Technology
Financial industry use AI to understand who their customers are
Published by Jessica Weisman-Pitts
Posted on October 17, 2023
5 min readLast updated: January 31, 2026
Global Banking & Finance Review®
Company
Published by Jessica Weisman-Pitts
Posted on October 17, 2023
5 min readLast updated: January 31, 2026
By Jonathan Sharp, CEO, Britannic
The financial industry has a sea of data that isn’t being used to make intelligent strategic business decisions with a colossal amount of knowledge is left unknown. It’s a dangerous place to be if you don’t know why your customers are contacting you and what their challenges and issues are with your service or product. It is very much a sink or swim situation, but if you don’t know then it is imperative that you find out, so you don’t drown and lose your customers to competitors.
Now is the time to deep dive into the interactions your customers have with your company to discover the detail that you have been missing, which can be turned into real treasures revealing what areas in your processes you need to improve and why. AI interactions analytics can provide a 360° comprehensive view of your digital interactions identifying and analysing key trends and patterns to enable you to implement strategic business decisions that will save money, increase efficiencies, improve customer service and increase margins.
A lot of banks and financial companies are swimming in the dark and don’t know how to improve their customer experience because they don’t know what the problems are and where they sit in the process. The omni-channel environment in the financial industry has a myriad of channels from email, voice calls, social media, reviews, comments, text messages all for customers to contact you on. That is a lot of channels for agents to manage and the data garnered from them is huge and overwhelming that many companies do not analyse it to their advantage, and often it sits there not being used.
Often banks and financial companies have a strategy whether that’s to improve customer service, reduce waiting times or increase first time resolution for example. Solution Providers need to understand what the strategy is and what the success criteria is so they can identify the problem areas to improve. Working with customers to understand exactly what their customers digital journey entails and using AI interaction analytics to analyse the text created from transcribed phone calls, emails, text messages, social media and online reviews etc. AI can then identify key words and patterns so problem areas or opportunities are highlighted and make decisions based on the findings. For example – a bank can identify emails that are enquiring about a loan and pass them onto the relevant team. A Solution Provider can then design and deploy an automated solution that will handle your digital enquiries, so they can be either be dealt with an automated and proactive digital update, or transferred to a human agent if need be. This enables the business to use the data to make intelligent business decisions and design automated solutions to handle enquires and make a difference.
AI interaction analytics is a fascinating solution that can not only collate and analyse text in data but also customer sentiment analysing customers emotions and categorising if it is negative, neutral or positive. Identifying if customers are upset, angry or happy so businesses can understand their experience and improve it. This can be done by analysing voice calls and through text as well.
Customer feedback forms, forums and traditional call recording evaluations only provide a fraction of the feedback you require, and it is often from point in time and when people are emotive, so it is not a true reflection. Whereas AI interaction analytics are because they analyse data and customer sentiment constantly providing an accurate 360° picture and a deep dive into sentiment and the nuances that usually aren’t revealed.
Quality management recruiting and training contact centre agents is always a challenge and AI interaction analytics can be structured to help you with identifying training gaps and share best practice. Companies can use data to not only improve customer service but also discover areas where they can cross sell or use for training and personnel development.
People can do the same thing but with some it works and with others it doesn’t. This is because we have different ways of doing things and sometimes people get better on with others and this what makes us human. By blending AI and humans together we can use AI analytics to match personas of agents/sales people and customers ensuring that we are getting results and improving the customer and agent/sales person experience will be more likely. By looking at their behaviour, sentiment, competence and understanding what are the successful outcomes.
All the above helps drive brand delivery ensuring that you are delivering your brand promises which will increase the power of your brand.
It is critical with any strategy that you define your success criteria so you can measure exactly how you are performing and identify problems and design improvements and test to see if they make a difference. This is an evolutionary process just like the AI interaction analytics solution is, it needs to be taught and will continue to learn with you. It is a evolutionary process that needs to be nurtured to grow with you and will reap the benefits. The more you know about your customers the more you will be able to offer them personalised services, you will retain them and reduce customer and agent churn, save costs by re-engineering your processes and even increase revenue. It is a win-win!
AI interaction analytics refers to the use of artificial intelligence to analyze customer interactions across various channels, providing insights into customer behavior, sentiment, and areas for improvement.
Customer sentiment is the emotional tone or attitude expressed by customers in their interactions with a business, which can be positive, negative, or neutral.
An omni-channel environment is a multi-channel approach to sales and customer service that provides customers with a seamless experience across various platforms, such as online, in-store, and mobile.
Customer experience encompasses all interactions a customer has with a company, from initial contact to post-purchase support, influencing their overall satisfaction and loyalty.
Data analytics involves the systematic computational analysis of data to discover patterns, trends, and insights that can inform business decisions and strategies.
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