Banking is one of the most data-intensive industries of the present times. With massive volumes of unrewarding data, one of the major challenges is to manage these data using conventional methods. Therefore, financial institutions are leveraging advanced data analytics to scale operations and enhance profitability. From providing better market insights to improving customer satisfaction ratio, these innovative data mining and data analytics processes have streamlined risk management besides preventing frauds in the banking sector.
Looking at the current scenario, the top financial institutions aim to comprehend the requirements of their customers better and provide them with viable solutions readily. To accomplish the same, they are leveraging data analytics in banking with predictive analysis and multivariate descriptive analytics as its chief components.
It is important to note that the usage of data analytics in the banking sector was not unknown. However, with the advent of sophisticated data tools and processes like Teradata to Azure migration, things have accelerated beyond measure and provided the banking institutions with the much-needed agility. Today, the capabilities of data analytics have boosted the customer profitability of the banking institutions and helped them expand into new markets, which was not possible earlier. For instance, Bank of America, has been leveraging Hadoop technology to manage their complex data operations, resulting in necessary reforms that function following the rules set by the new regulatory authorities. Furthermore, from the prevention of duplicate data systems to the reduction in manual efforts, data analytics has also improved the operational efficiency of the banking institutions manifold.
Banking institutions are most susceptible to fraudulent activities. Using data analytics in banking, frauds can be easily detected. The following practices showed astounding results in combating bank-related frauds:
- Calculation of statistical parameters
- Data classification and stratification
- Digital analysis
- Duplicate and gap testing
- Data validation
- Customer analytics
Banking institutions are gradually recognizing the importance of data analytics, and are, thus, streamlining the core challenges such as unstructured data, data fragmentation, lack of skilled human resources, etc.
If you are looking forward to the best data analytics solutions in banking, Impetus Technologies can provide you with the necessary assistance. With strategic data methodologies that are easy-to-comprehend, it offers you a required framework that leads to cost-efficiency and ensure that you start to achieve better results for your banking business in no time.