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Determinants of successful patent applications to combat financial fraud

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Abstract

Finding out the characteristics of patent applications that lead to successful grants is an important and yet under-investigated topic in the scientometric literature. Using data from financial fraud-related patent applications submitted to the United States Patent and Trademark Office (USPTO), this study aims to determine which factors that can be influenced by inventors relate to successful patent grants. A descriptive statistical model is proposed to estimate the likelihood of a patent document being granted by the USPTO based on a number of explanatory variables. The following factors are among the notable statistically significant determinants for the studied patent sample: number of drawings, drafting aggressiveness, proportion of granted patent prior art references, proportion of web-based non-patent literature references, subclass specialization, and representation by a patent attorney or agent. The implications of these empirical findings are discussed in the context of entrepreneurship.

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Notes

  1. An exception exists for patent applications that raise concerns for public safety. In these cases neither the applications nor patent grants will be published.

  2. Throughout the article the word “grantability” will be used to refer to the likelihood of the patent application becoming a granted patent in a given amount of time. The expressions “likelihood of granting” and “grantability” will be used interchangeably.

  3. For completeness, our study includes all the International Patent Documentation family members of patent applications that matched the searched keywords.

  4. Questel’s Orbit is a subscription-based comprehensive patent research platform that was launched in 2009 and updated multiple times since then (Landon 2012). It is a competitor product to Thomson Innovation. Building on the data feeds that they receive from USPTO, each offers different value-added features that aid data retrieval.

  5. Variations in the assignee or applicant names representing the same entity have been manually scanned and corrected, so that each assignee or applicant name represents a unique entity.

  6. The recommendations can be found at the following link http://www.fatf-gafi.org/media/fatf/documents/recommendations/pdfs/FATF_Recommendations.pdf.

  7. This information was obtained from the Financial Action Task Force (FATF) website: http://www.fatf-gafi.org/publications/high-riskandnon-cooperativejurisdictions/more/aboutthenon-cooperativecountriesandterritoriesncctinitiative.html?hf=10&b=0&s=desc(fatf_releasedate).

  8. The public statements can be found at the following address: http://www.fatf-gafi.org/publications/?hf=10&b=0&s=desc(fatf_releasedate).

  9. For all the variables indexed by subscripts i and/or j, the subscript j indexes the patenting entity, while the subscript i indexes the invention within that entity’s set of inventions. So, for example the variable FATF i,j shows whether or not the jth patenting entity’s ith invention has inventors that originate from high-risk or non-cooperative jurisdictions.

  10. The blog can be found at the following link http://patentlyo.com/patent/2014/08/increases-likelihood-patenting.html.

  11. This chain of events is continued all the way back to the very initial efforts made at patenting of the earliest related application.

  12. For the 84 applications for which the US classifications were unavailable at the time of data extraction, we calculated each of the 3 variables defined in this section using the median of the corresponding variables in the patent family based only on those applications for which the US classifications were available.

  13. Cancelled claims are ignored in this calculation.

  14. 35 U.S. Code Sect. 113 Drawings and related regulations 37 CFR 1.81 to 1.84.

  15. According to Thomson Reuters, “DWPI is the world's most comprehensive database of enhanced patent documents. Subject experts from Thomson Reuters correct, analyze, abstract and manually index every patent record, making it easier to quickly find the information needed to make informed decisions.” As part of their quality control, DWPI experts review the patent specification and subsequently provide their own summary of the patent application in the form of an enhanced DWPI abstract, which we use as an accuracy “benchmark” for comparison with the original abstract.

  16. Note that to overcome this issue Mann and Underweiser (2012) use binary term frequencies, which ignore the actual frequencies of terms appearing in documents. Moreover, if the ratio in the lengths of documents A and B is the same as that of documents C and D, while content-wise A and B are as similar as C and D, the measure proposed by Mann and Underweiser (2012) will nevertheless indicate differing alignments between the two sets of documents, if the length of document A is different from that of B, and the length of C is different from that of D.

  17. We defined this field by programmatically counting within all the referenced NPL corresponding to each patent document, all the references containing keywords characteristic of web-based material (e.g. “www”, “http”, etc.).

  18. This information was obtained by matching the kind codes appearing on publication numbers of referenced patent-related literature to kind codes denoting granted patents for each country, as provided by Thomson Innovation: http://www.thomsonfilehistories.com/docs/RESOURCES_Kind%20Codes%20by%20Country.pdf.

  19. All inventions by assignees “Kia Silverbrook” and “Silverbrook Research” were combined and represented in our analyses under the name “Silverbrook Research”.

  20. It is further assumed that the random effects vary independently from one entity to another, that they are normally distributed with mean zero and constant variance, and that conditional on entity, Y i,j are independent.

  21. Models with similar configuration of random effects are often colloquially referred to as “random intercept” models.

  22. The variables were removed in descending order of p values. Notice that control variables were retained in the model regardless of their p-values. Also, note that if at least one level of a categorical variable had a p value <0.1, the entire variable (i.e. with all levels) was retained in the model. This method of “hierarchical backward elimination” is described in Kleinbaum and Klein (2010). Finally notice that although the reported p values are before correcting for false discovery rates (fdr), we also performed the successive elimination of variables after updating the p values at each step using the Benjamini-Hochberg correction (Benjamini and Hochberg 1995). The results regarding the statistically significant variables found to be associated with grantability were consistent with the results reported without such a correction.

  23. Various transformations were also entertained for the remaining numeric explanatory variables but those did not yield improvements in the model fit.

  24. For the purposes of classification, the sensitivity is the proportion of all granted patents that were correctly classified. Similarly, specificity denotes the proportion of pending patent applications that were correctly classified as pending.

  25. Distance was measured based on Euclidean distance.

  26. Patent examiners give priority to the applications with the oldest effective U.S. filing dates unless an application is made special upon a petition by an applicant accompanied by any evidence showing that the state of health of the applicant is such that he or she might not be available to assist in the prosecution of the application if it were to run its normal course or if an applicant is 65 years of age or older.

  27. This number was obtained by dividing 0.4801 by 0.1469 appearing in the superscript of the odds ratio and rounding to the nearest integer.

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Acknowledgements

Ani Eloyan, William O’Sullivan, Ross Petty, Anthony Trippe, customer service support from Questel.

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Authors and Affiliations

  1. Division of Mathematics and Science, Babson College, 231 Forest St, Babson Park, MA, 02457, USA

    Davit Khachatryan

  2. Division of Accounting and Law, Babson College, 231 Forest St, Babson Park, MA, 02457, USA

    Brigitte Muehlmann

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  1. Davit Khachatryan
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Correspondence to Davit Khachatryan.

Appendices

Appendix 1

See Table 5.

Table 5 Parameter estimation summary for Model (1)
Full size table

Appendix 2

Control variables

As can be noticed from the parameter estimation summary, there exists a statistically significant relationship between the odds of granting and the main effect of the variable controlling for time (ScaledLife i,j ), the main effect of the variable controlling for the prior efforts (PriorEfforts i,j ), as well as the interaction of these two. Although not the primary interest of this study, these controls deserve a special note. The estimates signify that first, an increase in prior efforts spent at patenting of inventions related to the current application is in most cases associated with a higher likelihood of granting (ceteris paribus), regardless of how long ago or how recently the document was applied to the USPTO. However, the added value of each unit increase in prior efforts is greater for applications that have been submitted to USPTO relatively long ago, compared to relatively recent applications \(({\text{OddsRatio}} = {\text{e}}^{{0.2794 + 0.1469{\text{ScaledLife}}_{i,j} }} ).\) Further, the impact of time during which the patent document has been at the USPTO is beneficial only for documents with a significant amount of prior efforts, all else the same \(({\text{OddsRatio}} = {\text{e}}^{{ - 0.4801 + 0.1469{\text{P}}{\text{riorEfforts}}_{i,j} }} ).\) Put differently, the longer the amount of time the patent document was already at the USPTO at the time of this study, the higher are its odds of being granted provided that there had been an estimated number of more than three prior efforts preceding the submission of the patent document to the USPTO.Footnote 27 Among documents with less than or equal to three prior efforts, more recent submissions had a higher likelihood of being granted compared to submissions that had been at the USPTO system for longer periods of time. This may be attributed to recent submissions not needing as many prior efforts to reach granted status as compared to older submissions. These “older” applications that were submitted to the USPTO at a time when the technological domain of financial fraud detection and prevention was not as well understood as it is today, perhaps required several iterations in the form of continuations, continuations in part or divisional applications, to successfully reach granted status. Thus in the original form, in other words, devoid of these modifications, the fact alone that a patent document was submitted relatively long time ago does not imply higher odds of granting compared to more recent submissions.

Note also that although again, not the primary objective of this study, a statistically significant relationship was not present between grantability and the team size of inventors as well as with whether or not there existed an inventor on a patent from a high-risk and non-cooperative jurisdiction. Nevertheless, in line with the “hierarchical backward elimination” procedure outlined in Kleinbaum and Klein (2010) these variables were retained in the model, since for an accurate estimation of variables of main interest in this study we wanted to account for and filter out the impacts of these controls.

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Khachatryan, D., Muehlmann, B. Determinants of successful patent applications to combat financial fraud. Scientometrics 111, 1353–1383 (2017). https://doi.org/10.1007/s11192-017-2354-6

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