AI and contextual technologies are changing making a difference in how industries are approaching both compliance and customer experience.
In an industry where a single breach can shatter trust and a technological lag can cost billions, the financial sector is at a crossroads. The promise of AI offers unprecedented efficiency and personalisation, but it also introduces complex new risks. To understand how banks are navigating this transformative period, we spoke with Ranga Reddy, CEO and Whole-time director at Maveric Systems. In a candid interview, Reddy shared his perspective on the pivotal role of domain-led technology, the central challenges of the AI era, and his company’s strategy for helping financial institutions thrive by embracing a new paradigm of operations and technology.
How are AI and contextual technologies reshaping regulatory compliance and customer experience expectations in complex, high-stakes industries?
AI and contextual technologies are changing making a difference in how industries are approaching both compliance and customer experience.
On the regulatory compliance side, we are seeing AI move from being a back-end support tool to something that is actively watching over operations in real time, continuously monitoring transactions, communications, and processes. It isflagging any compliance breaches instantly so that risks are reduced. Contextual AI actually goes a step further by pulling insights from multiple data sources to spot emerging risks and shifts in regulations, so that firms can adapt before they are caught off guard. It also adds transparency and explainability, that regulators love because every decision has a clear, auditable trail. And when it comes to fraud or money laundering, AI can detect patterns that are very subtle for traditional systems to catch.
On the customer experience front, contextual AI is powering personalization at scale. It learns from customer behaviour and preferences so when a human interacts with AI it feelsrelevant and customized. So that helps in making the experience smooth, elevating customer experience. Throughchatbots and virtual assistants it also makes customer service faster by understanding context which help in resolving issues quickly. Plus, predictive analytics means that you can proactively offer help even before customers realize they need it. When AI processes are transparent, customers feel safer, especially when their sensitive data or critical decisions are involved.
What are some of the key challenges enterprises face in meeting regulatory expectations, and how can domain-focused technology partners help address them through AI-led innovation? How can domain-focused technology partners help through AI-led innovation?
There are many. For example, many a times blind spots in reporting and audit readiness occur due to a lack of integration between multiple tools and workflows. This causesfragmented compliance systems. Regulatory changes are dynamic. Soyou need constant updates from regulators and quickly act on adopting them and proactively anticipating its impact. In short, you need some kind of intelligence to anticipate these changes and their impacts. Compliance monitoring often flags non-issues, creating a lot of noise that slows down genuine risk detection. That typically increases high false positive rates.
Inconsistent data, data silos, and poor data lineage acrossdepartments limits traceability and auditability. Data being the foundation for AI to work, AI-led innovation slows down.Manual-intensive processes have over reliance on human interventions which again increases the chances of errors, and hence, cost. This also slows response time.
Often technology providers treat industry challenges as isolated point problems offering narrow, limiting solutions aimed at fixing one issue. Worse, many apply the same cookie-cutter technology without contextualizing it to the unique nuances of the industry. This one-size-fits-all mindset overlooks the reality that in sectors like BFSI, challenges are deeply interconnected, with operational processes, regulatory pressures, customer behaviours, and technology layers constantly influencing each other.
Domain-focused technology partners take a fundamentally different approach. Because they understand the nuances of the domain, they use their industry knowledge as a fundamental layer blending with technology while designing AI-driven solutions that are rooted in the realities of the sector. They focus more on solving the problems that are highly contextualized. So the focus is on context that can make a real impact on businesses where it matters the most.
Some of the key challenges I have already addressed where domain-focused AI partners can help, especially in highly regulated industries, there’s a big impact.
- Frameworks like KYC, FATCA, and Basel norms vary by jurisdiction and change frequently. Domain-trained AI models can ensure accurate risk detection and timely compliance to these.
- Domain-aware automations minimise false positives, freeing up time for compliance teams to focus on genuine threats, reducing compliance inefficiencies.
- Predictive compliance tools simulate potential regulatory changes and their operational impact, which enables proactive readiness.
- Knowing the domain well also helps in building data lineage, which helps in ensuring data integrity and makes tracking easy, transparent and traceable. In short, makes data audit ready.
- Process orchestration integrates regulatory adherence into workflows by design, so it’s not an afterthought.
- Having domain-rich information also means that AI is targeted. AI is deployed where it delivers the highest value. This saves time and resources. Because domain-focused partners have more nuanced context, the AI is trained on domain-specific data, regulations, and workflows, which makes it more accurate.
- Leveraging domain-trained AI to anticipate regulatory changes and simulate their operational impact allows enterprises to prepare ahead of time.
- Reducing false positives using algorithms that understand the domain context.
Cybersecurity has become a boardroom priority across sectors. How should mid-sized, domain-led partners support clients in building secure, AI-enabled systems while ensuring regulatory alignment?
Domain-led partners should support clients in building secureAI-enabled systems by combining specialized managed security services with strategic advisory that are focused on helping bring regulatory alignment and risk management tailored to mid-sized institutions.
When we talk about Managed Security Services, what should stand out is the approach. The focus should be on continuous monitoring, penetration testing, and vulnerability management. There needs to be some essential training, particularly on phishing awareness, because that’s a major risk. Plus, there’s a need to handle managed detection and response (MDR) and firewall, and also plan for breach response.
Domain-led tech providers can blend tailored MDR capabilities with strategic regulatory compliance advisory to build resilient, secure, and compliant AI-enabled operations. When it comes to specific industries, domain-led partners can offer security solutions that are tailored to fit the unique regulatory and operational needs fit for that industry. They can ensure compliance with data privacy laws like GDPR, and protect sensitive customer data, integrate AI-powered tools for fraud detection and anti-money laundering.
As technology is constantly evolving, there needs to be a greater focus on risk-based governance and advisory services to partner with leadership teams. There is a high need to prioritize cybersecurity as part of the overall business strategy. Aligning security initiatives with business helps in understanding the acceptable levels of risk, regulatory requirements, and planning for digital transformation goals.
Keeping employees abreast with the latest information, phishing attacks, common breaches, social engineering tactics, and insider threats, etc. are equally important. So training them at regular intervals through security awareness programs have also become imperative.
For cloud and digital infrastructure security, implementing best practices in identity and access management, data loss prevention, encryption, and secure API integrations are important. Banking and Financial institutions have to be prepared for any incident that may arise. Regular test incident response and recovery plans have become key in minimizing the impact of security events and guaranteeing a swift recovery.
With rising client expectations and evolving compliance standards, what does it take for mid-sized technology firms to scale operations and delivery to meet global benchmarks without losing agility?
For mid-sized technology firms, scaling to meet global benchmarks hinges on three things primarily. First is the ability to collaborate effortlessly across diverse stakeholders, second is a commitment to continuously enhancing domain and technical expertise, and third is the agility to adopt and tailor emerging technologies hand-in-hand with industry evolution.
Looking back on Maveric’s 25-year journey, what have been the pivotal decisions or investments that have helped the company stay relevant and competitive through multiple technology shifts?
Looking back at Maveric’s 25-year journey, our single most important decision has been to stay laser-focused on the banking and financial services industry. That focus has been our anchor. It has allowed us to build deep domain knowledge, spot patterns early, anticipate market shifts, and prepare for “what’s next.”
From day one, we have built our model of serving customers around understanding their context; what they need, when they need it, and how they want it delivered. This ability to bring together domain expertise, platform capabilities, and technology know-how has helped us craft contextual solutions that truly support transformation. Over the years, we have developed and scaled new service lines in line with our customers’ growth areas, always ensuring that our talent combines deep domain and technology leadership with a culture of ownership, energy, and commitment to client success.
We have always been agile and nimble. For example, if you study our journey, you will notice that we have operated in a way that have allowed us to anticipate change, pivot when needed. From calling ourselves a bank-tech company, we are pivoting to be an AI-led operations & technology partners for banks & financial institutions.
Technology is constantly evolving and so are our clients’ needs and hence, we are. When our customers show interest in new opportunities, we move quickly to adopt, build competencies, and put them to work in ways that matter. That’s why we have created accelerators, frameworks and AI powered Centers of Excellence like AI at scale and IntelliHub. Strategic partnerships with leaders like Snowflake, Databricks, Big Panda, and many others have helped us stay ahead of the curve, expand our reach, and deliver even greater value.
Through it all, we have invested in building strong leadership and skilled professionals who can take ownership and drive change. Our customer-centric approach has ensured long-term relationships. Every evolution in our services, every pivot we have made, has been rooted in solving our clients’ challenges.
As Maveric targets USD 200 million ARR and expansion in developed markets, what are your strategic focus areas across innovation, talent and delivery for the next phase of growth?
Our strategy is anchored on helping banks revision their business and, in doing so, reimagine the people, processes, and technology that support it.
Since November last year, we have been reorganizing our offerings to directly impact two critical areas for banks – operations and technology. On the technology side, our focus has been on three things – modernization, AMS re-engineering, and AI-native QA. On the operations side, we are driving transformation in regulatory compliance, customer service, wealth management, and lending.
The common thread across all of this is how we integrate AI, data, and automation as a combined force that can reengineer the business. In the pre-AI era, Maveric was built on deep strengths in data, digital, QA, product, and domain expertise. In today’s AI-centric world, the first question clients ask is not about tools or tech, but if we understand their business. Because once you apply AI, it changes the very fabric of how that business runs.
That’s why domain-led capability is now at the heart of our growth. For example, if you understand both wealth management and AI you are a priority partner, if you only know one, you will perhaps not be considered. To meet this demand, we are building AI fluency within the business context. Out of our 2,000 plus team, 10% are already AI-ready, and we plan to double that by March, continuing to scale as demand accelerates. We have also created our AI@Scale framework which guides banks especially early adopters through every stage of their AI journey. It brings together consulting-led strategy and governance, the right platforms and accelerators, and specialised delivery talent to ensure measurable impact. This is about deploying AI where it matters the most to create tangible business outcomes. We are pivoting to be a true operations and technology transformation partner for the AI era blending deep domain knowledge with responsible, scalable AI integration to help banks unlock the future of their business.
About the Author
As CEO and Co-founder, Ranga, strategizes and spearheads Maveric’s pursuit to become one of the world’s top three Bank-Tech solutions specialists transforming digital ecosystems of retail banking, corporate banking, and wealth management. For more than twenty years, Ranga’s laser focus has created an organization that learns, experiments, and innovates through its passionate people and ‘free radical’ practices. His customer success obsession is evident in Maveric’s industry-renowned solutions across pressing challenges in CX, Digital Ops, Regulatory compliance, and connected core domains.
Article Originally Published in BW Security World
