CaixaBank tests machine learning algorithms for risk classification model

Tuesday 21 April 2020 13:22 CET | News

CaixaBank, a Spain-based financial services company, has used quantum computing technology to develop a machine learning algorithm to calculate customer credit risk.

It is part of its experimental application of quantum computing to its financial products and services.

In 2019, the bank reported on its ongoing tests of IBM’s Framework Opensource Qiskit, which is being used to implement a quantum computing algorithm that will assess the financial risks involved with a mortgage portfolio and treasury bills portfolio. These have been created for this initiative and use real financial data.

According to Crowdfund Insider, the institution had been using a hybrid computing framework, which leverages both quantum computing and conventional (binary) computing in the different stages of the calculation process that is used to classify customers’ credit risk profiles.

CaixaBank’s software does this by using a public data set that corresponds to 1.000 ‘artificial’ customers, who have a profile that’s similar to actual clients, however, with information adjusted specifically for these tests. The complete results have not yet been released.

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Keywords: CaixaBank, Spain, financial, algorithms, credit, Quantum, computing, technology, machine learning, bank, IBM, mortgage
Categories: Banking & Fintech | Digital Identity, Security & Online Fraud
Countries: Spain
This article is part of category

Banking & Fintech