Financial inclusion is the process of achieving the development goal, but not the goal itself. It involves availing the financial services of financial institutions like maintaining savings account, having insurance or taking formal credit. Some but not all financial products are effective in achieving goals like eliminating poverty. Savings account which is earmarked for specific purposes such as school fees have quite an impact, whereas microcredit has mixed impact on low earning individuals. There is a lack of evidence of a link between financial inclusion and macroeconomic growth indicators as against that at the micro level. Results of field experiments cannot be replicated across countries. As technology changes better ways can be devised to link micro level benefits to macroeconomic goals. Read more at : http://blogs.worldbank.org/allaboutfinance/what-do-we-know-about-link-between-financial-inclusion-and-inclusive-growth

Rapidly changing consumer demands are becoming one of the major concerns of the financial institutions. Analytics is the technology which can be adopted to address this need. With evolving customer expectations, analytics solutions, too, have adapted, but the question under consideration is whether the banks are prepared to adopt and benefit from the next-generation analytics solution. As viewed by Thomas H. Davenport, evolution of analytics is a three-stage process of which Analytics version 3 is the latest generation which merges qualities of previous technologies and focuses on prescriptive analytics. Based on the data collected, Analytics 3.0 will enable the financial institutions can create tailor made services for customers. However, to fully reap the benefits, the institutions have to make sure that the right technologies and practices are in place. Read More at: http://internationalbanker.com/banking/are-banks-ready-for-next-generation-analytics/

Banking and finance are an indispensable part of our lives.  Though the world today is divided into rich and poor, but the common fact amongst these two groups is that they need funds to invest and grow. To meet this common need of these two different groups, we have two different institutions:

• Investment Banks
• Microfinance Institutions

Matthew Johnston, in his article at Investopedia.com, has compared these two financial institutions in terms of their history, use, recent trends as well as examples.

To know more, please visit the following link:

http://www.investopedia.com/articles/personal-finance/052215/how-microfinance-and-investment-banking-compare.asp

According to a 2014 survey of more than 2,000 business professionals by MIT Sloan and SAS Institute, 87% respondents share a common restlessness to elevate their organizations to the next level of analytics.

Being data driven, has now become a necessity for all businesses, especially financial institutions. Using predictive data analytics to interpret a wide range of internal and external data on customers helps financial institutions to identify best targets for a particular product and earn more by making timely pitches.

Russ Bunham, in his Forbes article, gives four tips on how financial institutions can use big data analytics to their advantage:

1. Creating a customized, consistent customer experience
2. Dissolving internal silos to have one view of the customer
3. Ensuring data insight flows to the right person to make the pitch
4. Using big data knowledge to enhance customer relationships

To understand them in detail, visit the following link:

http://www.forbes.com/sites/centurylink/2015/04/14/4-ways-financial-institutions-can-bank-on-big-data-in-2015/

One may think how anyone can make a profit by issuing credit cards. Lending money to people up front, so they can buy what they want to with it, then 30 days to pay it back without interest. But the contradiction is with a market valuation of about $133 billion and profit margins at 42%, Visa has proven that extending credit to consumers and assuming they'll be irresponsible is as gainful an industry as any. The process involved in the Visa model is: Bank X distributes its Bank X Visa cards to accountholders, who now have the convenience of not having to carry wads of bills for every commercial transaction. Now the banks start charging 14% or 19% or 24% interest which keeps adding to its total revenue. Visa, in the form which it is today would not have existed if people bought only what they could afford and saved for their large purchases. If you pay your Visa bill entirety every month, it costs your financial institution to accommodate you. They'll lose money on the deal. On the other side if you incur a balance and add to it with each pay period, you'll be contributing to a scenario whereby Visa's stock price has not only tripled over the past three years, but remains well shy of an ambitious one-year target estimate. Read more at: : http://www.investopedia.com/articles/markets/080714/how-visa-counts-your-credit-card-balance.asp

Big data gives governments tools to discover more effective and innovative ideas on how to decrease poverty across the world. Proper application of big data and technology advancement can improve the circumstance of people currently impoverished. Before, collecting reliable data from all corners of a country can pose as a hindrance in the complete elimination of poverty but now this problem is solved by the advances in mobile technology. Reportedly, more than 85% people in the world have access to mobile phones, even if some of them are the poorest people which lead to greater data collection on the poor and availability of big data acts as a catalyst to help the poor people prosper. Data collected from cell phone call data records and an individual's bill payment history banks and other financial institutions can effectively evaluate a person's ability to pay back loans and determine their risk attitude. This helps the institutions to give credit to the required people through micro financing. Read more at:

http://www.bigdata-startups.com/5-applications-big-data-in-government/