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Risk Modeling Solutions

Conning is using Julia in large scale Monte Carlo simulations for insurance risk assessment solutions

Conning is a hundred year old global asset management firm managing more than half a trillion dollars in financial assets for the insurance industry. Conning’s Economic Scenario Generator (ESG) generates the financial and macroeconomic variables that underpin risk modeling.

Conning’s platform undertakes very large scale multi-period Monte Carlo simulations involving a tremendous number of variables and periodicity varying from a single day to 50 years, which can amount to 4 million calculations per second per core. Languages like C are not an option because of the sheer complexity of the models and the amount of time it would take to code.

The legacy solution used interpreted array-based K, but as the size of data sets and complexity of models is growing fast, K was found to be inadequate for their needs.

Conning chose Julia for its:

  • Simpler, readable, easy to maintain code
  • High performance - Julia is 4 to 10x faster than K for the same functions
  • High productivity
  • Very accessible for new users and quants
  • Similarities with C, Python, MATLAB
  • Full suite of high performance array data structures and methods
  • High performance scalar code
  • Distributed parallel computing
  • Scalability
  • Cost effectiveness

Conning has re-written its entire application in Julia and has been running it in production since June 2016.