Tag: generative AI

AI-Powered Customer Support: A Win-Win for Insurers and Policyholders

AI-Powered Customer Support: A Win-Win for Insurers and Policyholders

AI-powered customer support is a major catalyst for change in the global insurance sector, enabling numerous benefits for insurers and policyholders alike. The insurance industry has already shifted focus towards offering top-notch customer service with a more customer-oriented model. As per several reports, in 2021, more than 40% of CIOs scaled up their budgets for implementing AI for their pilot projects in the insurance sector with an aim to enhance customer service.  The customer base in the insurance and financial services sector now desires more personalized solutions along with quicker processing for inquiries, and enhanced security for personal information, among other customer-focused aspects. Here are some advantages enabled by AI-powered customer support.  Insurer Customer Service- Benefits of AI in Insurance AI in insurance has been a game-changer for the industry, offering several advantages for both companies and their policyholders in terms of insurer customer services and support. Here’s looking at some of them in a nutshell:  How Else Can AI-Powered Customer Support Help?  AI-powered customer support is already revolutionizing the sector rapidly. Companies like Edelweiss General Insurance (EGI) have already set the ball rolling by introducing AI-based voice bots for enabling registrations of motor claims. This helps customers initiate their claims swiftly and seamlessly. This AI bot can easily interact with customers in English, Hindi, and even Hinglish. It also enables registration of claims in real-time on a 24-7 basis while offering round-the-clock support alongside.  These AI-backed insurer-policyholder interactions go a long way towards simplifying customer support and service, answering questions, offering guidance and information, registering claims, offering support around the clock and streamlining claims management. Bots will also enable swifter resolution of claims along with enhancing customer satisfaction and operational efficiency levels considerably. Interactions can be easily automated while robotic interpretation of voicemails helps save time and enhance overall accuracy levels before calls reach human representatives. AI also enables automated customer support throughout multiple channels, which ensures better responsiveness and availability. It can also augment interactions with customers through augmented email tagging and messaging alike.  AI in insurance can also analyze big data sets while suggesting relevant content based on customer location and behaviour among other aspects. AI can evaluate customer behaviour and sentiment to improve responses in the long run. It also builds personalized customer experiences, making it easier to bypass issues before they crop up. AI can help customer service representatives take care of their follow-up duties in time. Agents get help with writing in real-time along with insights from customer data. Generative AI can hugely boost customer segmentation in analytics. It can easily identify customer similarities and patterns by evaluating huge amounts of customer information. This includes psychographic, demographic, and behavioural information. It helps in segmenting customers more effectively. Insurers can benefit from features like automated feature engineering, personalized recommendations, customer clustering, predictive modelling, and sentiment analysis.  To sign off, AI-powered customer support helps insurance companies greatly in terms of enhancing their customer support and service functions with better guidance, quicker responses, and timely assistance. It is certainly the way forward for the industry, going by the recent trends.  FAQs How does AI-powered customer support enhance the insurance experience for policyholders? AI-powered customer support boosts the overall experience for policyholders greatly. They can get instant and timely resolutions to their queries along with better engagement and understanding of their concerns. At the same time, they also benefit from faster claims registration, management, and handling along with quicker and more hassle-free onboarding and claims processing.  What specific tasks and processes in the insurance industry can AI-driven customer support streamline and improve? AI-driven customer support can not only improve, but also support various processes and tasks including customer communication and notifications, answering questions, providing relevant content, registering claims, archiving requests, following up with requisite channels, managing claims, and more.  What are the potential cost-saving benefits for insurers when implementing AI-powered customer support? Insurance companies can save time and money considerably on customer support and service processes by automating diverse tasks. From eliminating the need to manually store, archive, and gather data to doing away with paper-based systems, the cost savings are huge for insurance companies.  How can insurers ensure the security and privacy of policyholder data while using AI in customer support interactions? Insurance companies can ensure more privacy and security of policyholder information while deploying AI for their customer support-based interactions. This is possible with steps like data encryption, fraud detection mechanisms, identification of suspicious customer behaviour patterns with relevant algorithms, and more. 

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How Generative AI Can Reignite Customer Relationships for Banks

How Generative AI Can Reignite Customer Relationships for Banks

The influence of generative AI in banking has reached profound levels in recent times. The implementation of AI and banking customer experiences today go hand in hand. There is a school of thought that generative AI can reignite and revitalize customer relationships in banking.  Early adopters of generative AI will naturally benefit from its productivity boosts and its impact on customer relationships. Accenture has reported how 90% of working hours in the banking sector may be eventually influenced by LLMs or large language models. 54 % of work timings, as per this report, has immense potential for automation via AI in the future. 30% of employee productivity benefits may also be witnessed by the sector by 2028. Generative AI can influence almost all sectors and aspects of the banking industry. Here’s looking at the same in more detail.  Advantages of Generative AI in Banking  Here is how customer relationships in banking get a boost through AI-powered customer engagement and other benefits of generative AI models.  How do Customers Benefit from Generative AI in Banking?  Generative AI in banking can completely and positively transform customer relationships in banking along with boosting overall engagement levels considerably. Here are some pointers worth noting in this regard.  It is not just about serving customers better. Banks also get several other advantages of using generative AI. They can apply AI and neuroscience-based Gamification to match the cognitive and emotional capabilities of aspirants with job profiles in the company. Using analytics can enable better candidates who are the right fit for banking roles in a more competitive and specialized environment.  At the same time, generative AI systems can also go a long way towards enabling superior employee training and retention. They can analyze employee data to predict future attrition rates and recommend steps for better talent retention. With high turnover costs in the banking sector, these insights will be hugely valuable for most entities. Data quality, of course, is a key cornerstone behind the successful implementation of these applications and also the algorithms used by banks. Hence, there is a growing need to invest in the right AI and analytics talent in order to leverage generative AI in banking to the best possible extent.  FAQs How can generative AI enhance the personalization of banking services for customers? Generative AI is crucial in enhancing banking service personalisation levels for customers. It helps banks suggest the right products/services to customers based on their preferences and needs. It also helps customers get individualized solutions and assistance from support teams.  What role does generative AI play in improving the customer experience in the banking industry? Generative AI plays a major role in enhancing customer experiences in the banking sector. It enables personalized recommendations and advice, along with customized service and support. It helps Chatbots and other tools respond faster to customer inquiries, replicating human conversations and understanding customer intent better.  How can banks use generative AI to predict and address customer needs proactively? Banks can leverage generative AI to forecast customer needs better, based on an analysis of their spending trends, transaction history, and preferences. They can address these needs swiftly and at the right time based on these customer insights.  What are the potential benefits of leveraging generative AI to reignite customer relationships in the banking sector? There are several potential benefits of leveraging generative AI for enhancing customer relationships in the banking industry. These include improved customer experiences and engagement, quicker resolutions of customer problems, personalized customer solutions and recommendations, and more.

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Customer Feedback Management with GenAI

Transforming Customer Feedback Management with GenAI

Customer feedback management and customer service are steadily being transformed with the use of GenAI or generative AI is a huge buzzword today. This transformation in customer support functions has naturally led to GenAI being a tool for business growth and empowerment. There are several aspects that clearly indicate the increasing adoption of GenAI amongst businesses. There are several aspects that clearly indicate the increasing adoption of GenAI amongst businesses. 51% of marketers, as per reports, presently use GenAI while 22% of them plan to use the same soon. 76% of marketers in copy and content writing are already using GenAI while 53% call it a game changer for data analysis, user messaging personalisation, marketing campaign creation, and optimisation/envisioning of SEO strategies. Generative AI has a direct impact on overall productivity, potentially adding innumerable value to the economy worldwide. 75% of GenAI value may be delivered in four categories, namely marketing and sales, customer operations, R&D, and software engineering. Banking, life sciences, and high tech will be industries that will witness the most impact. Here’s looking at the effect of GenAI on feedback management and customer service.  How is generative AI used in customer service? GenAI is highly effective in terms of streamlining customer feedback management and service alike. Here are a few aspects that should be understood in terms of how it can bring about a transformation in the segment.  How GenAI Can Help You Collect and Analyse Customer Feedback GenAI is a great tool to collect and evaluate customer feedback. Here are some major points to keep in mind in this regard:  The Future of Customer Feedback Management with GenAI Customer feedback management will undergo a huge transformation with GenAI in the near future. Here are some aspects that will become mainstream for companies.  To sign off, it can be said that GenAI will completely reshape customer feedback management and service functions in the future. More businesses will find greater value in leveraging generative AI to enhance customer journeys, tackle issues, and plug gaps. This will naturally put them on course towards achieving steady growth and their objectives.  FAQs  GenAI can transform feedback management through helping companies swiftly gather feedback from multiple channels and analysing the same. This results in helpful insights for companies to take better decisions. They can understand customer preferences and pain points while taking steps to address the same.  GenAI can easily accommodate diverse sources of feedback. These may include social media platforms and communities, emails, reviews, and direct interactions with the company. These can be easily gathered and analysed to generate valuable insights.  GenAI can be customised to various industries including life sciences, healthcare, technology, banking and financial services, and many more. Language learning models and generative AI-based algorithms can be customised to analyse and gather specific data and churn out insights accordingly.  There are concerns related to data privacy and security as far as the usage of GenAI is concerned. The analysis and training of input data has led to these concerns. However, with advanced encryption and other security measures, businesses can resolve the same seamlessly. At the same time, consent gathering and management is another solution in this regard. 

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