Financial institutions have huge repositories of information in their databases. Before big data came into the picture, this information was not being leveraged to its potential best.

The emergence of big data has effectively enabled the conversion of this information into meaningful insights through application of analytics. This has contributed to accuracy backed strategic decision making. This is not just beneficial to the financial institutions but to the customers as well.

A large percentage of financial institutions that have adopted the use of big data, will experience enormous changes in their industries before the end of the 21st century.

Big data analytics has enabled financial institutions not only to store the data but to aggressively use it to generate business insights, help in decision making and create more value to their customers by offering better financial services. Implementation of big data techniques can enhance the productivity of various areas within financial institutions.

Here are some areas that can benefit from the implementation of big data:

Fraud detection and mitigation

Sophistication in technology is aiding social engineering frauds. The finance industry is highly prone to cyber crimes and we have the technology to blame for it.

But, we also have big data to thank as it can go a long way in mitigating these fraudulent activities.

To begin with, big data has helped financial institutions to be able to detect frauds and terminate it before it causes loss to their systems and to their customer’s information.

Another important aspect that comes with big data is that it has acted as a catalyst in the process of uncovering and mitigation of fraud. Data has also unfolded important patterns that can aid in the uplifting of financial institutions’ security standards enabling them to easily detect any fraudulent activity before it goes out of their hands.

On the other hand, Data analytics has helped financial institutions to distinguish fraudulent transactions from the genuine ones.This has enabled financial institutions to block irregular transactions, thus improving their services to potential customers.

Risk mitigation

The term “finance” can be associated with risks as the industry has several risk factors attached. This could be risks due to uncertainty, volatility, bad loans or unsuccessful investments. Detection of these risks beforehand can help in reducing huge losses.

Financial institutions are obliged to make many agreements to keep their services moving. They must interact with fresh investors to agree on newer financial matters. On the whole, the process of coming into an agreement with the newer investors, financial institutions must make an assessment on the agreements to prevent risks and probabilities of financial harms. Previously, evaluation and assessment of agreements by financial institutions were considered impossible because the information needed for people was always scarce.

Big data has provided an opportunity to obtain a detailed background investigation on these individuals to enable financial institutions to make an informed decision putting all things into consideration. Moreover, big data has helped financial institutions to identify where things might go wrong and where their customers can benefit.

More importantly, the use of big data by financial institutions has enabled them to locate information in a simple way and counter the number of risks. Every information that is necessary to financial institutions is stored in a central platform, therefore, reducing the chances of losing their information as well as their customers’ information.

Learning customers’ expenditure patterns

Financial institutions can use customer transactions to recognize customers’ expenditure patterns. This helps financial institutions understand their prospects’ financial requirements.

Customers’ expenditure patterns also help financial institutions identify their most valued customers. This can be used to pamper your valuable customers with offers.

For the customer, big data can be used to identify huge risk expenditure patterns that can negatively impact customers in the long run.

Financial institutions have various customers with diverse financial needs as well as diverse financial activities. Big data has enabled financial institutions to classify their customers according to these parameters.

Segmentation helps financial institutions in marketing promotions to customers according to the services and the segments. This has helped financial institutions to create enhanced customer relationships.

Big data analytics has helped financial institutions to find out how they can hold their existing customers and entice new ones. In matters of personalized marketing, financial institutions can target their customers based on their buying behaviors.

Wrapping up

Financial institutions have benefited a lot by using data in their day to day financial activities and data has continued to convert the landscape of numerous industries. Various financial institutions are approving the use of big data analytics to sustain competitive edge as well as improve their customer services. However, implementing the use of big data technology requires amplified investments in the technology as well as increased employment of staff with big data skills and knowledge.

Financial institutions must be able to achieve, process, and utilize massive data sets in a quick and healthy manner for successful risk management; nevertheless, financial exploration and training has been slow to talk about the data revolution.


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