No matter how we bite it, but data-intensive is what banking industry is. It’s always been tricky to effectively mine important information out of it. Burdened with massive unused data and ironclad management rules, banking sector is facing multiple challenges to mitigate and manage risk, stay profitable and understand customer’s needs and preferences. Given the situation, advanced analytics in banking is to the rescue as now the sector seems anxious for the change.
With the magnificent processing power generated by cloud-based utility computing architectures and revolutionary advances in analytics software, banks can derive better understanding of customer behavior, respond to quickly changing customer preferences, overcome uncertainties and ensure compliance.
Following lines of this article are intended to provide deeper insight into why analytics are much needed in banking:
- The Ever-changing Customer behavior: After the financial crisis of 2008, the banks nearly lost their customer trust and loyalty, resulting in declining customer satisfaction with banks and their changing preferences. The key to success for banks is to retain their customers which make it necessary for banks to tune their strategies to customer-centric. Employing advanced analytics to exploit huge customer data and to understand their behavior will enable the banks to retain their tech-savvy, pragmatic and savings-oriented customer.
- Strategies for long-term solutions and Profitable Growth: As the customer’s preference changes, banks will need to devise better strategies to retain their profitable customers, go beyond historical data and use analytics that can nurture better decision making. To increase the profits, banks can take help from customer’s data and use it to enhance service, improve revenue and address process inefficiencies. As banks need to interact with their customers consistently, data-integration and analytics can facilitate multichannel banking that can facilitate enhanced banking experience.
- Risk management and Regulations: With the huge amount of data that banks deal with every day, it is imperative to maintain transparency and manage the data efficiently as a small mistake may result in huge losses to a bank. This speaks for the necessity to go beyond the traditional risk management techniques with narrow scopes and replace them with sophisticated analytics techniques to consider each risk-return scenario precisely. Another critical activity in banking is Fraud Detection to check the fraudulent activities that happen in bank transactions. Deploying Risk Analysis in banking will promote risk-aware decisions, identify and administer unusual and suspicious activities.
The economic crisis of 2008 led to dramatic expansion in the Regulatory oversight and the cost of compliance in the banking world. Under the heightened regulatory scrutiny, banks need to report the data that is predictive, calculated and risk-based. Analytics can help banks by providing high-quality and accurate data to comply with the radically different and stringent regulatory environment and to improve reporting.
For the banking industry today, Analytics is the most powerful value-creation tool available. Embracing Analytics-as-a-service ensures profitability, compliance, growth by effective decision-making and competitiveness. However, this sector is ready for the change but there may be challenges along the way to adopt new technologies yet we can believe that the better thing will always find its place.