AI-Driven Contact Centers in the Financial Services Industry

Quantiphi is a Business Reporter client.

Investing today in modernizing contact center operations can help financial services firms drive superior business outcomes in times to come.

The Covid-19 pandemic has forced companies to rapidly transform their businesses and embrace digital technologies. Digital adoption has taken a quantum leap at organizational and consumer levels alike. Increased usage of advanced digital technologies and touchpoints to keep critical services afloat has been a common denominator for all sectors, including financial services, as firms have accelerated the digitalization of their customer journeys and internal operations.

In the pre-pandemic world, a modern contact center equipped with artificial intelligence (AI) and advanced analytics capabilities was considered an indicator of competitive advantage. However, during the pandemic, it became a necessity. Organizations and their consumers adapted to remote and digital processes, and an efficient contact center became crucial to keep critical services afloat and ensure operational resilience.

Banks and other financial services firms should be encouraged to rise to the occasion and ensure that their customers receive the support they need in challenging times. The other side of the coin is that consumers have become accustomed to remote servicing and have realized its benefits; 75% of those using digital channels for the first time indicate that they will continue to use them when things return to “normal.”

Instead of reverting to pre-pandemic standards, customers are pushing for a hybrid normal. They expect a seamless and superior digital service standard from the financial services industry. Hence the question arises: How do we modernize contact centers faster, cheaper and at scale?

From the firm’s point of view, calls are the costliest medium of customer servicing and typically the least satisfactory channel. A primary goal of call centers has always been to reduce call volumes and deflect the call traffic to chat or self-service channels. However, adopting call-deflection strategies such as FAQ chatbots initially resulted in a poor customer experience as the responses were generally script-based and premeditated.

The goal of a digital customer servicing organization is to employ a consistent strategy across multiple channels—call, chat and self-service—to respond to customers, leading to improved customer experience and operational excellence. This seamless omnichannel customer experience with various self-servicing capabilities can be made possible with the adoption of advanced Al and machine learning (ML) in these business processes.

We are now at a technology tipping point where advancements in natural language processing (NLP), ML and computational efficiency have given us conversational AI-powered chatbots that can understand the real intent of customers. These bots learn from previous responses, existing databases and ongoing customer interactions to prepare answers in line with customer queries.

Voice technology has also seen exceptional advancements in recent times. Efficient text-to-voice and voice-to-text conversions and the natural flow of conversations with the ability to understand the context and stop words are bridging the machine-to-human communication gap. These automated communication channels can perform authentication, query registration and, in many cases, query resolution. Unresolved queries can then be routed to an agent for resolution, thus allowing multiple lines of defense before reaching the human in the loop.

Contact centers are growing in complexity as they shift from handling only transactional interactions, such as informational calls, to addressing more complex issues, including sales and purchase activities. Agents now play a vital role in lead identification and cross-sell and upsell of products and services.

With successful investment in self-service technologies and innovative deflection strategies, financial services firms enable customers to independently handle many of their basic issues and transaction activities. Every query handled by a chatbot saves 4 minutes of an agent’s time on average. This will allow agents to focus more on complex and high-impact customer interactions, increasing the customers’ lifetime value, or on targeting customers with high churn probability. With the evolution of omnichannel platforms, agents can also identify proactive communication channels.

More than 50% of banking customers surveyed want their banks to recommend products or services to proactively meet their financial needs. Among those interested in these services, 55% say that it would enormously increase their loyalty to their bank. The organizations require a central repository of customer information and interaction histories and agents to lead these conversations and achieve the proactive recommendations.

Although modern contact centers are expected to save an estimated $7.3 billion for banks by 2023, this is not beneficial just for the organizations, Customers also stand to gain enormously. Customers will not have to wait long before getting the chance to speak to agents as the successful deployment of conversational bots will bring down the call volume. While customers wait in line, conversational bots can complete customer verification, ask query details, perform Customer 360 analysis and retrieve interaction histories of the customer; these will help the agents maximize first-call resolution. Also, as call center agents are relieved from supporting simpler, low-impact queries, they can provide the customers with empathetic, higher-quality interactions.

While the modernized call center as an idea may seem overwhelming, we can develop secure, cost-effective infrastructures to accommodate this without a massive capital expenditure, due to the pay-as-you-go cloud deployment models. Major cloud providers have also brought in APIs that further bolster the adoption of intelligent chatbots and voice-assistant bots. These technologies ensure that customer interaction data is stored in a structured manner, further helping banks and financial firms accurately assess customer behavior to improve processes across the value chain.

To meet the challenges of this new normal and to support customers in using digital services, financial institutions must modernize contact centers and make them reliable and scalable. With the right technology, infrastructure and trained agents, modernized contact centers will deliver superior customer experience, gain and retain customers and help financial firms stand out in an extremely competitive industry environment.

— Bhaskar Kalita, Global Head, Financial Services and Insurance, Quantiphi Inc.

_{This article originally appeared on Business Reporter. Image credits: Courtesy of Quantiphi}