ARMS

IRRBB Regulatory Reporting & Planning

As IRRBB touches upon the core of the business, great flexibility is needed to cater for differences in specifications and assumptions.

Lightning Fast ΔEVE, ΔNII, and ΔNFI

The IRRBB Module calculating the regulatory metrics; economic value of equity (ΔEVE), sensitivity of net interest income (ΔNII) and net financial income (ΔNFI), has been designed with flexibility in mind. As the regulator prescribes a set of standardized stress tests to be performed, it does not in detail describe the other model features.

Depending on the size of the reporting institution, various levels of modeling flexibility is needed. The sensitivities for future earnings measures are required to be simulated using both a static and dynamic balance sheet assumption. Support for behavioral options, in loans and deposits can be hard to assess. For sizable institutions, value-at-risk style simulations are to be performed on the sensitivity measures.

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IRRBB Challenges

No two financial institutions are alike. As IRRBB touches upon the very core of the business, great flexibility is needed to cater for differences in contract specifications and business model assumptions. Even for smaller institutions, rolling cash flows into the future under multiple scenarios can be a time consuming task and fill both disk and memory. We have the skills and know-how to compress run-times measured in hours and even days into minutes.

Easy Integration

Using the IRRBB Module in the ARMS risk management platform, a comprehensive and easy-to-use integration to external portfolio systems is provided. Results can be consumed in desktop, drill-down views or exported via api:s to internal database, file or other aggregation software.

Built-in Extensibility

Many institutions appreciate the modular architecture of the ARMS platform. Extending the analysis into market risk, counterparty risk and liquidity management is cost efficient and fast. Instrument and position integration is only done once, making the ARMS platform truly multi-purpose and scalable.

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