Traditionally, businesses differentiated their markets based on price, product, or location. Today, the power of customer experience stands front and center as a defining competitive differentiator across industries, especially in the banking sector. Statistical evidence proves that elevated customer experience or CX enables long-term and sustained success.
Research shows that organizations that focus on customer success and improving customer experience grow 3.2X faster than those organizations that don’t as the age of hyper-personalization and on-demand services take over. Enhancing customer experience becomes even more essential for banks in the face of a dynamic and uncertain macroeconomic environment, rising digitization, and shifting financial practices.
The commitment to improved customer experience emerges as the most impactful differentiator in a competitive market. Along with this, banks need to increase their profitability.
In the Race for CX, Data Leads the Way
As customer experience becomes a competitive differentiator, data emerges as the backbone supporting it. Research has previously shown that data-driven organizations are:
23 times more likely to acquire customers
6 times more likely to retain customers
19 times more likely to be profitable
The writing is on the wall — the key to winning today and tomorrow lies in data.
Big data and data analytics are essential technologies that offer deep, clear, and actionable insights into user behavior and help banks optimize customer experience by elevating the entire banking experience.
Big data can elevate the banking experience in the following ways:
Improving Customer Profiling
Customer segmentation and profiling play a big role in elevating the banking experience. Big data provides information granularity that helps identify customer expectations, wants, and needs.
With big data, banks can better profile customers and segment them according to multiple parameters such as demographics, number of accounts they use, product use, declined offers, financial health, behavior patterns, etc.
Banks can proactively and contextually engage with customers with precise segmentation and granular insights.
Delivering Seamless Multi-Channel Experiences
Customers now leverage several channels to engage with banks to find information, conduct banking activities, or make transactions. Insights on the entire customer journey from the web and mobile usage are beneficial to determine the smoothness of the journey.
Big data helps banks fine-tune processes and create smooth digital customer experiences by pointing out roadblocks preventing seamless interactions across the customer journey.
Discovering Time-Sensitive Opportunities
Big data and predictive analytics infuse more agility into banking activities and operations. These can deliver more intuitive, Netflix-like interactions and help banks with time-sensitive opportunities by analyzing user behavior and other influencers.
These technologies help banks better understand customers and proactively meet their real-time needs. Big data analytics captures tons of raw data, tears down silos that impact customer experience, and reviews thousands of data points in real-time to understand customers.
Technologies such as NLP and ML give deeper behavioural analysis and allow banks to discover behavioural patterns that help them connect with the customer contextually and at the most opportune moment.
Prioritizing and Acting on Issues Based on Revenue Impact
Big Data analytics tools help banks allocate resources where they will have the most significant impact. Technologies like ML and NLP make creating personalized experiences easier, nurturing long-term relationships and allowing banks to prioritize and act on issues based on revenue impact.
These technologies allow banks to anticipate customers’ financial goals and develop proposals that are aligned with these. They also help banks identify the most pressing challenges that impede customer experience or identify processes that need improvement and divert funds most appropriately.
Improving Risk and Regulatory Compliance and Information Security
Big data analytics increases cybersecurity and helps banks adopt a more proactive posture toward regulatory compliance and security. This directly impacts customer experience significantly as concerns of data theft increase and cyber threats increase in sophistication. Adopting an aggressive security stand earns extra brownie points as it:
Contributes directly towards customer trust
Reduces chances of business disruption
Ensures compliance that further strengthens customer stickiness
Big Data in Banking – A Valuable Resource
Data volume, velocity, and complexity have exploded due to the rise of digital technologies. Therefore, the following are essential to generate value for big data:
Having the right tools and technologies to manage vast amounts of structured and unstructured data
Identifying the best way to manage this data
Removing silos by creating the best data lakes
The role of the cloud in accelerating computing and data processing should also be addressed. However, in the big data journey, pay attention to the following:
Creating the Right Big Data Implementation Roadmap
Creating the right big data implementation roadmap becomes crucial for banks when they embark on the big data journey. This ensures minimal disruption and makes technology adoption risk-free. Having a clear roadmap with defined objectives also makes it easier to identify the best tools and accelerators, such as cluster sizing tools, performance tuning guidelines, and Hadoop migration methodology — allowing rapid turnaround while achieving business objectives.
Managing big data well also solves operational challenges, increasing the need to focus on monitoring and supporting the big data infrastructure. Streamlining big data operations becomes crucial for real-time insights and improving the total cost of ownership.
Creating Perfect Data Lakes
The large volumes of structured and unstructured (PDFs, docs, emails, social media, etc.) data need a centralized repository to improve information access, drive robust analytics, and enable real-time decision-making.
Designing the right data lake helps banks leverage cloud, ML, and NLP technologies to arrive at analytics and the associated use cases. This also simplifies data extraction (web, log files, social media, pdfs, etc.) from external sources and data parsing using NLP techniques and ML algorithms. It further allows enterprises to model data according to business-specific models.
Data lake security and governance for on-premise and on-cloud implementations also become critical to driving bank customer experience.
Robust Cloud Implementation
The right cloud architecture and implementation are important as banks look at elevating the customer experience and delivering differentiated experiences.
Using cloud technology appropriately, creating the right infrastructure, building solutions with the most appropriate services on the cloud, and managing and supporting the cloud environments post-implementation are essential points of consideration.
These activities serve to:
Ensure that the data is secure both in transit and at rest
Enable real-time decisions
Ensure security and compliance with regulatory bodies/government
Drive better customer experiences
Managing the Legacy Environment
Legacy systems in the banking ecosystem can impede banking agility, velocity, and responsiveness and impact customer experience negatively. However, given a tough regulatory landscape, leveling this legacy environment of applications, infrastructure, and technologies must be calculated as heavy lifting.
As mainframe applications, batch processes, and datasets form an integral part of the banking ecosystem, identifying clear modernization opportunities and executing them while maintaining compliance need domain expertise to complement technical expertise.
The Ellicium Advantage
Today’s customer is well-versed with digital experiences. They expect banks to deliver seamless, hyper-personalized, and contextual experiences in this digital world. This is where Ellicium’s big data expertise comes to the fore. We help banks by:
Capably connecting all the dots, which gives them a complete, 360-degree view of the customer.
Creating a healthy big data ecosystem to target and communicate efficiently with customers across relevant channels and eliminate redundancies
We are delivering contextual, timely, and hyper-personalized experiences by upgrading banks’ digital ecosystem and using the data at hand.
All these capabilities come together to serve customers better, improve customer stickiness, and drive business scalability. We can make your considerable data work harder and smarter using our technology and domain expertise.