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Josef Schmalfuss是利用替代数据进行基本面投资的公认行业领导者。他曾在一家基础投资基金担任合伙人长达七年，是另类数据的买家/内部创建者。他认为，要改变当前用于投资决策的数据洞察生成流程，就必须进行创新。关键绩效指标（KPI）是衡量公司整体绩效的重要来源。目前，投资决策主要是基于回顾性的报告数据，包括季度或年度报告或财务报表。然而，还有许多其他领域表明公司的投资价值。为此，我们正在利用替代数据来生成KPI跟踪器，其中包含交易数据，应用程序下载，社交媒体和移动数据等数据。我们的解决方案基于这样一个理念，即公司的投资潜力不仅仅取决于它在一张旧纸上的外观。KP-Intel是一个改变游戏规则的平台，用于利用实时数据自动生成每日数据驱动的KPI估计，适用于 ** 每家 ** 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，这可能是昂贵的，困难的和耗时的。由于大多数投资者没有大量的数据科学团队和资源，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，这一过程得到了改善，但根深蒂固的低效率仍然存在。由此产生的社会影响是，优秀的公司可能会被投资忽视，从而降低英国的增长和创新。KP-Intel将使相关数据洞察的访问民主化，因此不需要数据科学背景来利用数据驱动的决策;消除其相关的低效率/提高可访问性。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.