Banks Struggle to Manage Technical Debt When Dealing with AI, Data Science

Managing technical debt, in the development of new AI models, can be expensive and can lead to significant cost overages throughout the project. This is primarily driven by the need for AI models to scale and adjust to different market conditions, liquidity and volatility situations, where vastly different data volumes and modelling approaches are required. …

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Using machine learning to explain extreme price moves

Data is abundant, not only in volume, but also in the number of sources it is derived from, the frequency at which it is updated, and the variety of formats it may take. Time spent sorting through that data, however, can keep businesses from generating actionable information at pace. Ask us how we can help…

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Finding market liquidity insights with data science

Congratulations to Joel Sebold and Refinitiv Labs for unlocking further potential from data science with their equity market liquidity discovery project. By combining the computer power of machine learning with creative visualizations, data science will take its rightful place in analytics space for capital markets. For fixed income market participants, explore Overbond’s suite of analytics…

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Apple, Oracle Dump Bonds and Create $300 Billion Hole in Market

As U.S. tax cuts prompt Apple Inc. and other tech companies to bring home their overseas cash hoards, it’s leaving a void in the market for short-term corporate bonds, where those firms had invested much of the money. That’s now making it more expensive for other companies to borrow. Source: Bloomberg   Once the biggest buyers of short-dated corporate…

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