The banking and financial industry is currently going through a process of overwhelming changes. These changes range from asking advice from a robot to insurance assessment using drones. Customer’s expectations have also changed greatly. They expect a more secure hassle free transaction in less time. The bank and financial services are aware that to be able to survive in a constantly evolving scenario they need to evolve as well. They know that they need to improve their operational efficiencies, fraud detection system, risk management and customer services.
At the center of every financial activity is the financial and private data from a customer, the need to store and protect it securely and also to gain leverage from this is increasing its importance every minute. More and more consumers are sharing their financial data online with the bank, financial technology firms and sometimes with tech giants like Facebook. In a situation like this, big data, machine learning, and advanced data analytics have become the major determining force to keep the competition alive among the financial services businesses.
You need to be vigilant at all time
The financial services industry and banking is the one industry where any criminal activity can destroy the reputation of the whole. In 2016, banks in Australia were attacked by malware and hackers could access to online financial credentials of thousands of customers. Banks and financial institutions are working day in and out to avoid dangerous situations like this.
Advanced application of Machine learning framework to engage data from various sources could enable businesses to track irregular activities in real-time, which could prevent any potential security attacks or criminal activity from taking place. Taking account of data in real-time and acting upon them would be a big advantage that can put the financial institutions one step ahead of the criminals. Analysis of both operational and analytical data and converge these into a single platform will help to anticipate attacks and proactively take precaution against them.
Targeted marketing will be more effective
Meaningful Big data analytics will also provide banks and financial institution the opportunity to create targeted marketing efforts. The analysis of the data will help identify segments of the different customer base.
Financial services businesses will be able to understand their customers at a micro level and should help them to create relevant, personalized and contextual communication content through leveraging data. A brand communicates strong effective message to their targeted audience and thereby increasing the conversion rates, customer base, and lifetime value. A big data platform allows businesses to do segmentation much more quickly and efficiently than legacy tools that utilize the resource to the max.
Optimizing the customer experience and keeping the customer loyalty
The biggest challenges of this digital age are to keep the customers happy and engaging. In most of the cases, banks or financial institutions do not need to physically meet the customers, so it has become more important to keep the relationship with their loyal customers and ensure their satisfaction.
Customer satisfaction is the most important area if the businesses would want to be a step ahead of their competitors. The key focus is on personalization and customization and data from a customer will surely helping the bank to have a 360-degree view of their customers. Technological advancement has made it possible to maintain a very personalized relation with every customer, for example like the “virtual bankers” which one of the banks from Australia is planning to do.
Big data gives you a single platform for analytics that also gives the power to combine data exploration, access, integration, and storage scalability. Businesses should be able to draw effective insights from big data analytics to boost up their profit and also to stay ahead of their competitors.