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How conversational AI mitigates the impact of bank branch closure

How conversational AI mitigates the impact of bank branch closure

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The pandemic has forced many businesses to temporarily close their locations. It specifically impacted the banking industry on a global scale. TSB, a U.K. bank, is planning a permanent closure of its 82 branches by the end of 2020, and many U.S. banks are doing the same.

Banks have been closing the doors of their branches at an exponential rate, fundamentally transforming the way they provide customer service and interact with their customers. While many large banks are already leveraging the power of conversational artificial intelligence (AI) to provide customer service, its potential remains untapped and technology underutilized by most.

Bank branch closures are not solely a consequence of the COVID-19 pandemic. It’s a response to a new generational trend in consumer preferences that’s here to stay. The Federal Deposit Insurance Corporation, a government-created entity that “examines and supervises financial institutions for safety, soundness, and consumer protection”, compiles data about branch closures. Their annual historical bank data shows the beginning of a decline in the number of branches in the U.S. starting in 2013.

The pandemic has accelerated a trend that has already been in motion.

Naturally, regulators are worried about what that means for consumers. In the U.S., The Office of the Comptroller of the Currency has a manual for bank branch closures to help mitigate the negative impact. However, the manual will sooner rather than later stop reflecting the reality of how consumers bank.

According to the manual, “A bank is expected to develop a reasonable method of allocating customers to specific branches,” and “if customers are assigned to a mobile branch or messenger service branch (collectively, mobile branch), normal customer notification requirements apply.” To close their branches, banks must reassure regulators that consumers and communities will not be left “underbanked.”

There would be no such thing as being underbanked in a world where conversational AI facilitates automated human-like interactions across multiple channels between large institutions, like banks, and their customers.

Over the past few months, as branches temporarily closed, some banks have had a more than 100-percent increase in customer calls compared to the pre-covid-19 levels. Customer service departments have found themselves overwhelmed, presenting an opportunity for banks to innovate, and conversational AI is the answer. Here are the three most important capabilities of conversational AI that banks need to consider.

  • Efficient and Timely Customer Service: When communicating with customers, banks can deploy artificial intelligence that has deep learning capabilities and can adapt their responses to different customers and situations. This is especially important for large banks with customers who speak different languages and dialects. Conversational AI can implicitly learn all dialects, accents, and new vocabulary through training data. It uses the spoken language by real customers to learn how to respond. This allows for personalization. The most sophisticated solutions have a speech-to-text transcription word error rate of 4 percent, which is consistently equal to or higher than the performance of customer service agents.
  • Industry-Specific AI Solutions: Every industry has its specific terminology and so do the segments of businesses within an industry. For example, credit unions refer to their customers as members, while that is not true for the entire financial services sector. With conversational AI, banks can implement a pre-built speech recognition technology that is tailored to the terminology their customers use. This way, the banks do not have to develop their own AI and natural language understanding (NLU) capabilities, both used to enable customer interaction, from scratch. Instead, a pre-built industry-specific conversational AI solution can understand up to 400 different intent requests from the caller. An added benefit is that it effectively reduces the time it takes for the technology to learn new information by 90 percent, making the implementation quickly deployable.
  • Enhanced Consumer Protection: Banks must have consumer protection capabilities in place for the benefit of their business and consumers. Secure authentication and verification of customers are critical aspects of the successful utilization of conversational AI. This is possible through the use of passive voice biometrics. Passive voice biometrics can authenticate a person’s identity through the creation of a consumer voiceprint. Voiceprints are created by using audio samples of a person’s voice when they call customer service. This capability is significant because fraudsters are figuring out how to circumvent conventional caller multi-authentication methods such as passwords, security questions, and one-time passcodes sent via text or email. Besides the anti-fraud measures, the combination of advanced conversational AI and voice biometrics can reduce the length of a customer service phone call up to 80%, saving resources in addition to improving the customer service experience.

Banks must first understand how to utilize conversational AI and know which solutions will work the best for them and their customers. To do so, they have to assess their core customer base, their business needs, and readiness to adopt AI. Banks should determine the average customer call volume and whether customer service agents can meet the call demand. Then, banks should take a close look at their customer demographics and the complexity of a typical customer’s request. How many bank customers speak languages that are not native to the country where they operate?

If a company has a high call volume and complex customer requests, they are better off using speech conversational AI than any other solution. A bank must identify the communication channels that its customers prefer to use (i.e., phone, webchat, email, text, smart speaker, social media) and consider an omnichannel communication approach. It’s also important to know if the current contact center is sufficiently equipped to withstand consumer fraud attempts. Most banks have a foundation in place to facilitate the implementation of conversational AI because they already utilize cloud technology to manage their CRM systems.

Seamless and easy customer experience can determine the customer’s impression of a bank and help support a strong business reputation. According to a 2019 report from Forrester, nearly one in three global IT decision-makers for companies cite virtual agents as a top investment priority. Banks are responding to the new consumer preferences and are utilizing AI to keep up with consumers’ interaction preferences for a quick and efficient customer service experience. Those who are not will need to catch up or remain behind.

Source : bdtechtalks.com

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