pricing products. Optimize portfolio management and personalize it to enhance clients’ risk and returns. Prepare tax returns and file statutory forms, such as Note S and C documents. Reconcile securities across different data sources to ensure accuracy and consistency.
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18. Monitor daily portfolios
Check daily portfolios and notify the portfolio manager or client if there are any variances from preset recommendations and preferences. Continuously adjust client portfolios using reinforcement learning-based trading algorithms. Perform data entry and analysis, restructuring tools, securities, and trade reporting, and transfer the information to authorities for compliance and reporting purposes.