The term ‘Big Data’ refers to a collection of data that can be used to analyze trends and patterns practiced by individuals while performing transactions with a financial institution. The information of this trade relates to the individual customers and helps in the determination of how able the client is of creditworthiness. This data is often used for enhancing good relations with customers. Data mining and warehousing technologies have helped the banking industry access information related to the mode of transactions and operations used by customers. As financial institutions and banks provide services, including cash management, it is necessary to understand the patterns through which the customer conducts the transactions that involve transferring money between accounts.
Benefits of data mining for banking sectors
Applying the various techniques and technologies of data mining has enabled banks and financial institutes to make better decisions when customers apply for loans or mortgages. At such times, the data of the customer transactions turn into valuable information that helps the bank to decide better if the customer is worthy enough for the loan or mortgage to be sanctioned. It is also beneficial to identify the payment cycle that the customer can handle. Data mining has a lot of other benefits in the banking sector, ranging from predicting market trends to determining the best tariffs and plans and understanding how each customer differs from the other and what methods can work best for them. It thus allows customer service radicalization in the banking sector. It helps to increase customer retention ability and implement new strategies.
Privacy concerns related to the use of big data
While data mining techniques and extensive data analysis have transformed how businesses treat information to date, privacy threats still need to be addressed. Identifying the dangers in the field and how the risks can hamper the business’s goodwill is necessary. Extensive data analysis starts with effectively sorting valuable data into tables and columns that can be used for the study. Many organizations store large data pools in their warehouses, which puts the customers’ sensitive information at risk of internal theft and information destruction. The privacy of the customer information is also at risk of unauthorized access that may sell the data to a third-party vendor.
The necessity to focus on privacy concerns while handling big data
Thus, the banking sector must establish clear definitions of its privacy policies and identify proper steps to maintain its data warehouses. As most of the data that banks and financial institutions deal with are the transactional information of the customers, focusing on privacy concerns is thus even more necessary. It will help the organization safeguard its goodwill while adopting better business strategies and confirm that none of its customers are at risk.