Our Solutions
Portfolio Analytics
AlchemyJ integrates data from diverse sources through flexible interfaces, ensuring seamless and accurate data import.
After normalizing the data for consistency, AlchemyJ applies advanced analytics algorithms, including asset allocation, risk assessment, and return evaluation. Users can interactively explore the data, adjusting it across dimensions and durations to gain deeper insights.
Reporting
AlchemyJ reporting engine is a powerful tool designed for generating financial reports and documents. It features an extensive data dictionary containing a wide range of financial data items.
The engine offers multiple report templates, including options for consolidated statements and other essential financial documents, which streamline the reporting process.
Order Processing
AlchemyJ provides a framework for order processing across various asset classes. Its process model allows it to accommodate the unique requirements of each asset class at different stages of the order processing.
These stages include validation, where it ensures the order meets necessary criteria; pre-trade checks, which confirm compliance with regulatory and risk parameters; enrichment, where additional data is generated; and order execution, where the trade is completed efficiently.
Cost and Fee Analysis
AlchemyJ performs an in-depth analysis of the costs, fees, and commissions associated with each financial transaction. Such analysis depends on numerous factors like transaction type, market conditions, and client agreements.
AlchemyJ employs a hybrid approach to take on this headwind. It integrates multiple methods, including a rule engine, a calculation matrix and advanced models to capture intricate relationships and scenarios.
Finance and GL
AlchemyJ generates General Ledger (GL) entries for accounting systems, enabling financial institutions to maintain an up-to-date view of their key financial positions.
It achieves this through a comprehensive and flexible booking rule model that defines how transactions should be recorded under various scenarios, ensuring accuracy and consistency across all entries.
Risk Analytics
AlchemyJ evaluates the valuation of collateral portfolios with sophisticated models like Lombard lending. It incorporates a multi-level, multi-dimensional haircut approach. Then it maps these valuations against the credit utilization to determine credit risk at different levels.
By analyzing how much credit is being used, it provides a comprehensive view of credit exposure, identifying potential risks and helping financial institutions make informed decisions on risk management.
