Expect Wider Adoption of Technology as Brands Seek to Personalize Service
By James Hewitt, Aigent
You may not know it, but artificial intelligence is everywhere today. Ever ask Siri, Alexa, or Google Home a question? Or used Waze to find your way home? AI powers the algorithms behind these devices and apps, the social media feeds we receive, and what we see when we log in to Facebook or LinkedIn. Every day, AI provides machines with the ability to learn, adapt, and make decisions.
Increasingly, AI is creating new opportunities for companies to deliver improved customer service – from using chatbots to interact with customers to facilitating data-based decision-making to improve customer experience. This is a seismic change for customer service, a five-decade-old industry whose prime shift until now was moving from phone-based call centers to the omnichannel support capabilities we see today. Those channels include email, phone, social media, and voice assistants, and the list is growing. Now, customer service is poised to undergo another dramatic shift as decision-makers adopt AI to revolutionize the customer experience.
AI adoption is in its early days but is on the rise as customer service teams turn to chatbots, text and voice analytics, and other tech-driven capabilities. Why? Decision-makers have long known that the ability to listen and truly understand customer needs is critical to winning the hearts of consumers. In recent years, they have begun to recognize that AI and machine learning can provide greater insight into shaping customer service offerings. AI can do this by enabling brands to deliver personalized experiences at each step of the customer journey.
Fintech companies were already known for disrupting the banking and payments industry. Now, payments, mobile banking, blockchain, and even insurance companies are increasingly leveraging the power of AI and machine learning to transform how they engage with customers. Think about applying for a credit card. Today, using AI, companies authenticate identification or perform background checks. A process that may have taken weeks now takes a few minutes. Chatbots that appear on payment company websites or apps and can provide customers with accurate answers to questions almost instantaneously.
Other ways customers are receiving improved service are on the calls themselves. Through voice recognition, for example, we can monitor calls in real-time with a high degree of accuracy. That same technology can help with transcribing and interpreting information, such as account information or routine requests. By listening to calls and using machine learning, we can equip agents to understand customer sentiment better. We’re marrying voice recognition with live voice and turning it into a product that helps customers by ensuring calls are dealt with efficiently and effectively.
How It Works
Machine learning and AI are dramatically changing the world we live in – from self-driving cars to product recommendations we receive during checkout on Amazon. These technologies are making our lives easier and better. So why shouldn’t they do the same for customer experience?
The technologies begin with a data link that is built over time. Data inputs come from a range of technology solutions and companies. Humans listen to these conversations and develop initial patterns. This process involves a great deal of hard coding at the outset. Companies can adjust various touchpoints that prove challenging by detecting patterns in a customer’s journey – from sentiment to even the purchase process. With a deeper pool of customer data, companies can initiate deeper analysis and personalize service accordingly. Over time, this enables them to help meet customer needs and understand how those needs change, allowing the companies to meet preferences in the future.
Reinventing the Call Center
There has been very little innovation to the call center model of today. Yet consumers are more digitally savvy and expect that questions will be answered, and problems solved quickly and efficiently. Enter technology such as AI and machine learning, which are transforming today’s call centers. Call center agents can use these tools to analyze speech and text in real-time and determine whether they are positive or negative. If a customer is upset or requires empathy, we can escalate a call to a supervisor in real-time. Conversely, simple questions can be resolved quickly, freeing agents to manage more complex calls.
By using this technology, we can involve a human only when necessary. Over time, an agent can better understand a customer’s preferences and behavior and if they’ve encountered problems before. In doing so, companies can provide more personalized service. It’s no surprise that many fintechs and other companies using AI are seeing an increase in first-call resolution and reductions in average handle time. On the surface, these advantages represent a fraction of what’s at stake.
One of those high-stakes areas is compliance. In today’s digital world, financial services companies are faced with meeting new regulations and being one step ahead of fraudsters. AI, for example, improves the ability to detect fraud by enabling financial firms to use facial recognition to verify identification or monitor customer behavior for suspicious activity. Transaction processing can be automated and completed more quickly. Names, addresses, or routing numbers can be verified, reducing potential fraud exposure. By using AI to mitigate these risks, firms can detect potentially fraudulent transactions more quickly – improving security and customer trust.
Firms have also begun to use AI to reduce the risk of incurring fines and regulatory orders associated with failures to observe compliance matters that they must adhere to. For example, banks can use machine learning to assess the credibility of data – often by comparing documents with transaction or system data to verify a person’s identity. And, when it comes to bank wire transfers, AI can be used to create call transcripts that ensure that the proper compliance checks to initiate a wire were conducted. How would a multinational company feel if a wire was held because its bank failed to ask required questions?
Companies are also using AI to drive new revenues. Facebook Messenger, for example, uses AI to generate ads that can be sent to those who have interacted with a brand’s page in the past. Chatbots can interact with customers based on responses to questions, deliver sales leads. And they can even complete sales transactions since all these activities occur within Facebook Messenger. In financial services, AI provides an opportunity to sell new products and services to customers. A bank customer can apply for a loan via a website’s Chatbot, for example.
A Bright Future
With its ability to deliver a personalized experience to customers, the adoption of AI is poised to increase. Companies have begun to recognize that AI provides a unique opportunity to truly understand customer preferences through data capture that enables them to deliver the proper interactions at the right time. Many have just begun to unleash the power of AI – many more will follow – to achieve greater efficiencies, meet compliance requirements, and improve their bottom lines. AI is the catalyst that will build deeper relationships with customers. At stake is an opportunity to create a prime differentiator in the race to build customer loyalty.
James Hewitt has been a leader in financial services and payment innovation for more than two decades. He has engineered industry changing fintech deals that have pioneered evolutions in payments in areas such as mobile wallets, international money transfers and state-of-the-art fund settlement platforms.