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Business Intelligence Is Rife With Opportunities For Financial Services
Total Articles: 6
The huge volumes and speed of incoming data poses a threat for the finance industry, especially financial services. The massive amounts of data have to be efficiently cleansed, stored, and analyzed before anything useful can be done. Thus, technologies like big data, Hadoop, or real-time analytics offer newer opportunities to age-old business intelligence practices in this sector.
How Big Data Has Changed Finance indicates big data has transformed business intelligence in the financial services; today, most financial institutions use big-data enabled insights and market intelligence to maintain a competitive edge. Moreover, technologies like algorithmic trading have brought new dimensions to financial BI in stock exchanges.
Current challenges for financial data analysis
Challenge 1: Although capable technologies are surfacing every day, the realm of day-analytics in financial services faces criticism for not keeping up with advanced statistical techniques for handling high volume data. Data discovery is still in immature stage, and most trend and pattern analysis based on historical finance data are not considered reliable for long-term use. Thus the lacuna or deficiency may be in the predictive algorithms or in the statistical methods used to develop those algorithms.
Challenge 2: According to a Cloud Computing news article, Skyhigh Network’s latest industry outlook indicates an average financial services company uses ‘more than 1,000 cloud services.’ The article also states that 15.5% of financial suffer compromised credentials, which is more than any other industry sector. As sensitive data moves over to the cloud in financial services, this sector faces an increased pressure of meeting regulatory requirements.
BI in the financial services in the big data age
As in most cases, challenges also signal new opportunities. So here is a roundup of some probable opportunities for big-data enabled BI in the financial sector:
Algorithmic Trading in the Financial Sector
In the big data era, algorithmic trading is easily possible with advanced machines. The automation of stock exchanges enable computers to execute business intelligence aided financial trades at high speed, and high frequencies, at optimized values, and in accurate and timely manner—attributes that no human trader can match.
Strategic and Tactical Intelligence through Intelligent Dashboards
Intelligent dashboards have suddenly gained popularity among the financial services community for the efficiency and operational wisdom of those tools. Custom dashboards can acquire data from multiple sources, and then provide quick, relevant, and user-friendly reports for instant decision making. These dashboards have revolutionized the role of business intelligence. Now, the newly engineered dashboards have the smarts to deliver restricted, role-based functionality to serve the needs of enterprise workers at any level or position. While senior executives in financial services may use the dashboards to meet the company’s strategic goals, the managers may use the dashboards to gain tactical insights into the business. Department heads may use the dashboards to periodically review operational processes. Thus, BI in the digital age has the potential to become an all-found business solution for enterprise financial services businesses.
Real-time Operational Intelligence
The sales folks in financial services can utilize dashboards to deliver real-time, actionable intelligence to the customers while keeping track of new sales opportunities! Also, with with custom dashboards, the sales personnel can monitor and compare the business growth and revenue from time to time.
Social Presence Management
The financial services team can manage its social media presence from a central BI-enabled dashboard to manage its various social media accounts and measure the effectiveness of social channels. The central dashboard greatly enhances marketing strategies and the quality of analyzed reports for board meetings.
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