The Innovation and Technology is transforming the finance and banking industry. The banking industry was one of the fast growing industry in all over the world. It also has the potential to become the fifth largest industry in the world by 2020. In order to stay competitive and to retain success the banks were taking the data analytics route to lure new customers, retain them, find opportunities to upsell and cross-sell and minimize their own losses. Nowadays the finance sectors are centralizing BI efforts and improving data management, as well as turning to predictive analytics to ensure everything is going through the right way and also the real-time business intelligence and analytics have been steadily gaining an significant role in the finance and banking industry over the last few months.
Many people has been wondering that how analytics is used to reduce chances of money laundering by identifying suspicious activity such as moving money to multiple accounts, finding large single-day cash deposits, opening a number of accounts in a short period of time or sudden activity in long-dormant accounts.
By using analytics, most of the financial problems has been solved where the bank would also be able to keep track of credit histories of customers and can hand out loans accordingly.
The finance industry were generating a large amount of data on a day to day basis. This makes the finance sector to increase the adoption of big data analytics as part of their core strategy. When it comes to big data business analytics, every industry has ambitious plans to achieve new insights where the business intelligence and analytics helps everyone to find deeper insights of data with the development and application of AI solutions.
The Cognitive information Insights allude to the extraction of ideas and relationships from different data streams to create customized and significant answers covered up inside a mass of structured and unstructured data. With the recent business intelligence platform we can easily obtain the real time key patterns and relationships from large amount of data across multiple sources to derive deep and actionable insights.
By using the right business intelligence tools we can easily able to manage the banking institutions which need to rely more on fact-based actionable information, gleaned from ever-increasing data assets, to reduce risk wherever and whenever possible. Through the BI we can easily able to reduce the fraudulent activity and also mitigate risk in the finance and banking sector.
You cannot successfully market and grow your business if you don’t understand who your ideal customer is, where this analytics helps to determine what is needed for business and make easy customer profiling and analytics. Analyze and interact promptly with the data stored in the core banking based on a range of customer segmentations and geographies to uncover the ideal and the most profitable customer profile. The customer base profitability can easily be analyzed to determine profitability across branches and products, and to track, develop new cross-sell and up-sell opportunities and marketing campaigns accordingly.
This involves the identifying the problem because of which branch may be losing money. This may involve separating profitable segmentation from the non-profitable ones. Managing and running bank was not an easy process where it needs proper analytics that helps the banks in designing, structuring and also in improving the customer response rate into higher.
Choosing the right business intelligence platform provides a very big opportunities for banks. At some level, actually, you can think of as it is a way to transform the bank into more customer relationship value across all the silos. The better data analytics to accurately predict the payment behaviour in financial sector and to get updated by getting actionable insights.
The BI techniques helps to track your bank’s end-to-end financial operations both fund based and non-fund based that provides a great assistance to ensure effective risk management by measuring exposure, i.e., the amount of money at risk and perform a periodic analysis of deposits and borrowings for different segments.
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