Mckinsey Launches A Generative Ai Chatbot To Bring Its Knowledge To Clients – The global bank worked closely with the client to build, test and launch a custom chatbot that uses next-generation AI technology to meet customer needs.
ING Global Bank hears from 85,000 customers every week via phone and online chat in the Netherlands, one of its main markets. While 40-45% of these chats are typically resolved by today’s classic chatbot, that still leaves 16,500 customers per week who need to speak to a live agent for help. This could potentially result in longer wait times for customers as they can only get direct assistance for non-urgent requests during business hours.
Mckinsey Launches A Generative Ai Chatbot To Bring Its Knowledge To Clients
The ability of generative AI to interact with human language in ways that were simply not possible before created an opportunity for teams from QuantumBlack, the AI division and ING to explore how advanced chatbot technology could be used to improve the customer experience and provided to customers. Help they need immediately
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The project has helped build a solid technical foundation that puts ING at the forefront of gene-AI applications in the banking sector.
There is a huge challenge for the banking sector to improve the customer experience, but there are also huge risks. says senior partner Andrea Del Milio. Leaders should ask themselves: What value do you add to technology? What benefits can you add to this technology to make it more useful to customers and better meet their needs?”
ING and the team worked for seven weeks to build a productive AI chatbot that provided customers with immediate and tailored assistance while using transparent guardrails to reduce risk. The team started with an in-depth analysis of existing chatbots to identify specific challenges. The final solution involved a multi-step pipeline to generate the best response for the customer, including retrieving knowledge from existing data stores and ranking possible responses based on usefulness. If there are multiple useful answers, the system provides the customer with multiple options – a process called disambiguation.
Finally, before sending the response to the customer, a series of guardrails were installed. To achieve this, ING’s risk stakeholders have been involved in the process from the start, and ING-specific safeguards (for example to prevent advice on mortgages and investment products) have been built using QuantumBlack’s out-of-the-box tools. . Labs, our innovation center for artificial intelligence and machine learning.
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General’s AI chatbot was released on test days to 10% of real customers in the Netherlands who used the support chat functionality in the mobile app. It provided a customer experience that was clearly superior to the classic chatbot, providing customers with more accurate and tailored responses and helping them resolve their queries faster. Since its launch in September 2023, thousands of customers have interacted with the next-generation AI chatbot, making it the first real customer pilot of its kind to run in Europe.
Marnix van Stiphout, CEO of ING, said: “By prioritizing real customer needs, security and ease of use, ING has been able to create a customized customer support tool that provides users with the best possible experience.
The speed of building and deploying a chatbot far exceeds the timeline required to develop previous industry-standard chatbots, which can take years of programming and tuning to get it right. In addition, the new chatbot provided a better customer experience in the first seven weeks of use compared to the previous solution – helping 20% more customers avoid long wait times and enjoy it. As the technology matures, more customers may switch from calls to chat, reducing the pressure on ING’s call centers.
When done right, the use of general AI can be very powerful in creating a better customer experience while prioritizing the safety of banking customers. Stephanie Hauser is a senior partner and one of the global banking and securities leaders
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“When done right, General’s use of artificial intelligence can be very powerful in creating a better customer experience while prioritizing the security of bank customers,” said Stephanie Hauser, senior partner and co-leader of global banking and securities.
As part of a broader effort, ING focused on building capabilities across more than 50 support functions – across risk, contact center and the analytics and technology office – giving ING a silver lining to expand the scales of its Gen-AI efforts. .
Together, ING and the team created a path to double the chatbot’s functionality over the next six months, build a scalable model that can be expanded to other ING countries, and create a technical foundation that enables ING to cover a wide range of cases. Check put. Generations of AI use cases across the group have helped define a blueprint for scaling across ten markets with the potential to impact more than 37 million customers in 40 countries.
Bahadur Yilmaz, ING’s chief analytics officer, said: “This project has helped build a solid technical foundation that puts ING at the forefront of genomic AI applications in the banking sector. Generational AI technology will continue to evolve and we feel we are well positioned to leverage these advances to deliver the best customer experience and remain a technology leader in our industry.
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Leading our global banking and securities performance and banking activities across the European region. Stephanie serves customers…
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In this session, we explored the unique challenges of implementing general AI in production environments, when agents are in direct contact with your customers. We shared the all-in-one solution of Iguazio and MongoDB to build next-generation AI applications that scale effectively and efficiently, with built-in guardrails and monitoring. We show how the end-to-end application lifecycle is addressed: from data management to production governance and monitoring. We shared a live demo of a customer-facing agent talking to multiple customers at a large bank and tailoring her responses and tone to each customer. We also had a live discussion and a crowd-sourced Q&A!
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