BFSI to Spearhead the Growth of Global Text Analytics Market

Allied Market Research adds a report titled “Global Text Analytics Market (Deployment Model, Application, End User and Geography) - Size, Share, Global Trends, Company Profiles, Demand, Insights, Analysis, Research, Report, Opportunities, Segmentation and Forecast, 2013 – 2020.” The report offers incisive market data on the global text analytics market and assist the numerous market investors to understand the market dynamics.

The application of Text analytics in the Banking Financial Services and Insurance Industry would open up avenues for the market. Banking Financial Services and Insurance (BSFI) comprise a wide range of firms that offer financial services to numerous sectors. BSFI includes of monetary organizations such as insurance agencies, commercial banks, mutual funds, non-banking financial companies, cooperatives etc. The banking segment comprises Investment Banking, Corporate Banking and Retail Banking. Banks such as Barcalys, Citygroup and HSBC encompass wide range of banking categories. Financial Services comprises of Mutual Funds, Non Banking Financial Companies (NBFCs) and Broking firms


Analyticsprovides a new opportunity for fraud detection in the BFSI sector. An innovative method for fraud detection is social network analysis, which enables companies to look through a large amount of data to find relationships between variables. Financial Institutions’ believes use of analytics to analyze the customer drives their business. Adoption of social media technology continues to accelerate amongst consumers,” states AMR analyst.

“Predictive data analytics also help in the detection of frauds in the sector. Infinity Insurance Co. claim that with the use of predictive analytics, the success rate of identification of frauds has increased from 50-88% and also that the time required for investigation is reduced as these analytics have an accuracy of about 95%,” adds the analyst.

Attensity, a text analytics leader, has announced a solution based on analytics for Retail Banks. Aforementioned software recognizes unknown patterns within the text of consumer discussions and supports the monetary service companies to implement numerous types of actionable data such as, sentiment analysis, churn analysis etc.

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