TAO Solutions - AI Use Cases

TAO Solutions believes Artificial Intelligence (“AI”)has a number of use cases withinthe administration of Structured Finance programs (this includes Asset-Backed Commercial Paper Conduits, Bank Funded Securitization Warehousing, ABS, MBS and Covered Bonds administration activities). As the market evolves, TAO Solutions’ ability to introduce a vendor driven, value-accretive automated software solution will provide our customers with distinct competitive advantages that will displace both internal solutions and legacy systems. Here are some examples of AI use cases in structured finance:

• Virtual Assistants and Chatbots: AI-powered virtual assistants like Siri, Alexa, and chatbots are used to provide customer support, answer queries, and assist with various tasks, improving user experience and efficiency.

• Personalized Learning: AI-driven adaptive learning platforms tailor training for end users, improving learning outcomes.

• Pool Selection / Portfolio Optimization: AI algorithms are used for pool selection based upon unbiased eligibility criteria / portfolio parameters, credit enhancement requirements, prior pool cuts and market trends that will identify the best combination of assets to achieve specific risk and return objectives.

• Market Sentiment / Preferred Funding Options: AI-powered sentiment analysis can help issuers gauge market sentiment, potential risks, and opportunities, impacting structured finance strategies.

• Natural Language Processing (NLP) for Document Analysis and Transaction Modelling: NLP algorithms can extract valuable insights from structured finance documents, such as prospectuses, legal contracts, and regulatory filings.

• Automated Reporting: AI can automate the generation of reports for stakeholders, providing real-time insights and reducing manual effort.

• Robotic Process Automation (RPA): RPA can be used to automate repetitive tasks within the structured finance process, such as data entry, reconciliation, and reporting.

• Regulatory Compliance: AI can assist in monitoring compliance with complex regulatory requirements in structured finance transactions, helping to reduce compliance-related risks.

• Cash Flow Predictions: AI can forecast cash flows for structured financial products, enabling better risk management and decision-making.

• Asset Pricing and Valuation: AI can assist in determining the fair value of assets and structured products by analyzing historical data, market trends, and relevant factors influencing asset prices.

• Stress Testing and Scenario Analysis: AI can be employed to conduct stress tests and scenario analysis on structured finance portfolios, assessing their resilience under adverse conditions.

• Fraud Detection: AI helps identify patterns of fraudulent activities in financial transactions safeguarding against financial losses.

• Risk Assessment: AI can analyze vast amounts of data to assess the credit risk of portfolio’s of data.



• Predictive Analytics for Loan Defaults: AI models can predict the likelihood of loan defaults, enabling proactive risk mitigation measures.