SBIR Phase II: Assessing Private Company Health Using Advanced Language Computing Techniques

这个小企业创新研究（SBIR）第二阶段项目将开发一个针对金融机构（贷方和投资者）的软件系统，该系统将为他们提供有关私营公司健康状况的可操作的实时情报。这项正在开发的技术将扫描和分析数以百万计的结构化、半结构化和非结构化信息源，以寻找私营公司健康状况的信号。然后，根据上下文，它将通过算法处理、分类和评估这些不同信号的情绪和强度，以提供一个全面、连贯和实时的视角，了解私营公司的健康状况、可能的融资需求以及金融机构最适合的融资解决方案。S的产品组合。使用该公司的产品线，金融机构将能够以一种完全不同的、更智能的、更可扩展的、数据驱动的方式来看待私营公司，使他们能够高效、智能地做出关键的融资和资本配置决策。具体来说，他们将有潜力实时识别合适的私营公司，并将拥有他们可以用来为他们提供适当融资解决方案的情报。该系统能够处理各种结构化、半结构化和非结构化信息源，并以编程方式得出公司健康状况的衡量标准，这将对机构贷款和私营公司投资的准确性、严密性和可扩展性产生深远的积极影响。如今，私营企业融资市场建立在高度不精确和不完善的启发式基础上，导致企业贷款违约率居高不下，最糟糕的情况是，2009年发生的银行倒闭。这种情况的下游影响是小企业无法获得所需的融资，正如2009年所证明的那样，根据美联储的数据，只有40%的寻求银行融资的私营小企业实际上获得了所需的资金。根据小企业管理局的数据，雇员少于500人的企业占全国就业人数的一半以上，占GDP的近一半。因此，作为经济催化剂的健康私营公司获得融资至关重要。不幸的是，如果没有可靠、可操作、可扩展和实时的信息来区分健康和不健康的私营企业，金融机构仍然处于信息劣势。这增加了它们的风险，反过来又阻碍了成长中、健康的私营企业获得所需的融资。如果成功部署，该提案所支持的技术有可能在市场上产生重大影响。

This Small Business Innovation Research (SBIR) Phase II project will develop an software system directed at financial institutions (lenders and investors) that will provide them with actionable, realtime intelligence into the health of private companies. The technology being developed will scan and parse millions of structured, semi-structured and unstructured information sources searching for signals of a private company's health. Then, based on context, it will algorithmically process, categorize and assess the sentiment and strength of these disparate signals to offer a comprehensive, coherent and real-time view of a private company's health, its likely financing needs and best fit financing solutions from a financial institution?s product portfolio. Using the company's line of products, financial institutions will be able to look at private companies in a fundamentally different, smarter, more scalable and data-driven way that empowers them to efficiently and intelligently make critical financing and capital allocation decisions. Specifically, they will have the potential to able to identify the right private companies in real-time and will be armed with intelligence they can use to offer them appropriate financing solutions.The system's ability to process a diversity of structured, semi-structured and unstructured information sources and programmatically derive measures of company health would have profound positive effects on the precision, rigor and scalability of institutional lending and investment into private companies. Today, the private company financing market is built on highly imprecise and imperfect heuristics that result in high business loan default rates, or at its worst, bank failures as occurred in 2009. The downstream impact of this is that small businesses do not get the financing they need as evidenced in 2009 when, according to the Federal Reserve, only 40% of private small businesses that sought bank financing actually received the funding they needed. Per the Small Business Administration, businesses with fewer than 500 employees account for more than half the nation's employment and nearly half of GDP. As a result, it is critical that healthy private companies which are an economic catalyst have access to financing. Unfortunately, without credible, actionable, scalable and real-time information which distinguishes between healthy and unhealthy private businesses, financial institutions remain at an informational disadvantage. This increases their risk, which in turn hinders growing, healthy private companies from receiving the financing they need. If successfully deployed, the technology being supported by this proposal has the potential to make a significant impact in the marketplace.