Fintech Legacy systems are expensive to maintain, difficult to scale, and


oſten incompatible with the data governance and security demands of modern finance. More worryingly, they’re a primary reason many contact centres cannot adapt to evolving customer behaviours such as channel-switching, asynchronous support, and remote resolution. Modern contact centre platforms, especially those integrated


natively into tools like Microsoſt Teams, offer more than just functionality; they offer flexibility. With one common environment for voice, chat, email, and social media, every agent becomes part of a larger, orchestrated engagement network. And with cloud-native deployments, contact centres can be spun up or down in days, rather than months. Tis is critical for resilience in times of crisis or rapid growth. Financial services are inherently personal, and every inquiry,


whether routine or high-stakes, occurs in a context. Yet in too many organisations, agents are forced to hunt across screens and systems for that context, delaying resolutions and frustrating customers. Te future belongs to organisations that place customer data at the


core of every dialogue, automatically presenting customer history, preferences, and relevant product details at the moment of contact. Tis is how self-service becomes smart, agents become trusted advisors, and institutions gain the consistency and personalisation needed to differentiate in a crowded market. Moreover, with tight customer data integration, switching between


channels (from bot to agent, from chat to call) becomes frictionless. Te customer never has to repeat themselves, and every touchpoint builds on the last.


frontline managers to consistently improve services without relying on IT. As a result, we’ve observed that institutions can reduce call handling times by as much as 30% simply by streamlining the user experience. Too oſten, AI is positioned as a silver bullet. In practice, most


financial institutions have already deployed chatbots and self-service tools only to find them more frustrating than functional. Tis is not a technology problem; it’s an orchestration one. Te goal isn’t to replace humans, but to augment them. High-


performing institutions distinguish between automation for efficiency and automation for engagement. Bots, when intelligently deployed, can handle up to 65% of inbound requests, which can range from account balance queries to payment status updates, while seamlessly escalating complex needs to live agents. Te key factor here is context. AI-driven voice and chatbots need


access to real-time customer data to provide personalised and relevant support. For example, if a customer requests their last two statements, they shouldn’t have to navigate through three menus or go through re- authentication. Smart conversational AI can handle the task in seconds by recognising the customer, verifying them securely, and completing the task end-to-end. Tis level of seamless, proactive automation reduces cost, minimises


friction, and, crucially, improves customer satisfaction rather than sacrificing it.


Legacy platforms are costing you more than you think Te debate over cloud versus on-premise is over, and financial institutions that are still tied to legacy communication infrastructure are exposing themselves to significant risk while at the same time lagging behind the competition.


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Reporting Is not enough Traditional KPIs such as Average Handle Time (AHT), First Contact Resolution (FCR), and Customer Satisfaction Score (CSAT) are useful, but they only tell part of the story. In an omnichannel, distributed world, real-time visibility into all customer dialogues, across departments and channels, is non-negotiable. Tis not only optimises the contact centre, but it also surfaces


customer insights across the entire enterprise. Why are customers calling more about a certain feature? Why are service requests spiking in one geography? Where is friction accumulating, and how can it be preempted? Advanced dialogue analytics, powered by AI and integrated with


BI tools like Power BI, are enabling financial institutions to go beyond tracking performance to improving it. When you can measure the end-to-end customer journey, you can proactively design better outcomes. Banks and financial institutions have always led with trust. But in


a world of heightened expectations, that trust must continuously be earned, in every interaction. It’s time to reimagine customer engagement not as a cost centre,


but as a strategic differentiator. Tat means investing in the tools, platforms, and people that can deliver frictionless, contextual, and human-centred experiences at scale. Te road ahead will not be paved with buzzwords or off-the-shelf


bots. It will be led by institutions willing to modernise the backbone of their customer operations with one smart investment at a time. Because in this new era, how you talk to your customers may matter more than anything else you offer.


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