Assessment of technological capabilities to counter fraudulent practices in the banking sector

In connection with the strengthening of Western sanctions on the Russian banking sector, the number of malefactors, who enjoy the confidence of panicking depositors and the unstable situation in the banking market, has increased dramatically. The article discusses the key issues of the application of big data analysis as a technological basis for countering fraud in the practical activities of banks. The objectives of such a struggle are to determine the operations of intruders in the flow of large volumes of statistical information with the greatest accuracy and to take preventive measures to minimize damage. The purpose of the article is to assess the possibility of using machine learning technology by banks and develop an algorithm for detecting fraudulent transactions based on programming. Particular attention is paid to the current economic environment, its impact on the financial system as a whole, and in particular, on the reorientation of the banking sector to combat fraud in the context of increased fraud activity

A Peripheral Blood Diagnostic Test for Acute Rejection in Renal Transplantation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93759/1/j.1600-6143.2012.04253.x.pd

Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers