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

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$500,000.00
Award Year:
2011
Program:
SBIR
Phase:
Phase II
Contract:
1127191
Agency Tracking Number:
1127191
Solicitation Year:
2011
Solicitation Topic Code:
Phase II
Solicitation Number:
n/a
Small Business Information
Corporate Portfolio Management LLC
56 Pine Street, Suite #3D, New York, NY, 10005-1538
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
808473610
Principal Investigator:
Anand Sanwal
(917) 279-2101
asanwal@cbinsights.com
Business Contact:
Anand Sanwal
BEng
(917) 279-2101
asanwal@cbinsights.com
Research Institution:
Stub




Abstract
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.

* information listed above is at the time of submission.

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