Case Studies | Fund Administrators
How we help our clients grow their business
Category
Challenge
Managing private SPVs in inventory finance and trade receivables required tracking complex cash flow transformations across multiple asset types. Inventory is purchased, sold, converted into receivables, and repaid under different contractual structures – often across fragmented counterparties and reporting standards.
Solution
Cardo AI implemented a structure-aware cash flow tracking framework capable of following assets from inventory purchase through receivable conversion and final repayment. The platform automated reconciliation of realized cash flows against contractual repayment schedules and liability obligations, while embedding contract-driven compliance logic directly into workflows. Counterparty data was standardized into a single environment, enabling consistent reporting and centralized oversight across multiple private SPVs.
Outcome
- Full end-to-end visibility from inventory sale to receivable repayment
- Automated reconciliation aligned with contractual waterfalls
- Improved investor transparency with real-time reporting
- Optimized liquidity management across SPVs
- Scalable framework supporting additional esoteric structures
Challenge
A leading corporate trustee managed rising deal volumes and increasingly complex structures that had become a significant operational bottleneck. The team depended on fragmented, inconsistent inputs from various issuers and servicers, which made it difficult to validate data quality before downstream processing.
Solution
Cardo AI supported the trustee with a modern data and transaction operations layer that standardized incoming information, automated core validations, and improved control over recurring deal workflows. This enabled the trustee team to reduce friction in high-volume recurring processes while improving transparency across the entire deal lifecycle
Outcome
- Strengthened stakeholder trust with audit-ready transparency
- Shortened reporting timelines by reducing operational friction
- Removed reconciliation gaps through standardized data
- Handled higher deal volumes with greater precision and speed
Challenge
Identifying early deterioration signals and modeling loan evolution under varying economic scenarios required deeper data integration and predictive capability.
Solution
Cardo AI deployed machine learning models powered by servicer data, partner bank data, European securitization datasets, and alternative data sources. The platform analyzed historical payment behavior, borrower characteristics, and macroeconomic indicators to predict deterioration probabilities, simulate loan evolution, and evaluate management strategies such as restructurings, write-offs, or retention. Scenario engines enabled forward-looking return modeling under multiple economic conditions.
Outcome
- Proactive identification of at-risk loans before delinquency
- Earlier mitigation actions reducing portfolio deterioration
- Data-driven workout strategy evaluation
- More accurate expected return forecasting under multiple scenarios
- Enhanced portfolio health through predictive classification