Software Development

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Software Development 2017-01-16T09:00:30+00:00

Why?

As well as developing our own products, we develop custom software on demand. We merge our financial knowledge and our software development expertise to accommodate customer’s particular preferences and expectations.

Among our development team, we count on several top-level software engineers and masters in computer science. After dozens of projects, we have developed a strong background on mature technologies while keeping an eye on the new cutting-edge trends. We dedicate plenty of resources to bring innovation to the finances sector. Over the latest years, we have encouraged the use of technologies related with highly parallel computing, as grids engines o GPU computing (specifically, CUDA).

Our lab proofs have leaded us to experiment with mobile software as well, which brought us to develop BToolKit.

Our experience

Correlation and Dependence Tool

CDT

Correlation and Dependence Tool

The Loss Distribution Approach for modeling operational risk loss relies on the assumption of independence between the magnitude of the losses, and only the frequency of the events may show dependence.

Therefore, an adequate measurement of the dependence is vital for validating the correct modeling of operational risk. Also it is important for avoiding unnecessary increments in capital requirements taken due to conservatism.

We developed a tool for ORX that allowed its members to carefully study the dependence structure underlying its data, and validate the results by comparing their measurements against the ones performed on similar institutions.

Rating

Rating

Rating

Obtaining a precise estimation of the probability of default of a counterparty is key need for financial institutions, not only for adequately granting loans but also for meeting the regulatory requirements for using advanced approaches in the calculation of capital requirements.

We helped Santander, a leading institution worldwide, build their credit rating platform for corporate counterparties. The tool was developed under a client-server approach and allowed the analysts to build multiple models using a highly advanced statistical engine.

Interest Rate and ALM

ALM

Interest Rate and ALM

Liquidity has been proven to be a major risk. A precise asset liability management, incorporating a wide range of reliable interest rate scenarios, is vital for holding back liquidity threats.

We developed a set of Matlab routines for Banesto which helped them address this problem. Cash flows at risk could be estimated under a massive set of interest rate scenarios, obtained from a Rebonato-type model of historical simulation.

Parallel Computing – CUDA

CUDA

Parallel Computing – CUDA

With finance models becoming more and more computationally intense, Parallel Computing has gained momentum as a solution for these complex problems. Our experience spans on multi-core solutions and GPGPU solutions (general-purpose computing on GPUs).

Our Credit Analytic Tool incorporates a CUDA Monte Carlo engine which has proved to overpass other standard procedures. We have also performed several studies for third-parties to analyze the improvement using CUDA. For instance, on your left you can see the improvement when pricing caps, swaps and swaptions using a LMM model.

MatRisk

MatRisk

MatRisk

MatRisk is a simple market risk tool for computing the value at risk and the expected shortfall for different time horizons.
The calculation of the measures is performed using a parametric approach.

The application covers the Gaussian approach, the Gaussian mixture distribution and the use of extreme value theory for modeling the excesses over threshold.