Dallas, Texas (PRWEB) May 11, 2014
The service providers are applying an analytical approach to meet AML compliance and there are different methodologies applied by service providers to identify suspicious activity reports. However, some traditional approaches such as linear regression analysis generate false alerts along with suspicious activity reports, which are not worth investigating. On the other hand, predictive analytics enables enterprises to reduce the false alerts by 60 to 70 percent and reduces the compliance cost of adopting AML software. Predictive analytics is also a better methodology because it can encode more information about an account or customer’s activity.
Analysts forecast the Global Anti-money Laundering AML Software market will grow at a CAGR of 11.54 percent over the period 2013-2018. According to the report, most people are increasingly shifting toward debit cards as a preferred mode of payment because of the ease of use. This leads to data breach by criminals to access huge amounts and acquire debit card information. Large-scale data breaches of major retail chains are currently common. If there are a number of debit frauds against an enterprise customer satisfaction is not met and thus they stop availing the service. To save customers loss and prevent customers from becoming the victim of such activities, many enterprises are deploying AML software.
The Global AML Software market can be divided into four segments: Internal Spending, Software, Services, and Hardware.
Global AML Software Market 2014-2018, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the Americas and the EMEA and APAC regions; it also covers the Global AML Software market landscape and its growth prospects in the coming years. The report also includes a discussion of the key vendors operating in this market.
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Further, the report states that one of the major challenges is the inconsistency in the data because of the data in enterprises are collected by the different departments and proper functioning of AML software requires consistency in data.
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