SS&C Algorithmics provides leading risk analytic products and services for the financial services industry worldwide; including Balance Sheet Risk Management (ALM and Liquidity Risk), X-Value Adjustment (xVA), Fundamental Review of the Trading Book (FRTB), Standardized Approach for Counterparty Credit Risk (SA-CCR), Current Expected Credit Losses (CECL) and Targeted Review of Internal Models (TRIM).
Algorithmics fundamentally redeveloped its Balance Sheet Risk Management solution three years ago, to address the increasing demands of regulators and our customers with an innovative, intuitive and high-performance solution. This built upon years of experience of working with our customers and led to the first ALM and Liquidity Risk Management solution with the option of Big Data. The use of modern technologies allows clients the ability to run data with full granularity, even with tens of millions of records supporting supervisory and business needs.
Clients were also provided with a completely redesigned user interface and architecture, paired with a modern workflow, extensive instrument coverage and complemented by the high-performance, in-memory reporting solution Algo Workspace Analyzer (AWA). We have received very positive feedback for the ALM and Liquidity Risk Management solution from existing and new clients.
During 2019, Algorithmics completed a number of successful implementations of our Balance Sheet Risk Management solution for clients across the globe. A European client went live on Workspace Analyzer for Liquidity Risk purposes, which improved both reporting speed and business user interactivity. In Brazil, another client went live on ALM and Funds Transfer Pricing and achieved increased flexibility, robustness, and performance for their processes. A Chinese client in Asia went live for Interest Rate Risk in the Banking Book (IRRBB) supporting enhancements needed for BCBS 368 regulation, generating and reporting upon measures including interest rate gaps, the present value of gaps for Economic Value of Equity (EVE) and Net Interest Income (NII) under both the regulatory prescribed 6 scenarios and the bank’s internal risk measures.
In addition to the clients who completed implementations, there are a number of clients who are currently in the process of implementing the Balance Sheet Risk Management solution.
A European client with total assets in excess of €200 billion has started using the solution to model its banking book at full granular level for Economic Value of Equity (EVE) analysis with approximately 20 million transactions, calculation of valuation, sensitivities, and at pooled level for Value-at-Risk calculations. Using the Algorithmics ALM and Liquidity Risk Manager interface, business users can create new simulations, select position and market datasets, create new scenarios and change modeling assumptions. The Funds Transfer Pricing module is used to split valuation, earnings and cash flows between client rate and internal transfer charges.
Another client, a European technology service provider, is using Algorithmics Balance Sheet Risk Management to address regulatory needs of financial institutions of over 100+ regional and community banks with aggregate total assets greater than €100 billion. The project entails implementing all regulatory needs for CRD IV/V related to Interest Rate Risk in the Banking Book (IRRBB), Liquidity Coverage Ratio (LCR), Net Stable Funding Ratio (NSFR) and interest rate risk stress testing.
A leading retail financial institution in Asia is implementing the Algorithmics Balance Sheet Risk Management solution to address Interest Rate Risk in the Banking Book (IRRBB) and Liquidity Risk for both internal risk management and regulatory requirements purposes. The project entails the generation of all measures for Basel III liquidity risk reporting including LCR, NSFR, and Additional Liquidity Monitoring Metrics (ALMM), as well as cash flows for various internal liquidity gap reporting needs. With regards to IRRBB, implementation of Algo ALM encompasses measurement of the different types of IRRBB, including Gap Risk, Basis Risk, and Option Risk, both from Value and Earnings points of view.
Other companies are just beginning their journeys with Algorithmics Balance Sheet Risk Management. A European financial institution selected Algorithmics for the flexibility to sandbox, prototype, and create complex behavioral and planning assumptions with less IT intervention. Another client, a German Direct Bank, chose Algorithmics to address Interest Rate Risk in the Banking Book (IRRBB) and regulatory cash-flow analysis. The client selected Algorithmics for its breadth of modeling functionality and, particularly, the ability to handle complex behavioral features, including sophisticated option-based modeling for amortizing callable loans.
For more information about how Algorithmics can help you address current and future challenges, download our "SS&C Algorithmics Balance Sheet Risk Management" brochure.
Commercial Lending, Regulation