In the fiercely competitive world of banking, products and rates are no longer the sole differentiators. Today, Customer Experience (CX) has become the battleground where loyalty is won or lost. But as CX teams advocate for greater investments in design, technology, and service, business leaders ask a critical question:

❝ What’s the return on investment for improving customer experience? ❞

The answer? When done right, CX isn’t a cost center — it’s a growth engine.

Why CX Matters More Than Ever in Banking

The modern customer expects anytime-anywhere access, hyper-personalized communication, and zero friction across channels — whether digital or physical. But it’s not just about meeting expectations. It’s about understanding how meeting (and exceeding) those expectations impacts key financial metrics.

Let’s break it down:

How Great CX Directly Impacts Business Outcomes

1) Retention and Loyalty Drive Long-Term Revenue

Acquiring a new banking customer costs 5–7x more than retaining an existing one.

• CX initiatives that reduce customer pain points—like streamlining onboarding, improving app navigation, or enabling instant issue resolution—lead to higher retention.
• Loyal customers are more likely to stay through rate fluctuations, new fees, or minor errors.

ROI Link: A 5% increase in retention can increase profits by 25%–95%. That’s direct revenue, saved acquisition costs, and greater LTV.

2) Satisfied Customers Expand Their Relationship

Customers who feel valued are 4x more likely to buy additional products.

• A seamless credit card application, a frictionless mortgage journey, or proactive fraud alerts build trust—and trust builds wallet share.
• Predictive CX, powered by data, enables timely offers: “You’re pre-approved for a home loan” hits differently when it appears just after a customer browses listings.

ROI Link: Higher cross-sell and upsell rates improve revenue per customer and drive down average acquisition cost per product.

3) Digital CX Reduces Cost-to-Serve

A digital transaction costs a fraction of an in-branch or call center interaction.

• But digital migration only works if the experience is delightful.
• Banks investing in user-centric mobile apps, AI chatbots, and seamless KYC verification are seeing massive adoption—and saving millions.

ROI Link: Reduction in branch traffic and support center load leads to direct operational cost savings.

4) Promoters Fuel Organic Growth

82% of consumers trust recommendations from friends and family over ads.

• When customers are happy, they don’t just stay—they recommend.
• A single promoter may bring in 2–3 new customers, and in high-trust domains like banking, those referrals convert faster and churn less.

ROI Link: Higher NPS leads to referral-based growth and reduced acquisition spend.

Proving the ROI: CX Metrics vs. Business KPIs

To make CX investments boardroom-proof, banks must connect experience data with financial impact.

Real-World Examples: CX That Pays Off

DBS Bank

Used customer journey mapping to streamline digital onboarding. Result:

• 3x increase in mobile onboarding
• 30% higher cross-sell in digital customers

Barclays

Introduced personalized financial coaching in-app. Result:

• 15% boost in NPS
• Increased uptake in investment products

ICICI Bank (India)

Revamped WhatsApp banking and chatbot services. Result:

• 60% drop in call center volumes
• $1.2M in annual cost savings

Final Word: CX is Strategy, Not Support

When you invest in customer experience, you’re not just designing better journeys you’re designing better financial performance.

The most future-ready banks are those that:

• Treat CX as a strategic lever
• Build a culture of continuous listening and improvement
• Marry customer insight with business analytics to track ROI

Bottom Line:

Happy customers stay longer, buy more, cost less to serve, and bring in others. That’s not just good CX — that’s smart business.

With 25 years of expertise in BankTech, Maveric Sytstems has been at the forefront of driving transformative solutions in the banking domain. Through the Maveric BankTech Insights newsletter, we bring you deep insights overcome digital friction in Banking that not only attract but also retain and delight customers for the long term.

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The future of work isn’t just automated—it’s intelligent.

As businesses across industries race to digitize operations and improve productivity, automation technologies have taken center stage. But there’s a growing confusion between Robotic Process Automation (RPA) and Intelligent Automation (IA) two terms often used interchangeably, but fundamentally different in capability and impact.

Understanding this distinction is crucial to shaping your automation strategy and unlocking true digital transformation.

What is Basic RPA?

Robotic Process Automation (RPA) refers to software bots that mimic human actions to perform repetitive, rule-based tasks. These bots interact with digital systems just like a human would clicking, copying, pasting, filling out forms, and moving files between applications.

Key Features:

• Works with structured data
• Follows predefined rules
• Doesn’t learn or adapt on its own
• Best suited for high-volume, repetitive tasks

Common Use Cases:

• Invoice data entry
• Employee onboarding processes
• Payroll processing
• CRM data updates

Limitations:

• Can’t handle exceptions or changes in input format
• Not equipped to interpret context or make decisions
• Breaks easily when underlying systems or rules change

Industry Insight:

According to a Deloitte Global RPA Survey, 78% of organizations have already implemented RPA or are in the process of doing so—but nearly half struggle to scale it enterprise-wide due to its limitations.

Why It Matters

The choice between RPA and IA isn’t about replacing one with the other. It’s about using the right tool for the right stage of your automation journey.

RPA is a great starting point. It delivers quick wins and ROI by automating repetitive back-office tasks. But as your business grows, processes become more complex and data becomes more diverse this is where IA becomes essential.

Business Benefits of Intelligent Automation:

• 30–60% cost reduction in operations (McKinsey)
• Up to 50% efficiency gains in complex workflows
• Improved customer experience with real-time, intelligent responses
• Higher accuracy and fewer exceptions requiring human intervention
• Scalability across departments and functions

Final Takeaway

Basic RPA is like a calculator. Intelligent Automation is a data scientist. While both are useful, their capabilities and their value to your business are vastly different.

If you’re automating only simple, structured processes, you’re leaving massive potential untapped. Intelligent Automation allows you to unlock that potential empowering your workforce, streamlining operations, and creating space for innovation.

With 25 years of expertise in BankTech, Maveric Sytstems has been at the forefront of driving transformative solutions in the banking domain. Through the Maveric BankTech Insights newsletter, we bring you deep insights overcome digital friction in Banking that not only attract but also retain and delight customers for the long term.

Wish to know more? Subscribe to our Newsletter

The pricing landscape for customer experience (CX) technology is rapidly evolving, as traditional models are being replaced by more flexible, scalable options that better align with the needs of today’s businesses. Historically, CX solutions relied heavily on large, upfront license fees, but the growing demand for agility, scalability, and cost predictability has pushed the industry towards subscription-based, cloud-enabled models.

Companies are increasingly seeking pricing structures that allow for greater flexibility, enabling them to pay for only what they use, while also aligning costs with business outcomes. This shift is driven by several key factors: the rise of cloud technologies, the preference for subscription models, and a focus on performance-based pricing. Below are the main pricing models reshaping the future of CX tech:

• Subscription-Based Pricing
  Moving away from one-time licenses, subscription models provide a recurring, predictable cost structure that gives businesses access to ongoing updates and new features without large, upfront investments.

• Cloud-Based Flexible Pricing
  Cloud-based solutions offer pay-as-you-go models, which allow businesses to only pay for what they use, offering greater flexibility and cost control as CX needs fluctuate.

• CapEx to OpEx Shift
  The shift from capital expenditures (CapEx) to operational expenditures (OpEx) allows businesses to spread out costs over time, aligning spending with actual usage and providing financial flexibility.

• Outcome-Based Pricing
  Pricing tied to the achievement of specific business outcomes, such as customer satisfaction or retention, ensures that companies only pay for results, aligning vendor incentives with customer success.

• Use-Based Scalable Pricing
  This model adjusts pricing based on actual usage, making it easier for businesses to scale their CX investments according to demand and ensuring they only pay for what they need.

• Integrated Stack Pricing
  Bundling multiple CX technologies into one integrated solution simplifies vendor management and provides a more competitive price point, offering a holistic approach to customer experience.

Market Insights: Key Industry Stats

• Subscription Models Growth: According to Gartner, 75% of CX tech providers are now offering subscription-based models, up from just 40% in 2020.
• Cloud Adoption: A report by Forrester found that 70% of businesses have shifted to cloud-based solutions, with 80% of CX investments expected to be cloud-centric by 2026.
• CapEx to OpEx Shift: A study from Deloitte revealed that 62% of businesses are prioritizing operational expenditure models over capital expenditures for IT solutions, citing greater flexibility and reduced risk.
• Outcome-Based Models: Research from McKinsey shows that 48% of CX tech buyers now prefer outcome-based pricing, focusing on results and performance rather than flat fees.
• Usage-Based Pricing: 60% of organizations surveyed by IDC report that scalable, usage-based pricing is crucial for managing budgets and adapting to fluctuating demand.

Best Practices: Navigating the Shift in CX Tech Pricing

• Understand Your Needs: Choose pricing models based on your company’s growth trajectory and specific CX goals. Subscription and usage-based models offer flexibility but require clear alignment with customer demands.
• Embrace the Cloud: With more organizations moving to the cloud, ensure your CX solutions are cloud-enabled to take advantage of flexible, scalable pricing options.
• Focus on Outcomes: When considering pricing structures, focus on the value delivered—outcome-based models can align costs with actual results, making them a compelling choice for performance-driven teams.
• Leverage Integrated Solutions: Integrated stack pricing can offer significant cost savings and simplify vendor management by consolidating CX technologies under one umbrella.

Future Trends: What’s Next in CX Tech Pricing?

As the CX tech landscape continues to evolve, several emerging trends are set to shape pricing models in the coming years:

• AI-Powered Dynamic Pricing
  With the rise of AI and machine learning, CX tech providers will likely begin to offer dynamic pricing models that adjust in real-time based on customer data and usage patterns. These models will enable businesses to optimize their spending based on actual CX performance, making pricing more personalized and aligned with specific needs.

• Greater Customization in Pricing Structures
  As companies increasingly demand tailored solutions, we can expect to see more highly customized pricing models that fit specific industries, business sizes, or use cases. Providers will likely offer more modular pricing options, allowing businesses to select the features or services they need and only pay for what they use.

• Blockchain for Transparent and Secure Pricing
  The adoption of blockchain technology could lead to more transparent and secure pricing models. By leveraging blockchain’s decentralized nature, CX providers can offer transparent pricing, reduce fraud, and ensure trust in payment systems, leading to more confidence in pricing structures.

• Sustainability-Linked Pricing
  As sustainability becomes a greater focus for companies, we might see pricing models that are linked to sustainability outcomes. For example, providers could offer discounts or incentives to businesses that meet certain sustainability benchmarks, aligning financial incentives with environmental goals.

• Predictive and Outcome-Driven Pricing
  In the future, predictive analytics and outcome-driven pricing could become the norm. Businesses might only pay based on predictive metrics of success, such as customer retention or lifetime value, allowing for a more proactive approach to CX spending.

With 25 years of expertise in BankTech, Maveric has been at the forefront of driving transformative solutions in the banking domain.
Through the Maveric BankTech Insights newsletter, we bring you deep insights  overcome digital friction in Banking that not only attract but also retain and delight customers for the long term. Wish to know more? Subscribe to our Newsletter

AI is reshaping the banking landscape by driving efficiency, enhancing customer experiences, and improving decision-making across the industry. However, banks are at varying stages of AI adoption. To stay competitive, it’s crucial for banks to assess their current stage of AI maturity and strategically prioritize AI use cases that align with their specific goals.

This article will guide banks through the four stages of AI adoption: Exploration, Adoption, Integration, and Transformation, and will help them prioritize which AI use cases to apply across the commercial banking value chain.

Market Insights: AI Adoption Trends in Banking

1. AI Adoption Rate: According to McKinsey, over 70% of global banks are in the early stages of adopting AI, with a focus on automating customer service, fraud detection, and loan decisioning.
2. Customer Experience: A PwC study shows that banks utilizing AI-powered virtual assistants have seen a 30% increase in customer engagement and a 15% reduction in operational costs.
3. Fraud Prevention: AI-based fraud detection is proving successful, with financial institutions reducing fraud losses by 40% over the last 3 years. (Source: Accenture)
4. Risk Management: AI-driven risk management solutions are estimated to save banks $450 million annually by 2025. (Source: Deloitte)
5. Revenue Impact: Capgemini predicts that AI will contribute to a $1.1 trillion increase in global banking revenues by 2025.

Prioritizing AI Use Cases Based on Your Bank’s AI Stage

As banks move through the stages of AI adoption, it’s essential to prioritize use cases that match their current maturity level. Here’s a suggested approach:

• In the Exploration Stage, banks should focus on simple automation and customer interaction tools like chatbots and synthetic data to test responses and build a foundational understanding of AI’s potential.
• In the Adoption Stage, banks can begin integrating AI into key operational areas like loan decisioning, fraud detection, and personalized business insights to improve efficiency and customer engagement.
• In the Integration Stage, banks should expand their AI capabilities to more advanced areas such as real-time credit risk assessments, dynamic payment routing, and AI-powered customer support to optimize operations and enhance service delivery.
• In the Transformation Stage, banks can fully harness AI for continuous innovation, AI-powered omni-channel onboarding, and strategic decision-making, creating a seamless, highly personalized banking experience for customers.

Conclusion: Aligning AI Adoption with Strategic Goals

AI adoption is not a one-size-fits-all approach. By understanding where your bank stands in the AI adoption journey, you can better prioritize use cases that align with your current capabilities and business objectives. Whether you’re just starting with customer service automation or advancing to AI-driven strategic decisions, prioritizing AI use cases at the right stage will help your bank stay competitive, improve operational efficiency, and enhance customer satisfaction.

With 25 years of expertise in BankTech, Maveric has been at the forefront of driving transformative solutions in the banking domain.
Through the Maveric BankTech Insights newsletter, we bring you deep insights  overcome digital friction in Banking that not only attract but also retain and delight customers for the long term. Wish to know more? Subscribe to our Newsletter

Spotlight:

The way banks organize their IT teams are fast transforming. Traditionally, Application development and Operations teams are organized in silos with clear responsibilities around development and support activities (further classified between Infrastructure and applications). This segregation leads to disconnected teams with different priorities, inefficiencies, slow response times, and bad customer experiences.

Creating a cross functional team for managing changes and operations has got its own benefit. According to a study from McKinsey, with cross-functional teams managing development, support, and operations, we can resolve technical issues 30% faster, ensuring minimal disruption and a more seamless customer experience.

A cross-functional model is an autonomous self-sustaining model with capabilities from multiple disciplines organized for every value stream that matters to business. These teams will have roles with clear segregation of duties, coming together to handle operational issues, reliability/ availability issues, changes to be addressed in systems running in production environment. They collaborate heavily with a dedicated development teams that work on long term/ futuristic feature additions and large transformation programs.

Cross Functional Business-first AMS Model

Cross-functional organizations, eliminate the inefficiencies of multiple handoff that result in productivity lapses impacting end customer satisfaction. Cross functional organizations seamlessly integrate the engineering skills in the operations teams, thereby ensuring not only the reliability and availability of the platform but also significantly reducing the lead time for critical issues. Availability of moder observability solutions deliver right insight about the topography while Introduction of AI, accelerates the speed of delivery. This whole chain come together effectively to make sure that the business is able to focus on what matters to them, and measure them effectively, instead about worrying about the system efficiency.

For ex:- lead time reduction in loan disbursal and hence increase in customer satisfaction could be an important metric that matter to a bank. When the Engineering and Operations work collaboratively in ensuring this happens, the business KPI becomes completely traceable to the engineering and operation metric that can help in achieving significant result around the KPI.

Best Practices:

To successfully implement a unified AMS model, consider these best practices:

• Cross-Functional Teams: Factor Engineering, tooling and Functional skills as part of the team in addition to the traditional operations skill.
• Integrate SRE into Production: Site Reliability Engineering (SRE) should be an integral part of the production support teams.
• Focus on Business Metrics: Tracking technical metrics as the reflection of the operational efficiency could lead to “watermelon effect” trap. Track KPIs that matter to the business and establish clear traceability of these metrices to IT systems.
• Leveraging AI and Machine Learning for Optimization: Adopt AIOps as a means for optimizing operations and create ML models that can learn from historical data and make meaningful insights on the situation.
• Create Innovation Councils: Create joint innovation councils for democratising the process of idea generation and implementation. Reward top ideas that make tangible impact to business.

Closing Thoughts:

As the landscape of AMS continues to shift, businesses must adapt to stay competitive. Moving from a siloed approach to a unified cross functional organization structure focused on business outcomes will not only improve operational efficiency but will also create more value for customers and stakeholders alike.

With 25 years of expertise in BankTech, Maveric has been at the forefront of driving transformative solutions in the banking domain.
Through the Maveric BankTech Insights newsletter, we bring you deep insights  overcome digital friction in Banking that not only attract but also retain and delight customers for the long term. Wish to know more? Subscribe to our Newsletter

Spotlight: Key Metrics That Drive Impact

In today’s competitive banking landscape, CXOs, including Chief Customer Officers (CCOs), Chief Operations Officers (COOs), Chief Digital Officers (CDOs), and Vice Presidents of Customer Experience, are at the forefront of driving innovation and optimizing customer experiences. To stay ahead, these leaders must focus on key performance metrics that directly impact customer satisfaction, loyalty, and long-term business growth.

Why Focus on these?  

• Banks with high NPS scores grow 2x faster than their competitors. 
• 81% of customers prioritize the ease of resolution when it comes to satisfaction.
• Focusing on metrics like FCR and CES helps boost retention and improve customer loyalty 

Market Insights: What the Data Reveals

Here’s the current state of the banking industry: 

• Digital Transformation: 73% of customers prefer digital banking channels, with mobile app usage growing by 50% in 2023. 
• Churn Rates: The average annual churn rate stands at 11%, with poor customer service being the leading cause for customers leaving their banks. 
• Personalization is Key: 68% of customers say personalized experiences greatly enhance their satisfaction, but only 30% of banks are utilizing advanced personalization strategies. 

Key Takeaway: Banks that invest in digital innovation and personalized customer experiences are securing customer loyalty. 

Best Practices: How to Improve Your CX Strategy

Looking to enhance your CX metrics? Here are effective strategies to implement: 

1. Streamline Processes: Simplify account opening, loan applications, and issue resolution to reduce customer effort.
2. Utilize Data Insights: Leverage analytics to pinpoint pain points and create personalized interactions.
3. Empower Your Team: Provide frontline staff with the tools and training needed to resolve issues on the first point of contact.
4. Invest in Digital: Upgrade your mobile apps and online platforms to meet increasing customer expectations.

Pro Tip: Banks with FCR rates exceeding 85% see a 10-15% improvement in retention. Focus on resolving issues swiftly and effectively. 

Future Trends: What’s on the Horizon for Banking CX

The future of CX in banking is all about innovation and anticipation. Here’s what to watch for: 

• AI-Driven Personalization: Artificial intelligence will power highly personalized experiences, offering tailored product recommendations and predictive support.
• Voice and Chatbot Banking: By 2026, 60% of banking interactions are expected to be managed by AI-powered chatbots and voice assistants.
• Proactive Customer Service: Banks will move from a reactive to a proactive service model, using data to anticipate customer needs ahead of time. 
• Sustainability-Focused CX: Customers are increasingly choosing banks that align with their values, such as sustainability and ethical practices.

The Bottom Line: Banks that embrace these innovations will be the leaders in customer satisfaction and loyalty moving forward.

With 25 years of expertise in BankTech, Maveric has been at the forefront of driving transformative solutions in the banking domain.
Through the Maveric BankTech Insights newsletter, we bring you deep insights  overcome digital friction in Banking that not only attract but also retain and delight customers for the long term. Wish to know more? Subscribe to our Newsletter