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  • Home Finance Barclays Pushing into AI to Manage Risk

    Barclays Pushing into AI to Manage Risk

    Recently, Barclays announced its collaboration with Simudyne, which is a graduate of the Barclays Accelerator program.

    The partnership is spearheaded by the need to evaluate new risk mitigation solutions.

    Simudyne is known for allowing banks to develop computer models that simulate millions of possible future scenarios, enabling them to assess how individual aspects will not only perform but also interact with each other in diverse situations.

    Simudyne runs complex simulation tests to minimize the risk exposure of entities. In fact, Barclays is currently creating simulations through Simudyne’s toolkit, which it refers to as agent-based modeling.

    The simulation tech allows the automated recognition of a considerable event in quantities analysis, which will enable entities to simulate additional complex scenarios.

    Furthermore, the financial institution explained in its announcement that agent-based modeling is different from regression-based models, which depend on historical behavior data analysis.

    READ MORE: 10 Applications of Machine Learning in Finance

    READ MORE: Deloitte Says that 19% of Financial Services are Using AI

    According to Justin Lyon, the CEO of Simudyne, simulations that are based on agent-based modeling methods enable banks to account for the capabilities of agents including traders, firms, and people among others.

    Doing so allows them to optimize, shift from rationality or take advantage of their surroundings.

    He went on to say that the models can be utilized in seeing how a system can reconfigure itself after a policy change.

    Lyon emphasized that the platform was ideal for exploring tail events including trade wars or even other unforeseen policy results. C.S Venkatakrishnan, the chief risk officer of Barclays Group, said that through creating agent-based models, the financial institution hopes to identify and prepare for risks emerging from direct and contingent, dynamic and large, counter-party exposures.

    In turn, he said that this effort would allow the creation of a more stable and robust bank for its customers, shareholders, and clients.

    In another statement, Justin Lyon said that agent-based modeling has brought about several opportunities for banking institutions to tests their decisions before investing their vast resources or even taking any form of action into the real world.

    He further stated that Barclays’ decision to utilize simulation serves as a competitive advantage that expresses the financial institution’s dedication to innovation.

    According to Justin Lyon’s statements, Simudyne is working in collaboration with Barclays’ Center of Excellence to explore more functionalities of the risk management technology.

    READ MORE: Top 25 AI Software for the Banking Industry

    What’s more, Andy Haldane, the Bank of England’s chief economist, highlighted the capacity of agent-based models to address advanced macroeconomic queries, especially those where heuristics, heterogeneity, and networks play a fundamental role.

    Simudyne took part in the Barclays’ Accelerator program, which was hosted in London, last year.

    According to the company’s CEO, Lyon, Simudyne’s software allows banks to recreate the aspects that are important to the financial marketplace.

    He added that situations such as the spread of contagion or the collapse of a bank are the outcomes of multiple aspects that lead to a tipping point.

    When it comes to lending, Simudyne’s software enables banking institutions to create simulations based on various inputs including how people behave as borrowers, how they spend their money and household incomes.

    Currently, a team at Barclays, for instance, is working on ways of modeling a fraudster’s actions.

    Source FT

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    KC Cheung
    KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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