In the dynamic landscape of fixed-income securities, the role of generative artificial intelligence (GenAI) has become increasingly prominent. This transformative force is shaping the future of data, analytics, and predictive modeling, presenting both challenges and opportunities for industry leaders.
First, the challenges:
Managing GenAI applications in a responsible and ethical manner requires developers to be mindful of data security, data integrity, respecting intellectual property, and compliance standards, among other considerations. To this end, RiskSpan:
- Maintains control over its data within its AWS instance and shares data with AI models solely for processing requests
- Employs data encryption during transit and at rest to ensure confidentiality and access controls to restrict unauthorized data access within the AWS environment.
- Affirms client ownership of inputs and outputs generated by the AI model’s API, ensuring data integrity and compliance with regulatory requirements.
- Supports common compliance standards, including GDPR and HIPAA.
Standing at the forefront of this evolution within the loans and structured products space, RiskSpan is actively furthering the advancement of three specific GenAI applications aimed at transforming how market participants work and maximizing their efficiency and performance.
1. Modeling Private Credit Transactions
Many financial institutions and legal advisors still spend an extraordinary amount of time reading and extracting relevant information from legal documents that accompany structured private credit transactions.
RiskSpan has partnered with clients to develop a solution to extract key terms from private credit and funding transactions. Trained multimodal AI models are further extended to generate executable code valuations. This code will be fully integrated into RiskSpan’s risk and pricing platform.
The application solves a heretofore intractable problem in which the information necessary to generate accurate cash flows for private credit transactions is spread across multiple documents (a frequent occurrence when terms for individual classes can only be obtained from deal amendments).
Execution code for cash flow generation and valuation utilizes RiskSpan’s validated analytics routines, such as day count handling, payment calculations, discounting, etc.
2. Tape-Cracking 3.0: Making RiskSpan’s Smart Mapper Even Smarter
RiskSpan’s Edge Platform currently uses machine learning techniques as part of its Smart Mapper ETL Tool. When a new portfolio is loaded in a new format, the fuzzy logic that powers the Platform’s recommended mappings gets continually refined based on user activity.
In the coming months, the Platform’s existing ML-driven ETL process will be further refined to leverage the latest GenAI technology.
GenAI lends additional context to the automated mapping process by incorporating an understanding not only of the data in an individual column, but also of surrounding data as well as learned characteristics of the asset class in question. The resulting evolution from simply trying to ensure the headers match up a more holistic understanding of what the data actually is and the meaning it seeks to convey will be a game changer for downstream analysts seeking to make reliable data-driven investment decisions.
RiskSpan made several updates in 2023 to help users automate the end-to-end workflow for loan valuation and surveillance. AI-based data loading combined with the Platform’s loan risk assumptions and flexible data model will enable users to obtain valuation and risk metrics simply by dragging and dropping a loan file into the application.
3. “Insight Support”
Tech support is one of today’s most widely known (and widely experienced) GenAI use cases. Seemingly all-knowing chatbots immediately answer users’ questions, sparing them the inconvenience of having to wait for the next available human agent. Like every other company, RiskSpan is enhancing its traditional tech support processes with GenAI to answer questions faster and and embed user-facing AI help within the Platform itself. But RiskSpan is taking things a step further by also exploring how GenAI can upend and augment its clients’ workflows.
RiskSpan refers to this workflow augmentation as “Insight Support.”
With Insight Support, GenAI evaluates an individual user’s data, dynamically serves up key insights, and automatically completes routine analysis steps without prompting. The resulting application can understand an individual user’s data and recognize what is most important to identify and highlight as part of a loan data analysis workflow.
Insight Support, for example, can leverage insights obtained by the AI-driven “Smarter Mapping” process to identify what specific type of collateral reporting is necessary. It can produce reports that highlight outliers, recognize the typical analytical/valuation run settings a user would want to apply, and then execute the analytical run and summarize the results in management-ready reporting. All in the name of shortening the analysis time needed to evaluate new investment opportunities.
Conclusion
Considered collectively, these three applications are building toward having RiskSpan’s SaaS platform function as a “virtual junior analyst” capable of handling much of the tedious work involved in analyzing loan and structured product investments and freeing up human analysts for higher-order tasks and decision making.
GenAI is the future of data and analytics and is therefore the future of RiskSpan’s Edge Platform. By revolutionizing the way data is analyzed, AI-created and -validated models, dashboards, and sorted data are already allowing experts to redirect their attention away from time-consuming data wrangling tasks and toward more strategic critical thinking. The more complete adoption of fully optimized AI solutions throughout the industry, made possible by a rising generation of “AI-native” data scientists will only accelerate this phenomenon.
RiskSpan’s commitment to pushing the boundaries of innovation in the Loan and Structured Product Space is underscored by its strategic approach to GenAI. While acknowledging the challenges posed by GenAI, RiskSpan remains poised for the future, leveraging its expertise to navigate the evolving landscape. As the industry anticipates the promised benefits of GenAI, RiskSpan’s vision and applications stand as a testament to its role as a thought leader in shaping the future of data analytics.
Stay tuned for more updates on RiskSpan’s innovative solutions, as we continue to lead the way in harnessing the power of GenAI for the benefit of our clients and the industry at large.
