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Open Finance: Reality or Hype?

3 minutes read

Open Banking has reshaped the fintech industry. Customers want a seamless experience with more convenient and flexible access to services. Technological innovation and digital transformation have led to the emergence of neobanks which offer a banking experience similar to delivery apps. Now the customers can avail of services like opening an account in minutes. In the last few years, another new concept- Open Finance has joined the queue. What exactly is open finance? Is it just hype or reality? And how open finance might improve customer experience (CX). These are some of the questions that we’re going to talk about in this blog. 

Open Banking

In open banking, banks and other financial institutions allow third-party financial service providers to access the bank’s customers’ data via APIs (application programming interfaces). This helps banks to create more personalized offerings and meet the changing needs of their customers.

What is Open Finance?

Open Banking and Open Finance are similar. However, Open Finance is slightly more advanced in the process. Simply put, it is the next step in open banking. 

Open Finance is a more customer-centric approach. It gives users a safe and dependable way to share their data with the financial tools and apps they prefer to use.

How is Open Finance different from Open Banking?

How is Open Finance different from Open Banking?

Source: Accenture

Open Banking has certain limitations when it comes to sharing of financial data. Here, only that data can be shared which is related to financial operations made within the bank’s app or in a branch office. Open finance goes beyond this limitation.

In Open Finance, non-banking financial data including mortgages, savings, pensions, insurance, and consumer credit – basically your entire financial footprint – could be opened up to trusted third-party APIs if you agree.

Open finance will help open new gateways for financial institutions to improve CX. Let’s dig deeper to understand how this concept will change CX in the Fintech world for the next-Gen customers. 

  1. 360-degree Customer Insights: Data acts as a tool to study deeply about your customers. Organizations can analyze the customer data and extract some valuable insights to design the complete customer journey. Open Finance opens a more secure pathway for financial institutions and gives a more complete picture of their customer’s finances. 
  2. Partnerships & Collaborations: With open finance, comes an opportunity for the financial institutions to network and collaborate with various providers. This means they could deliver a wider variety of services based on consumer data, uncovering new business models and innovations.
  3. Transparency for the Lenders: Lenders can evaluate and measure the creditworthiness of potential borrowers, audit documents, and offer customized solutions by securely collecting customer data. Machine learning algorithms may help to extract valuable insights from raw data.

Open Finance offers freedom and flexibility to consumers giving more options and control over the data they share and how they engage with their finances. With just 8 seconds of attention span, the new age consumers want better experiences to get hooked to one brand. Open finance creates unparalleled access to a broader range of products and services. With data sharing, banking organizations can keep track on the changing customer expectations who want frictionless interactions and hyper-personalized experiences across all touchpoints of the customer journey.

The Road Ahead

Statista predicts that there will be 63.8 million open banking users globally by 2024, increasing at an average annual rate of about 50% between 2020 and 2024. This means there will be more demand for innovative products and services in the industry. Banking organizations would need to analyze the rising customer expectations more closely than ever. And for this, data would act as a key to designing the experience of tomorrow. 

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What’s Next in Cloud Optimization? Can We Optimize Costs Without Sacrificing Performance?

Not too long ago, storing data meant dedicating an entire room to massive CPUs. Then came the era of personal computers, followed by external hard drives and USB sticks. Now, storage has become practically invisible, floating somewhere between data centers and, well, the clouds—probably the ones in the sky. Cloud computing continues to evolve, As cloud computing evolves, optimizing costs without sacrificing performance has become a real concern.  How can organizations truly future-proof their cloud strategy while reducing costs? Let’s explore new-age cloud optimization strategies in 2025 designed for maximum performance and cost efficiency.

Smarter Cloud Strategies: Cutting Costs While Boosting Performance

1. AI-Driven Cost Prediction and Auto-Optimization

When AI is doing everything else, why not let it take charge of cloud cost optimization too? Predictive analytics powered by AI can analyze usage trends and automatically scale resources before traffic spikes, preventing unnecessary over-provisioning. Cloud optimization tools like AWS Compute Optimizer and Google’s Active Assist are early versions of this trend.

  • How it Works: AI tools analyze real-time workload data and predict future cloud resource needs, automating provisioning and scaling decisions to minimize waste while maintaining performance.
  • Use case: Netflix optimizes cloud costs by using AI-driven auto-scaling to dynamically allocate resources based on streaming demand, reducing unnecessary expenditure while ensuring a smooth user experience.

2. Serverless and Function-as-a-Service (FaaS) Evolution

That seamless experience where everything just works the moment you need it—serverless computing is making cloud management feel exactly like that. Serverless computing eliminates idle resources, cutting down costs while boosting cloud performance. You only pay for the execution time of functions, making it a cost-effective cloud optimization technique.

  • How it works: Serverless computing platforms like AWS Lambda, Google Cloud Functions, and Azure Functions execute event-driven workloads, ensuring efficient cloud resource utilization while eliminating the need for constant infrastructure management.
  • Use case: Coca-Cola leveraged AWS Lambda for its vending machines, reducing backend infrastructure costs and improving operational efficiency by scaling automatically with demand. 

3. Decentralized Cloud Computing: Edge Computing for Cost Reduction

Why send all your data to the cloud when it can be processed right where it’s generated? Edge computing reduces data transfer costs and latency by handling workloads closer to the source. By distributing computing power across multiple edge nodes, companies can avoid expensive, centralized cloud processing and minimize data egress fees.

  • How it works: Companies deploy micro data centers and AI-powered edge devices to analyze data closer to the source, reducing dependency on cloud bandwidth and lowering operational costs.
  • Use case: Retail giant Walmart leverages edge computing to process in-store data locally, reducing latency in inventory management and enhancing customer experience while cutting cloud expenses.

4. Cloud Optimization with FinOps Culture

FinOps (Cloud Financial Operations) is a cloud cost management practice that enables organizations to optimize cloud costs while maintaining operational efficiency. By fostering collaboration between finance, operations, and engineering teams, FinOps ensures cloud investments align with business goals, improving ROI and reducing unnecessary expenses.

  • How it works: Companies implement FinOps platforms like Apptio Cloudability and CloudHealth to gain real-time insights, automate cost optimization, and enforce financial accountability across cloud operations.
  • Use case: Early adopters of FinOps were Adobe, which leveraged it to analyze cloud spending patterns and dynamically allocate resources, leading to significant cost savings while maintaining application performance. 

5. Storage Tiering with Intelligent Data Lifecycle Management

Not all data needs a VIP seat in high-performance storage. Intelligent data lifecycle management ensures frequently accessed data stays hot, while infrequently used data moves to cost-effective storage. Cloud-adjacent storage, where data is stored closer to compute resources but outside the primary cloud, is gaining traction as a cost-efficient alternative. By reducing egress fees and optimizing storage tiers, businesses can significantly cut expenses while maintaining performance.

  • How it’s being done: Companies use intelligent storage optimization tools like AWS S3 Intelligent-Tiering, Google Cloud Storage’s Autoclass, and cloud-adjacent storage solutions from providers like Equinix and Wasabi to reduce storage and data transfer costs.
  • Use case: Dropbox optimizes cloud storage costs by using multi-tiered storage systems, moving less-accessed files to cost-efficient storage while keeping frequently accessed data on high-speed servers. 

6. Quantum Cloud Computing: The Future-Proof Cost Gamechanger

Quantum computing sounds like sci-fi, but cloud providers like AWS Braket and Google Quantum AI are already offering early-stage access. While still evolving, quantum cloud computing has the potential to process vast datasets at lightning speed, dramatically cutting costs for complex computations. By solving problems that traditional computers take days or weeks to process, quantum computing reduces the need for excessive computing resources, slashing operational costs.

  • How it works: Cloud providers integrate quantum computing services with existing cloud infrastructure, allowing businesses to test and run quantum algorithms for complex problem-solving without massive upfront investments.
  • Use case: Daimler AG leverages quantum computing to optimize battery materials research, reducing R&D costs and accelerating EV development.

7. Sustainable Cloud Optimization: Green Computing Meets Cost Efficiency

Running workloads when renewable energy is at its peak isn’t just good for the planet—it’s good for your budget too. Sustainable cloud computing aligns operations with renewable energy cycles, reducing reliance on non-renewable sources and lowering overall operational costs.

  • How it works: Companies use carbon-aware cloud scheduling tools like Microsoft’s Emissions Impact Dashboard to track energy consumption and optimize workload placement based on sustainability goals.
  • Use case: Google Cloud shifts workloads to data centers powered by renewable energy during peak production hours, reducing carbon footprint and lowering energy expenses. 

The Next Frontier: Where Cloud Optimization is Headed

Cloud optimization in 2025 isn’t just about playing by the old rules. It’s about reimagining the game entirely. With AI-driven automation, serverless computing, edge computing, FinOps, quantum advancements, and sustainable cloud practices, businesses can achieve cost savings and high cloud performance like never before.

Organizations that embrace these innovations will not only optimize their cloud spend but also gain a competitive edge through improved efficiency, agility, and sustainability. The future of cloud computing in 2025 isn’t just about cost-cutting—it’s about making smarter, more strategic cloud investments.

At Mantra Labs, we specialize in AI-driven cloud solutions, helping businesses optimize cloud costs, improve performance, and stay ahead in an ever-evolving digital landscape. Let’s build a smarter, more cost-efficient cloud strategy together. Get in touch with us today!

Are you ready to make your cloud strategy smarter, cost-efficient, and future-ready with AI-driven, serverless, and sustainable innovations?

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