Credit Risk

Credit risk analytics has become increasingly complex. New regulatory requirements are piling on costs as a spike in inflation coupled with rising interest rates adds to the challenge of managing credit risk. Credit risk managers need minute-by-minute flexibility in their ability to analyze markets – to filter, slice and dice data and create ‘What-If’ scenarios on-the-fly to assess the impact of any change in a the credit risk portfolio.

CVA PFE Aggregation and Analytics – BCBS 325

With Atoti+ you can precisely hedge CVA incrementally or recalculate it on-the-fly with up-to-date sensitivities. Analyze CVA, PFE, or EPE down to the individual trade level and understand significant deviations at any point in time. Atoti+ consumes market data and other trade attributes and exposes multiple counterparty credit risk related parameters such as CSA terms and collateral and netting sets for interactive analysis. To determine the cheapest CVA counterparty to deal with or simulate the impact of a rating change or credit spread using ‘What-If’ analysis has never been so easy to facilitate the decision making process.

Danske bank – Case Study

Credit Risk with Limit Monitoring

Maintain a watchful eye over your credit portfolio. Examine the impact of a change in a counterparty ratings downgrade. Do it at scale across hierarchies (country of risk, counterparty, organization) or on a few trades or one book. Create scenarios to test sharp swings in markets that result in counterparty default. Swap out certain long-dated positions (such as illiquid instruments) in trading portfolios for higher quality assets to test issuer credit risk. Check credit limits incrementally on new trades or positions as they update.


Atoti+ allows you to slice and dice data and perform dense calculations that feed into the regulatory requirements. Consolidate data from different systems into one unified platform for exploitation and further analysis. Simplify complex data gathering across asset classes, netting and hedging sets, down to trade level details. Run simulations such as swapping one set of margined trades out for unmargined trades and view the impact on the capital charge instantly. Swiftly create meaningful views of your data and report findings to supervisors on interactive dashboards.

ActiveViam’s SA-CCR Accelerator

ActiveViam’s SA-CVA & BA-CVA Accelerator

Counterparty Credit Risk – BCBS 507

Centralize and manage counterparty credit risk. Atoti+ lets you compute counterparty credit risk exposure and CVA on the fly. With a few swift clicks you can examine the impact of a change in an underlying credit spread. Swap out one counterparty for another and view the impact across any dimension, country or product type. Run exposure at default scenarios to determine whether increased margin or a change in CSA terms is needed. Hypothetically close out netting sets to determine a precise net loss or gain.


For IFRS9, the computation logic of the ECL (Expected Credit Loss) is not particularly diffcult, however, the analysis of the variation and change of credit worthiness can be very complex, require twelve month of historical data and the role of the risk analyst is key to assess if a given contract should be in stage 1, 2 or 3, according to the IFRS9 regulation. This analysis require a lot of attributes (days passed dues, rating change,…) and this is the reason why it is so important to be able to ddrill down to the most granular level on the dataset. Working on pre-aggregated data on IFRS9 is not an option anymore.

ActiveViam for IFRS 9