Utilising alternative data to develop a machine learning-based artificial intelligence platform for real-time KPI tracking of UK companies for fundamental investors

利用另类数据开发基于机器学习的人工智能平台，为基本面投资者实时跟踪英国公司的 KPI

• 批准号: 10057969
• 金额: $ 24.81万
• 依托单位: OXFORD DATA PLAN LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10057969
• 关键词: Utilising; alternative; data; develop; machine

Our founder and CEO Josef Schmalfuss is a recognised industry leader in utilising Alternative Data for Fundamental Investing. Having spent seven years as a partner at a fundamental investment fund as a buyer/in-house creator of alternative data, he decided that innovation is required to transform current processes of data-insight generation for investment decision-making.Key performance indicators(KPIs) are a hugely important source to indicate the overall performance of companies. Currently, investment decision-making is predominantly based on backwards-looking reported data comprising quarterly or annual reports or financial statements. However, there are many other areas that indicate a company's worthiness for investment. We are utilising alternative data for this purpose, to generate KPI trackers that incorporate data such as transaction data, app downloads, social media and mobility data. Our solutions are based on the idea that the investment potential of a company is based on more than just how it looks on an old piece of paper.KP-Intel is a game-changing platform for the autonomous generation of daily data-driven KPI estimations, utilising real-time data, of **every** mid-size/larger UK company and a significant proportion of small-to-medium-sized enterprises. Currently, to generate alternative data insights, companies and investors must seek the input of a data scientist in the process, which can be expensive, difficult and time-consuming. Since most investors do not have substantial data science teams and resources, data-driven decision-making is limited. With a data science team and optimised results, the process is improved but ingrained inefficiencies remain.The resultant societal effect is that good companies can be overlooked for investments, reducing UK growth and innovation. KP-Intel will democratise access to relevant data insights so that no data science background is required to utilise data-driven decision-making; removing its associated inefficiencies/increasing accessibility. Long-term, this will drive innovation and growth of the UK economy while improving investor transparency.

我们的创始人兼首席执行官Josef Schmalfuss是利用替代数据进行基本投资的公认行业领导者。他在基本投资基金担任买方/内部替代数据创建者的合作伙伴七年后，他认为需要创新来改变目前的数据潜能生成过程以进行投资决策。关键绩效指标（KPIS）是指出公司整体业绩的重要来源。当前，投资决策主要基于倒退的报告数据，该数据包括季度或年度报告或财务报表。但是，还有许多其他领域表明公司的投资价值。我们正在利用替代数据为此目的生成KPI跟踪器，这些跟踪器包括交易数据，应用程序下载，社交媒体和移动性数据等数据。我们的解决方案是基于这样的想法：公司的投资潜力不仅基于它在旧纸上的外观。目前，为了产生替代数据见解，公司和投资者必须在此过程中寻求数据科学家的投入，这可能是昂贵，困难且耗时的。由于大多数投资者没有大量的数据科学团队和资源，因此数据驱动的决策是有限的。通过数据科学团队和优化的结果，该过程得到改善，但根深蒂固的效率仍然存在。由此产生的社会效果是，可以忽视优秀的公司的投资，从而减少英国的增长和创新。 KP-Intel将民主化对相关数据见解的访问，以便不需要数据科学背景来利用数据驱动的决策；消除其相关的效率低下/增加可访问性。长期，这将推动英国经济的创新和增长，同时提高投资者的透明度。