SBIR Phase I: Assessing Private Company Creditworthiness Using Advanced Information Extraction and Translation Techniques
SBIR Phase I: Assessing Private Company Creditworthiness Using Advanced Information Extraction and Translation Techniques
批准号:
1013402
负责人:
Anand Sanwal
金额:
$15.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-07-01 至 2010-12-31
中文摘要
这个小型企业创新研究(SBIR)第一阶段项目解决了提供有关私营公司的可靠,可操作和实时情报的挑战-金融机构,投资者,服务提供商,研究人员和企业家强烈感受到的挑战。该公司计划开发一个平台,该平台将(1)从数百万个相关来源收集有关私营公司的信息;然后(2)提取和构建这些信息,最后(3)通过算法提供公司信誉和健康的持续定量测量-从而开发私营公司实力情绪评分。第一阶段研究包括三个阶段:(1)建立,包括确定推动得分的实力和情绪指标(SSI)以及确定相关数据源;(2)数据&技术,包括优化收集SSI数据的现有技术以及收集测试样本的真实的财务和运营私人公司数据;以及(3)分析,包括准备数据集、运行统计分析和创建SSI分数。第一阶段的最后一步是审查产出与为私营公司收集的经验数据之间的相互关系,以便评估预测价值。这一努力的主要商业利益将是增加美国小企业获得具有竞争力的价格信贷的机会。如果成功,这一努力将减少围绕私营公司信息的信息不对称,从而使金融机构能够更好地估计与可能寻求信贷的私营小企业有关的初始和持续风险。根据SBA宣传办公室的说法,小企业信贷供应增加带来的更广泛的社会影响包括“各种规模企业的经济增长、就业和工资”的增加。除了有利于机构贷款外,这一努力还有可能为那些提供贸易信贷或供应商采购融资的企业以及股权投资界提供重大好处,例如,风险投资私募股权从长远来看,为创建和跟踪公司得分而收集的数据代表了一个丰富的创业私营公司数据库,可以利用这些数据来创建数据驱动的产品,帮助企业家,学者,研究人员和公共政策专业人员了解和支持我们国家的创业生态系统。
英文摘要
This Small Business Innovation Research (SBIR) Phase I project addresses the challenge of offering reliable, actionable and real-time intelligence about private companies - a challenge acutely felt by financial institutions, investors, service providers, researchers and entrepreneurs. The company plans to develop a platform that will (1) collect information on private companies from millions of relevant sources; then (2) extract and structure this information and finally (3) algorithmically deliver an ongoing quantitative measure of company creditworthiness and health - thus developing a Private Company Strength & Sentiment Score. The Phase I research is comprised of three stages: (1) Set Up, which includes the identification of Strength and Sentiment Indicators (SSIs) that drive the score as well as identification of relevant data sources; (2) Data & Technology, which includes optimizing existing technology for collection of SSI data as well as collecting real financial and operating private company data for a test sample; and (3) Analysis, which includes preparing the data set, running statistical analyses and creating SSI scores. This final step of Phase I entails examining correlations between outputs and the empirical data collected for private companies so that predictive value can be assessed. The primary commercial benefit of this effort will be the increased availability of competitively priced credit to US small businesses. If successful, the effort will reduce the information asymmetry surrounding private company information and thus allow financial institutions to better estimate the initial and ongoing risk associated with private small businesses who may be seeking credit. Broader societal impacts resulting from increased credit availability to small businesses include increased "economic growth, employment and payrolls at businesses of all sizes" according to the SBA Office of Advocacy. In addition to benefitting institutional lending, the effort has the potential to offer significant upside to those businesses providing trade credit or supplier financing of purchases as well as to the equity investment community, e.g., venture capital, private equity. Longer-term, the data collected to create and track companies' scores represents a rich repository of entrepreneurial & private company data that can be leveraged to create data-driven offerings that assist entrepreneurs, academics, researchers and public policy professionals their attempt to understand and support our nation's entrepreneurial ecosystem.
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SBIR Phase II: Assessing Private Company Health Using Advanced Language Computing Techniques
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批准号:1127191
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2011
-
负责人:Anand Sanwal
-
依托单位:
国内基金
海外基金
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