Generative AI in the Financial Services Call Center

80% of the customers confirm that they would change brands because of poor customer experience. Therefore, it becomes critical for companies to conduct excellent customer care service through their call center. Especially for financial services, call centers can be a key differentiator for their business success.

43% of customers confirm that even a single poor experience is enough for them to consider changing brands. Companies can not afford to slack off in their call center services, especially, for a competitive industry like finance and insurance.

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The Current State of Insurance Contact Centers

Finance or insurance contact centers are responsible for several key functions, such as collecting new applications, renewing policies, answering customer queries, resolving customer concerns, and fostering customer relations. 

These are some of the important areas where customer call centers must maintain exceptional care to direct business growth. However, to do so, insurance call centers must overcome several operational issues:

• Inconsistent customer interactions

As per Salesforce, 79% of customers expect consistent interaction across different departments and channels. However, it is quite hard for insurance companies to connect the dots so users can resume their interactions from where they left off the last time.

Likewise, it is hard for insurance companies to merge and summarize customer interactions across platforms with a growing number of channels such as emails, chatbots, Whatsapp, and social media apps.

• Training & retaining customer care agents

30% of the insurance agents quit their jobs within three months, while a whopping 87% of insurance agents quit in three years. This attrition rate is way beyond any other industry. Retaining talented agents would require insurance companies to make the job easier for agents.

Moreover, hiring and training new agents would require several months of time and can add up to significant costs, almost over $5K for each agent. Consistent quality of their training and effectiveness is not easy either.

• Longer queues and delayed response time

Without overhead manpower, companies can’t always keep up with customer requests and queries. This could lead to longer customer queues during peak hours and seasons. However, insurance companies can ensure their customers don’t end up waiting for a powerful alternative.

Chatbot assistants are one viable solution for replacing human agents. These bots can handle over 95% of customer interactions, which could be game-changing in the insurance industry. It can drastically reduce wait time and provide immediate attention to customers.

• Lack of personalization

Insurance companies have long suffered from a lack of personalization. Providing personalization to insurance customers is a tough nut to crack, especially with a vast manual support team and traditional rule-based chatbots. 

56% of consumers claim that they might become repeat customers if businesses deliver a positive and personal experience. Therefore, insurance companies have long wished to create and provide a personalized user experience.

• Updated regulations and policy rollouts

A key aspect of an insurance business is keeping up with regulations and any changes to it. Companies must always remain compliant to these regulations and to do so they must educate their workforce effectively.

Likewise, employees must be educated about new policies and plans so that they can pass them on to customers and propose the most suitable solution while consulting them. However, effectively executing that company-wide is a massive task on its own.

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How Will Generative AI Help Financial Customer Call Centers?

Generative AI is growing at a rapid pace. Innovative ways are being found to leverage it in different industries every day. Here are some ways it can help financial customer services:

1. By improving customer experience:

• Generative AI can help provide customers with personalized interactions and experiences. AI can process a vast amount of customer data and patterns to personalize their customer experience. Generative AI can be the key to resolving customer queries or making personalized recommendations effectively.
• AI-powered chat assistants can help minimize or even nullify any dependencies on human assistants. These chatbots can provide instant support to customers through their basic queries and questions, while agents can focus on more sophisticated tasks.
• Not only an instant, but customers can also even expect 24/7 effective support if there is an AI suite to attend them. This would mean customers are never left unattended and can get help as needed, leading to much better customer satisfaction.
• Getting some human help if needed: AI chatbots would understand customers’ queries and sentiments to determine when it is appropriate to hand over their concerns to a human agent, bringing the best of both worlds.

2. By overcoming operational limitations

• Generative AI can help automate a handful of activities, which would make the job easier for human agents. Automating tasks such as fetching or feeding data, summarizing conversation notes, or even drafting responses to assist agents.

This could help insurance companies get a lot of things done with almost the same manpower capacity.

• AI can help make the job easy for agents. AI can assist agents through real time information and conversation-ready battle cards that can make sales calls easy. It would also take care of any laborious activities such as data entry so agents can be at ease. 

These efforts could be helpful in improving the critical attrition rate of the insurance industry. 

• Taking it one step forward, AI can help save a lot of the costs and effort of insurance companies. With better retention rates and automation, companies would spend less time and costs into hiring fresh agents and training them. It would improve the productivity and output of the company.
• AI assistance can help make customer care become more consistent with their quality and knowledge. AI solutions can keep the agents updated with necessary insights, recommendations, and customer background all the time.

This assistance reduces the dependency on an agent's individual characteristics and skill set through a vetted AI solution.

3. More sales & revenue:

• Sales enablement is the most important factor for considering AI solutions. Agents can have much better sales conversion by using AI assist to prepare for customer calls, learning their problems, making the right suggestions, and even comparing different options available.
• AI can also make up for any gap in the sales rep’s individual experience by generating sales pitch, communicating effectively, and even creating any necessary collateral for prospects.

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The bigger picture: Impact of GenAI on insurance companies

More than just providing assistance to customers and agents, GenAI transforms insurance as an industry. With the long-standing challenges resolved by GenAI, insurance companies can focus almost their entire energy on providing better insurance policies and solutions.

As AI takes care of other responsibilities, insurance companies can improve their claim processing and thrive to grow rapidly. Such a change would be beyond any traditional practices or process optimization tools. Not to mention, AI can even participate in claim processing and documentation, which would further improve their business outcomes.

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Use Cases of AI in Insurance Contact Centres

The key is to have a sales enablement suite that would assist agents in their process and chat agents that would help customers with their interactions. Here are some use cases of GenAI applied to insurance contact centers:

• Sales Rep Assist:

Sales Rep assist is an AI tool that would assist agents with the support for different operations such as:

• Fetching customer insights and requirements
• Recommending the right product or solution
• Preparing battle cards to help agents prepare
• Assisting agents with their pitch and supporting information
• Following up calls by creating necessary collaterals
• Help draft sales communication with GenAI

• Website Assist:

Website Assist refers to adding an AI agent that would help increase sales conversion. It can help with:

• Responding to basic customer queries
• Collecting customer concerns and creating tickets
• Automated allocation of customer tickets to agents
• Automated chat with customers and handing over to agent as needed
• Gauging customer sentiment and making the right recommendations

How to Implement AI in Insurance Contact Centers? 

The right way to begin using GenAI into your business is starting with prioritizing. It is crucial that an insurance company performs a SWOT analysis to identify the key concerns to start addressing. 

For instance, if sales is the key concern, insurance companies can leverage GenAI solutions that would enable their internal sales staff to improve sales conversation.

Likewise, if there is a need to assist agents perform a better job in customer support then one can start evaluating the best areas to help them. From helping sales reps prepare for calls to helping them craft collaterals, Generative AI can be used into various different areas of the sales cycle.

The Challenges of Generative AI and How to Overcome Them

Generative AI does present several challenges of its own as well. These challenges are something that a company must consider and evaluate before implementing any GenAI solution.

• Data quality

Quality of data is fundamental to the model development and training that would determine the performance and accuracy of GenAI models. Inconsistent or inaccurate data would mislead GenAI model to wrong results.

Overcoming these challenges require a well-trained AI model as well as accurate data collected from customers. Wrong data collected from customers would yield wrong recommendations and pitch for a sales assist ML model. Data cleaning and preprocessing is vital to the data quality.

• Biases

If trained upon only certain specific touchpoints, ML models might not be diverse enough to provide unbiased output universally. To overcome biases, AI models must be trained to use diverse data sets to be neutral and unbiased. Watching over the consistent output of an AI solution can be a proof to unbiased and neutral functioning of an AI model.

• Responsible AI

AI solutions must be ethical in their applications to avoid any misconduct. To avoid any false commitments and suggestions would mean that the AI is implemented responsibly. Sufficient guidelines and rulesets must be used in the AI application to conduct ethical usage.

• Immature testing

Generative AI must be tested thoroughly to be entirely sure about the models functioning and output. Thorough testing would allow GenAI solutions to operate fairly and accurately as per their initial intent.

There are AI solutions which are readily available in the market to overcome such limitations. Some of the effective solutions to overcome Generative AI limitations include regular ML models and data updates. Moreover, companies can call in an expert to ensure collaborative approach to optimize the solution.

There are proven companies that could assist financial service providers with their customer care and sales conversion. Alltius is one such company that provides a comprehensive set of GenAI solutions and is well-proven in assisting finance companies in managing their customer care and sales initiatives.

To summarize,

The potential of GenAI for financial services call centers is unparalleled and can help companies entirely transform their end-to-end functioning. Not only just satisfied customers, Generative AI can even help companies keep their agents happy. Higher sales, better customer retention, and reduced agent attrition are some of the key perks of using such a solution.

Schedule a quick call with our expert to learn how Generative AI can be helpful to a financial services company like yours.

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