Embracing Customer Experience and Loyalty in Banking: IPS Consulting’s Approach to 2025

As we step into 2025, the banking industry faces a critical challenge: how to regain customer loyalty amidst growing digital interactions. With customer satisfaction scores declining, many banks find themselves at a crossroads, needing to innovate to survive. A purely digital, transactional approach no longer suffices for retaining loyalty—what’s required is an integrated experience that blends both technology and human interaction.

At IPS Consulting, we’ve developed a customer-first model designed to address these evolving challenges by merging cutting-edge technology with a deep commitment to customer engagement. We understand that the voice of the customer is essential for driving not only satisfaction but also long-term loyalty. In this blog, we’ll outline our framework that empowers banks to embrace CX, customer voice, and loyalty while seamlessly integrating technology for enhanced service delivery.

The IPS Consulting CX-First Framework: A Model for Success

To meet the demands of today’s tech-savvy customer, banks need more than just digital solutions; they need a comprehensive, adaptable approach to customer experience. IPS Consulting has developed a framework that emphasizes customer-centricity by leveraging AI, data analytics, and real-time communication, creating a hybrid experience that combines both digital and human touchpoints. Here's how our model works:

1. CX Strategy & Integration: Technology That Enhances Human Connection

Banks must deliver personalized experiences at scale, and that’s where IPS Consulting’s CX strategy comes in. By integrating AI-driven insights, data analytics, and cloud solutions, we empower banks to engage customers via their preferred channels—whether through chatbots, mobile apps, or live support. Our approach ensures that every interaction adds value and aligns with your customers' preferences, enhancing their overall experience.

Through seamless technology integration, we create an environment where customers feel heard, valued, and understood. By tapping into the power of AI, banks can proactively offer solutions, anticipate needs, and resolve issues before they escalate. This ensures that technology serves as a tool for enhancing human connection rather than replacing it.

2. Customer Feedback Loop: Listening and Adapting in Real-Time

Customer feedback is the backbone of an effective CX strategy, and in our model, it is a continuous, evolving process. We implement feedback systems that actively capture customer concerns, needs, and suggestions, enabling real-time adjustments to products and services.

By analyzing customer feedback using advanced data analytics tools, banks can immediately identify pain points and swiftly adjust operations to improve the customer journey. Our integrated systems ensure that every piece of feedback is logged, reviewed, and acted upon quickly, closing the feedback loop and driving continuous improvement.

3. Loyalty and Trust Building: Cultivating Long-Term Relationships

In today’s competitive market, fostering loyalty is more than just about providing services—it’s about building trust. IPS’s model is designed to create an emotional connection with customers, which is critical to retaining their business. Our AI-powered solutions enable banks to offer immediate, empathetic responses, while our seamless digital and human interaction channels ensure customers feel supported at every step of their journey.

By combining personalized services with responsive, real-time problem-solving, our framework ensures that customers see tangible value in their relationship with your bank. When customers feel confident that their bank is there for them—whether through 24/7 chat support, secure transactions, or personalized financial advice—they become not only loyal but also strong advocates for your brand.

The Future of Banking with IPS Consulting

The need for transformation in the banking industry is clear. Banks must evolve to meet the changing expectations of their customers while embracing new technologies that enable growth, efficiency, and security. IPS Consulting’s CX-first framework empowers financial institutions to stay ahead of the curve by creating personalized, scalable solutions that improve customer satisfaction and loyalty.

Our approach is flexible, designed to work seamlessly with your current systems, and scalable to grow with your business. We focus on aligning technology with human interaction, ensuring that every customer feels valued and supported. This is not just a short-term fix but a long-term strategy that positions banks for success in an ever-evolving landscape.

Ready to transform your customer experience and drive growth in 2025?

Contact IPS Consulting today to learn more about how our CX-first framework can help your bank or financial institution innovate, enhance customer loyalty, and stay competitive in a rapidly changing industry.

A Practical Guide for Business Leaders on Data Modernization

Business leaders often hear terms like 'data modernization,' 'digital transformation,' and 'cloud migration' tossed around, but too often, these terms are used interchangeably—and incorrectly. The reality is, each represents a different strategy with its own set of actions and benefits.

For many leaders, the challenge lies in clearly defining what 'data modernization' means for their organization. They know it’s important, but how does it align with their business vision? Where do you begin? How do you ensure your data infrastructure supports your business objectives and avoids costly mistakes?

This practical guide will walk you through the steps to effectively modernize your data systems, select the right tools, and implement a strategy that scales with your business growth.

What is Data Modernization?

Data modernization is about updating your data governance and management practices to align with both current and future business needs. This process focuses on adopting the right technologies to streamline how your organization collects, processes, stores, and analyzes data. It may involve migrating to cloud solutions, replacing outdated systems, or integrating advanced analytics capabilities.

It’s important to understand that there’s no single definition of a "modern" data system. Many companies are already in the process of modernizing their data systems, though they may not always be doing so intentionally. Effective data modernization should aim to achieve two primary goals:

1. Ensure data architecture supports business objectives.

2. Build a flexible, scalable, and future-proof infrastructure.

Align Data Architecture with Business Objectives

Modern data architecture must align with business objectives. This means creating a framework that integrates IT strategy with business strategy. Effective data governance requires aligning people, processes, and tools to ensure each supports the other. When these components work in harmony, the organization can leverage data-driven insights to drive business growth and operational efficiency.

Data architecture defines how a company collects, stores, manages, and utilizes data. As the business evolves, the data infrastructure should scale accordingly. For example, a business expanding through acquisitions will need a flexible data framework to integrate diverse systems, while a more stable business might focus on ensuring reliability and consistency across data processes.

A Secure Yet Flexible Approach: Medallion Architecture

A critical element in successful data modernization is Medallion Architecture, which ensures data systems align with business objectives while maintaining security and flexibility. This approach uses different levels of data refinement—typically referred to as the gold, silver, and bronze layers—to protect valuable data while allowing experimentation with less critical information. The gold layer is reserved for mission-critical data, requiring the highest levels of security and governance. For example, in industries like financial services or high-frequency trading, where data accuracy and uptime are crucial, stringent governance frameworks are essential to mitigate risk.

In contrast, businesses focused on growth and innovation can take a more flexible approach with the silver and bronze layers. These layers allow for rapid iteration and experimentation, with fewer constraints, to foster innovation. Silver layers contain cleaned, enriched data suitable for analysis, while bronze layers include raw, unprocessed data used for testing and development. Once the layers are defined, the next step is selecting the right tools and platforms that support each layer’s specific requirements, ensuring seamless execution of your data modernization strategy.

Finding the Right Tools for Modern Data Architecture

Building an effective modern data architecture starts with selecting the right tools that streamline data management and analysis. Many of today’s best platforms have evolved from early frameworks like Hadoop, which was initially groundbreaking for handling massive datasets across multiple servers. However, Hadoop’s complexity and high maintenance costs made it impractical for today’s fast-paced business needs. Modern tools such as Microsoft Fabric, Snowflake, and Databricks have redefined how businesses store, manage, and analyze data. These platforms are faster, scalable, and more cost-effective, allowing businesses to gain real-time insights, improve operational efficiency, and respond quickly to market changes.

Microsoft Fabric, for instance, integrates various tools from Microsoft's cloud platform into one unified system, providing real-time insights from raw data almost instantly. Unlike batch processing, which can take hours, Fabric enables businesses to make data-driven decisions quickly. Snowflake is a leader in cloud-based data solutions, offering simplicity, scalability, and seamless interoperability with other platforms. It’s ideal for companies that need to grow and adapt rapidly. Meanwhile, Databricks, built on Apache Spark, excels in processing large datasets and supports businesses focused on AI and machine learning to uncover trends and predictive insights. When selecting the right tool for your data modernization journey, ask key questions: Does your business need real-time data processing? How scalable are the tools for future growth? Does your team have the expertise to maximize the tool’s potential, or will training be necessary? Consulting with trusted technology advisors can ensure you choose the right solution tailored to your unique needs.

How to Modernize Your Data on a Budget

Business leaders have traditionally hesitated to invest in data modernization due to the high upfront costs and the risks associated with the "big bang" approach—where companies made large investments only to face long timelines, unforeseen challenges, and unclear ROI. This approach is now considered outdated. At IPS Consulting, we advise a shift toward scalable, sustainable, and customized data modernization strategies. Modern data solutions are adaptable, allowing businesses to start small and scale as needed, without the burden of massive initial investments. By taking an iterative approach, organizations can manage their budget more effectively while driving value from day one.

When evaluating data solutions, it's crucial to focus on results-driven value. Before committing significant resources, ask your vendors and internal teams to answer the following questions: Why is this investment critical now? Which pricing tier strikes the best balance between cost and functionality? What is the expected timeline for measurable returns? By defining clear outcomes and breaking the process into smaller, manageable phases, you can ensure that the chosen solution delivers real value early on. Platforms like Microsoft Fabric, Snowflake, and Databricks are well-suited to this flexible, scalable approach, allowing you to expand your capabilities progressively without the need for large upfront commitments.

Our Rule: Embrace Change, Don’t Force It

We believe in driving change through collaboration, not imposition. When modernizing data systems, it’s essential to engage your team and stakeholders early, ensuring they understand the value behind each decision. Change should always enhance efficiency and functionality—never disrupt established processes without clear improvement. If a tool or system is to be replaced, it should be because it genuinely adds value, not just because it's the latest trend. By respecting the existing tools your team relies on, and carefully introducing alternatives with clear benefits, you foster a culture of thoughtful, impactful innovation that aligns with your business goals.

The Path Forward

Modernizing your data goes beyond simply implementing new technologies—it’s about creating meaningful value for your employees and customers. When users see that a system enhances their workflow or simplifies their tasks, adoption becomes seamless. There’s no need to enforce the use of the latest tools; instead, employees will naturally embrace solutions that address real, everyday challenges.

By focusing on the core priorities of your business, you can develop a data strategy that not only modernizes your operations but also cultivates trust and loyalty within your team, fostering long-term success.

Empower Your Nonprofit with Modern Data Solutions

we helped a Jewish philanthropy nonprofit modernize its data infrastructure, streamline operations, and scale their network. Read the Full Story to see how we can help your organization achieve similar success.

Artificial Intelligence on AWS: Ensuring Secure Generative AI Adoption

Generative artificial intelligence (AI) is revolutionizing industries with its ability to create content, generate realistic models, and enhance decision-making. However, as adoption accelerates, security professionals urge caution. AI-driven innovations are not without their risks—data privacy issues, model bias, harmful content creation like deepfakes, and malicious input influencing AI models are all concerns that require careful consideration.

IPS Consulting is here to guide you through the key protective measures necessary for securely adopting generative AI. If you're looking to integrate generative AI on AWS while maintaining security, privacy, and compliance, here are four crucial questions you must address on your journey.

1. What Do You Need to Protect?

The first step in securing any AI deployment is understanding what’s at stake. For generative AI, this extends beyond data and models to include the intellectual property and content generated by the system. Protecting sensitive data, including training datasets and user-generated content, is critical to avoid exposure to proprietary or personal information. AWS offers strong encryption options, such as AWS Key Management Service (KMS) and AWS Identity and Access Management (IAM), to safeguard data at rest and in transit.

Key Actions:

• Classify and categorize the data you’ll be using for AI models.

• Implement strong access controls and audit mechanisms.

• Ensure all datasets, especially sensitive ones, are encrypted.

2. How Can You Help Maintain Compliant Performance?

Compliance with industry regulations, such as GDPR, HIPAA, and CCPA, is non-negotiable. Generative AI models can potentially expose organizations to compliance risks if sensitive data is mishandled or if AI-generated content violates privacy laws. AWS’s compliance tools, like AWS Artifact and AWS Config, can help you map your AI workloads to relevant regulatory standards, track your compliance posture, and manage risks.

Key Actions:

• Use AWS compliance resources to ensure alignment with regulations.

• Regularly audit and monitor model activities for compliance.

• Document and track all data handling and usage procedures.

3. How Can You Ensure the Models Perform as Intended?

Generative AI models can exhibit unexpected behaviors if not properly trained or monitored. Ensuring that models produce outputs aligned with business goals, ethical standards, and security requirements is essential. AWS services such as Amazon SageMaker and Amazon Rekognition can help with training, testing, and validating AI models in a secure environment, reducing the likelihood of unintended outcomes.

Key Actions:

• Implement model monitoring and evaluation mechanisms.

• Conduct regular bias and fairness assessments.

• Use AWS’s AI model versioning and rollback features to revert to trusted models if necessary.

4. Where Should You Start?

Starting with AI adoption on AWS requires a phased approach. Begin by identifying high-priority AI use cases that align with your business needs. Build a proof of concept (PoC) to assess feasibility, followed by small-scale experiments before full-scale deployment. AWS offers a wealth of tools to help you scale AI workloads securely, including AWS AI & ML services like Amazon Polly, Lex, and Comprehend, along with detailed security configurations.

Key Actions:

• Identify your most impactful AI use cases.

• Build a PoC to test generative AI securely.

• Leverage AWS’s security framework to scale AI securely.

Conclusion

Generative AI holds incredible potential, but integrating it securely and responsibly requires careful planning and the right tools. By addressing these four questions, you can ensure a secure, compliant, and effective AI adoption journey. At IPS Consulting, we specialize in helping organizations manage AI risks, ensuring that you can leverage the power of AWS’s generative AI tools while maintaining the highest standards of security and compliance.

Ready to explore secure AI integration with AWS? Talk to IPS Consulting today about how we can help you build robust, compliant, and secure AI systems for your business.

IPS Consulting Blog: Share Thoughts, Stories, and Ideas

Welcome to the IPS Consulting Blog—a space for sharing ideas, stories, and insights. We believe in the power of collaboration, where diverse perspectives come together to spark meaningful conversations on business transformation, technology, and strategy.

Here, we explore industry trends, client success stories, and the experiences of our talented team. We aim to provide valuable content that inspires, educates, and encourages innovation within our field.

We invite you to join the conversation! Share your thoughts, ideas, and stories with us. If you'd like to contribute, reach out at info@ipsglobalconsulting.com. Let’s create, learn, and grow together.