Research by Jonathan J. Koehler and Siquan Liu on the accuracy of distinguishing between two close non-matches was published in Sept. 2020. Attorneys should be aware of the error rates presented in this paper, particularly when working on cases involving a match to a suspect developed by searching a fingerprint database. As fingerprint databases grow, the likelihood of the database containing prints that are close non-matches will increase, leading to potential false positive errors.
The paper is available for free download here.
From the abstract:
The accuracy of fingerprint identifications is critically important to the administration of criminal justice. Accuracy is challenging when two prints from different sources have many common features and few dissimilar features. Such print pairs, known as close non-matches (CNMs), are increasingly likely to arise as ever-growing databases are searched with greater frequency. In this study, 125 fingerprint agencies completed a mandatory proficiency test that included two pairs of CNMs. The false-positive error rates on the two CNMs were 15.9% (17 out of 107, 95% C.I.: 9.5%, 24.2%) and 28.1% (27 out of 96, 95% C.I.: 19.4%, 38.2%), respectively. These CNM error rates are (a) inconsistent with the popular notion that fingerprint evidence is nearly infallible, and (b) larger than error rates reported in leading fingerprint studies. We conclude that, when the risk of CNMs is high, the probative value of a reported fingerprint identification may be severely diminished due to an elevated false positive error risk.