Bank ALM system of the year – SS&C Algorithmics

Steve Good, SS&C Algorithmics
Steve Good, SS&C Algorithmics

SS&C Algorithmics provides an integrated risk framework that helps financial institutions efficiently measure and manage banking book risk, including interest rate, basis, optionality, liquidity, foreign exchange, volatility and credit spread risks.

Algo ALM has an intuitive browser-based application that allows the configuration and orchestration of all asset-liability management (ALM) tasks, such as defining advanced behavioural, planning and rate formulas, as well as scenarios and product-modelling structures. Clients can parameterise ALM models, create sandboxes, undertake ad hoc runs and perform simulations with minimal requirement for support from IT. Calculations are performed using the long-established RiskWatch engine. 

The solution is built on Algo One’s extensive cashflow, simulation and term structure modelling engines and capabilities. For reporting, Algo Workspace Analyzer uses efficient in-memory technology to provide a highly scalable, enterprise environment for aggregating diverse risk data from multiple sources. The business user interface (BUI) – Algo ALM and Liquidity Risk Manager – enables clients to create new simulations, select position and market datasets, create new scenarios and change modelling assumptions. A funds transfer pricing module splits valuation, earnings and cashflows between client rate and internal transfer charges.

Scenarios are generated by Algo Scenario Engine, with the calculation of corresponding distributions using full revaluation under each scenario. In addition to value-at-risk (VAR) and expected shortfall, more advanced measures are available, such as partial, marginal, decomposed and stressed VaR, and using analytical, historical and Monte Carlo methods. More than 300 product types are covered, with the computation of pricing across all asset classes using analytical (closed-form) and/or numerical methods. 

The solution is built on state-of-art technology, with deployment options that include the Hadoop big data framework and Spark data analytics engine, along with advanced batch configuration and analysis tools. A new non-big-data deployment option continues to leverage modern technologies such as Spark for fast and efficient multiprocessing, but allows clients to use traditional relational database management systems for data storage. 

SS&C recently improved the extensibility of Algo ALM, allowing clients to define rate, behavioural and planning assumptions via a user-friendly equation builder, or via RiskScript, Python or Risk++. Models can be uploaded via the BUI. Algo ALM also now leverages technology originally developed for the Fundamental Review of the Trading Book for more efficient scenario simulation by determining which instruments are impacted by a particular scenario and only resimulating those instruments. 

The judges said:

  • SS&C Algorithmics ALM provides rich and comprehensive integrated functionality. It makes good use of technology, both current and older, which is pragmatic for a pluralist and diverse global user base.
  • The company demonstrates that innovation is a continuous process.

Steven Good, global product manager, balance sheet risk management, SS&C Algorithmics, says:

“We are very proud to win this award recognising our next-generation SS&C Algorithmics ALM solution and the benefits our clients are realising. Business user experience is transformed with our browser-based application, and clients benefit from a wide range of product models, behavioural, planning and rate equations, and unrivalled Python extensibility. The highly scalable in-memory technology for reporting allows banks to answer questions the data presents. The solution is built on cutting-edge technology, including Hadoop big data, Spark-boosted 3-Tier and cloud, providing unparalleled performance even on tens of millions of transactions and thousands of scenarios.”

Read more about the Risk Technology Awards 2020 winners

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