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

我们的创始人兼首席执行官约瑟夫·施马尔弗斯在利用替代数据进行基本面投资方面是公认的行业领导者。他在一家基本投资基金担任了七年的合伙人，担任另类数据的买家/内部创建者，他认为需要进行创新，以改变当前为投资决策生成数据洞察的流程。关键业绩指标(KPI)是指示公司整体业绩的一个极其重要的来源。目前，投资决策主要基于回溯的报告数据，包括季度或年度报告或财务报表。然而，还有许多其他领域可以表明一家公司的投资价值。为此，我们正在利用替代数据，以生成包含交易数据、应用程序下载、社交媒体和移动数据等数据的KPI跟踪器。我们的解决方案基于这样一种理念，即公司的投资潜力不仅仅取决于它在一张旧纸上的样子。KP-英特尔是一个改变游戏规则的平台，用于自主生成每日数据驱动的KPI估计，利用实时数据，**每一家**中型/大型英国公司和相当大比例的中小型企业。目前，为了产生替代数据洞察，公司和投资者必须在这个过程中寻求数据科学家的投入，这可能是昂贵、困难和耗时的。由于大多数投资者没有强大的数据科学团队和资源，数据驱动的决策有限。有了数据科学团队和优化的结果，这一过程得到了改善，但根深蒂固的低效仍然存在。由此产生的社会影响是，优秀的公司在投资时可能会被忽视，从而降低英国的增长和创新。KP-英特尔将普及对相关数据洞察的访问，因此不需要数据科学背景即可利用数据驱动的决策制定；消除了相关的低效率/提高了可访问性。从长远来看，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。

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.