Tuesday, November 29, 2016

Risk Model Optimization and Traceability for Solvency II

Solvency II and Basel III, the new standards for insurance and bank regulations, codify and unify capital, data management, and disclosure requirements for insurers and banks in order to protect companies and consumers from risk.

More specifically, with Solvency II the effect of every insurance contract capital market relation, optionally and risk source has to be modeled and measured. The goal is to ensure insurances have enough equity to cope with any forecasted risk. Considering the amount of heterogeneous assets and liabilities owned by an insurance company, algorithms such as Monte Carlo are suitable to estimate the result of different scenarios with a given accuracy and get metrics such as VaR (value at risk).

A typical process using a Monte Carlo algorithm regularly involves multiple steps:

  1. Defining a model for each asset, liability, economic scenarios, etc. using tools such as Quantlib, Bloomberg solution, Wall Street system, Apollo, etc.
  2. Create scenarios based on these models (It can easily go above 2 millions scenarios)
  3. Calculate the result of each scenario
  4. Merge the results
  5. Calculate metadata on merged results
  6. Publish results for BI tools or other tools

To perform efficiently this process which can take more than 6 hours on more than 500 nodes each step has different requirements. Step 2 and 3 require a lot of CPU in order to quickly create each scenarios based on the predefined models and calculate the result for each scenario. Step 4 requires a lot of RAM (~100Gb) to efficiently merge the results from the different sources. Step 5 will create some post calculation based on all the results, it will require a mix of CPU and RAM. Step 6 might require a big amount of RAM depending on the speed required for BI tools and the shared results selected.

Finally, in parallel to this process, every transaction and calcul have to be recorded for traceability purposes.

To support this complex requirements and efficiently provide business insight, a few software specifications have been detailed below: Resource management to ensure each server, instance, VM, etc. is efficiently used according to each step needs

  • Advanced error management to ensure an error will not break the whole process
  • Security to ensure the process is kept away from any disruption and that data is kept in a safe environment
  • Logs for traceability
  • Prioritization to ensure critical jobs are completed in priority
  • Public cloud abilities to increase the number of nodes (e.g. 10,000 nodes)
To conclude, ProActive from ActiveEon offers an open source solution allowing insurance companies to leverage their algorithms with an efficient utilization of their IT infrastructure. The software will ensure traceability, reliable and fast execution while meeting the specifications mentioned above and the Solvency II requirements.

A White Paper is also available to give a broader view of the effect of Basel III and Solvency II on the IT infrastructure.

Finally, in the same way Solvency II is an opportunity for insurance companies to improve their financial health, the Payment Service Directive 2 (PSD2) is also an opportunity for Banks to create a broader and healthy ecosystems. ProActive being fully open allows more communication between apps and services and securely offers a single access point for different users.

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