“We are experiencing higher than normal call volume to our customer service call centre. We are dealing with your enquiries as quickly as possible but please bear with us during this time.”

It’s the infuriating phrase that makes every customer cringe. A refrain that’s become a standard part of every customer hotline greeting the past two years.

The ramifications of Covid-19 have hit brick-and-mortar establishments hard, and the banking, financial services, and insurance (BFSI) industry were not spared. Around the world, besides bank closures and movement restrictions, customers’ in-branch visits have been limited to appointment-only. As a result, call centre volumes have significantly grown across geographies and industries.

Overworked frontline staff do not have breaks, face more stress, and are unlikely to be productive or more helpful. Yet, customers still need reliable and empathetic remote support from banks to access critical services.

On the other hand, early adopters of conversational AI and virtual voice assistants have stood to gain customer loyalty by improving the customer experience, especially with AI-enabled possibilities from customer interactions to data analytics and operations.

Why is conversational AI causing a paradigm shift in BFSI customer service? Let’s find out more about the common business challenges and how Voice AI can help to power the financial services industry through the pandemic.

Legacy systems frustrate customers and may damage brand loyalty

Trust forms the foundation of the BFSI industry. Having convenient access to banking, insurance, and financial services directly impact customers’ well-being. Customers need to trust that BFSI businesses can recommend the right products and services, attend to them promptly, and provide relevant and personalised advice.

Customer experience, especially at critical engagement touchpoints like call or contact centres, can make or break customer loyalty. The experience starts from the moment the customer picks up the phone to dial your business. Insights from PwC found that:

• Three out of four customers make buying decisions based on their experience with a bank’s contact centre experience.
• About a third of customers are inclined to abandon a brand they liked simply because of a single negative customer experience.

In challenging times like the pandemic where people are socially isolated, BFSI businesses like banks may find customer trust and satisfaction eroding dangerously. The change from face-to-face interactions to digital banking has resulted in an alarming fall in trust, according to Accenture. Even as companies deliver effective digital service, building long-term trust through positive customer interactions have become more important for the BFSI industry today.

It does pay to make your customers happy as being in their good books can affect your business value. A McKinsey study also found that good customer satisfaction drives shareholder value. A key way of building trust is to listen to your customers and ensure they know they are being heard.

However, Interactive Voice Response (IVR) systems could do the very opposite. IVRs can frustrate customers with long menus or wait times before a human agent could attend to them. A survey found that customers dislike IVRs because they are forced to wait through too many options irrelevant to their problem, and sometimes their reason for calling cannot be found on the menu. 

McKinsey research shows customers don’t like legacy IVR systems, but still tolerate it as speaking to a human agent may be the fastest way to solve their problems. 27% of calls were abandoned because of IVRs, and 85% of consumers ended at least one call according to a survey. It stands to reason that voice AI solutions can add outsized value to the customer service experience on calls.

Conversational AI helps accelerate financial services response to Covid-19

Voice AI solutions can help transform IVR systems into smarter bots that are capable of handling complex customer interactions in BFSI. AI-powered voice assistants can help engage customers in a personalised and seamless manner like how they would communicate with a human customer service representative. Rather than sitting through a long checklist dictated by a robotic voice, and selecting numerical options one after another, a customer could just speak into the phone and receive the right assistance.

Voice AI creates seamless and empathetic customer support based on urgency

Conversational AI is more likely to succeed in triaging critical issues or customer problems that customers present than an IVR, which may only be able to identify broad words like “credit card”.

For instance, a customer requires immediate and urgent support for “stolen credit card, help” versus “issue new credit card”. Conversational AI can help identify a customer’s tone, accent, and language, providing nuance to either a routine or a panicked conversation.

Conversational AI can complement digital tools

With the “always-on” availability of digital banking and the proliferation of digital financial products and services, there are many reasons why a customer would appreciate on-demand support. While we continue to see accelerated adoption of digital banking and services, banks and financial institutions need to rethink their CX and how conversational AI can play a part to keep pace with the demand. Once customers get past the initial adjustment period, conversational AI can help smoothen the adoption process when deployed alongside digital services like tutorials and timely content. 

Conversational AI can understand complex and non-routine questions

Especially during the pandemic, customers are also more likely to ask non-routine and complex queries that require human judgement such as deferring loan payments or accessing health insurance. Accurately triaging or prioritising problems or intents means customers can be directed to the right agent for support quickly. Moreover, fast, and effective resolution means customers do not have to call repeatedly, reducing the burden on call centres.

Respecting customers’ time shows the customers that they are valued and respected while meeting their fundamental desire to solve the problem quickly.

Conversational AI can support telemarketing and telesales

Conversational AI can replicate the way humans talk and can be plugged into a rich database of customer demographics, behaviours, and purchase history. Through voice analysis and contextual clues, conversational AI could identify customers who are ready for conversion and recommend the relevant BFSI products and services in their preferred spoken language. This can be done at scale while delivering consistently outstanding service. 

Voice AI reduces stress on call centre operations

Besides improving customer experience, conversational AI solutions can help smoothen call centre operations. A shift to remote work in some pandemic-affected areas mean call centre staff have to set up operations at home, where equipment and internet may not be as reliable.

BFSI businesses are in a sticky situation. Businesses have to assist millions of customers, provide essential services in extraordinary conditions, remain, good custodians of personal data while managing health and safety in the workplace. It may cost thousands of dollars for call centre businesses to set a single agent up at home with adequate equipment and protocols around data privacy. 

Call centre staff may also be similarly reeling from the effects of the pandemic. Absenteeism or attrition rates may increase due to emergencies or anxieties caused by the pandemic. Moreover, Covid-19 has caused a mental health crisis with more people experiencing poorer well-being and is most likely here to stay. On the other hand, Voice AI can identify stress and urgency from voice calls more accurately, compared to pre-programmed menus and IVRs. It can also reduce emotional burnout that human agents face at call centres due to increased work volumes and more people being distressed.

Conversational AI can handle routine processes, reducing high-stress and high-volume work that human call operators face at all hours. Human agents can focus on providing specialised support, augmented with knowledge from data gathered from voice transcription and customer data collection.

Moreover, conversational AI can be deployed at any time of the day. Fewer human agents may have to be deployed at odd hours, serving active customers across different time zones. Call centres can allow people to work shorter but more effective shifts too by scheduling more human agents during peak hours, but allowing AI to do heavy lifting off-peak.

How the BFSI industry can start embracing Conversational AI

According to McKinsey, companies that successfully translate speech data into actionable customer insights can see cost savings of up to 30%, improvements of customer satisfaction by 10%, and more revenue unlocked. Early and accelerated adopters of conversational AI have felt benefits during the Covid-19 crisis, especially those in BFSI.

Examine customer journey and touchpoints to deploy Voice AI

To leverage voice AI effectively, BFSI services may want to look into their customer journey to identify opportunities and use cases: channels that customers use, and how they interact with the business.

Customers expect a seamless journey from digital platforms to human interactions. Voice AI should be adaptive to the customer, and seamlessly hand off the customer to the human agent. For instance, AI could identify customer profiles who struggle with digital banking and match them with a human agent speaking the right language as soon as possible.

With the digitalisation of BFSI products and services, and more customers getting on the internet, customers have different ways of interacting with the business and a multitude of journeys beyond purely financial products.

For instance, they could be purchasing a home and so require access to an ecosystem of related services: mortgage loans, renovation loans to pay regulation-approved contractors, and personal or property insurance. Conversation AI solutions are likely to be the stronger candidate to keep abreast of these services and deliver on live calls with customers, compared with traditional systems.

Use Voice AI to promote inclusivity

Customers who stand to benefit from Voice AI include those with limited mobility, visual, or language ability. For instance, people with low vision or physical tremors may be unable to dial the next digit or press an incorrect number. Voice AI can provide a fully voice-based service in the language of their choice, improving accessibility at scale.

AI can provide data analytics for consumer insights

Human agents are better at supporting customers by providing live troubleshooting, making judgement calls for critical non-routine decisions, and empathising or reassuring them. However, getting agents to record all the data they encounter in a shift would be a huge administrative load and ineffective use of their time. 

McKinsey found challenges organisations face when trying to get insights from customers’ voice conversations.

• Organisations are unable to capture all interactions but manually sample random calls. At only 2% of all interactions captured, the data is not representative or complete. 
• Legacy processing systems and transcription do not capture useful information. 

Implementing a voice AI solution can help extract and accumulate a treasure trove of data from incoming customer calls. This means that BFSI businesses will need a well-planned data strategy to address privacy concerns.

Sentiment analysis of data at scale identifies customer opinions 

From customers’ voice data, sentiment analysis can be performed too. Sentiment analysis is valuable for business. With Automatic Speech Recognition, it reduces the time required by humans to read and interpret transcripts.

Deploying Voice AI and sentiment analysis can help improve the application, filter and assess huge amounts of customer data and opinions that a team of humans may not be able to complete, and provides BFSI companies important insights that can be used to optimise product or service.

Predictive analytics manages company crises that reduce consumer trust

Real-time data from Voice AI can even be used to predict issues before they occur, such as a sophisticated phishing scam targeted at customers. Banks can take immediate action if they sense a sudden influx of urgent calls, where Voice AI analytics can help to identify critical issues or identify problematic patterns. This allows banks to investigate and take precautionary measures in real-time, preventing emergencies from developing into full-blown crises. 

Improve and identify gaps in training

Besides improving customer experience, these insights can be used for training purposes. Analytics captured by Voice AI can help call centre operators or customer service teams forecast demand, staff appropriately, and identify new or existing areas of training.

Conversational AI helps financial services emerge stronger

With more than one channel of communication, from emails, telephone calls to social media, customers demand and expect businesses, at the very least, to offer a seamless brand experience while remaining accessible and interactive.

How? The opportunity lies in Voice AI. Voice technology is leading the way in improving this experience and augmenting human customer service agents to be better at their jobs, saving everyone money and time while increasing accessibility and convenience for consumers.

With businesses overwhelmed by customer requests during Covid-19, Voice AI has proven to be a natural choice — especially in financial services and banking — to provide the agility needed to deal with the business impact of the pandemic.