10th October 2024
Utilising Artificial Intelligence within your complaints management processes and systems
By Anthony Eghan, Business Development Manager, Civica
Utilising artificial intelligence (AI) within business operations and systems has become a high priority for many firms. Implemented in the right way, AI has the potential to deliver efficiency gains, cost savings, a unique competitive edge and exceptional customer service.
Earlier this year, the Financial Conduct Authority (FCA) published their approach to AI, which followed the Government’s publication of its pro-innovation strategy. The FCA stated that they are a technology-agnostic, principles-based and outcomes-focused regulator. They went on to state that they have been carefully reviewing and understanding how firms are safely and responsibly adopting new technology, which included understanding what impact AI innovations are having on consumers and markets. They were keen to point out that scrutiny of the systems and processes firms have in place to ensure regulatory expectations are met, remained a priority. However, their conclusions relating specifically to AI were very positive, confirming that AI could make a significant contribution to economic growth, capital market efficiencies, improve consumer outcomes and further improve regulation.
Here at Civica we have been exploring how AI can further improve the critical services we provide for our customers. Specifically, over the last year, the iCasework team at Civica have been exploring how AI could be utilised within complaint handling processes and the iCasework solution used by our existing clients, prospective clients and industry partners. Some of the areas we have explored are detailed below:
1. Intelligent complaint routing:
AI can be embedded into complaints and feedback routing processes to assist with analysing the nature of the complaint, the customer's previous interactions, and the firm's internal capabilities to direct complaints to the most appropriate department or specialist. This can help ensure that complaints are handled by the right person with the necessary expertise, leading to faster and more effective resolutions. By incorporating the consumer duty into the complaint routing logic, firms can ensure that complaints are handled fairly and consistently, taking into account the customer's best interests.
2. Sentiment analysis:
Sentiment analysis of audio call recordings and text entered into data fields can be used to analyse the emotional tone of customer complaints and feedback, allowing firms to quickly identify and address any recurring issues. By incorporating the consumer duty into the sentiment analysis model, firms can prioritise complaints that require urgent attention and demonstrate their commitment to putting the consumer's interests first. This can help firms improve customer satisfaction, reduce the number of complaints, and demonstrate their compliance with the consumer duty.
3. Predictive analytics:
Predictive analytics can be used to analyse historical complaint data and identify patterns and trends that may indicate potential issues before they escalate. By incorporating the consumer duty into the predictive analytics model, firms can prioritise areas where they need to improve their products, services, or processes to prevent complaints from occurring in the first place. This can help firms demonstrate their commitment to the consumer duty by continuously improving their offerings and putting the consumer's interests first.
4. AI complaint handling assistant:
AI-assisted complaint handling functionality can involve using AI models to assist complaint handlers in categorising complaints, making decisions, providing recommendations and drafting appropriate response letters. This can help ensure that complaints are handled fairly, efficiently, and in accordance with the consumer duty. By incorporating the consumer duty into the AI-assisted complaint handling process, firms can demonstrate their commitment to putting the consumer's interests first and improving their complaint handling processes.
5. Automated redress assessment:
In the assessment of redress to be paid to the customer, AI can be utilised in several ways to ensure fairness, transparency, and compliance with the consumer duty. AI-powered algorithms can be used to automatically assess the redress amount to be paid to the customer based on the severity of the complaint, the firm's policies and procedures, and the customer's individual circumstances. This can help ensure consistency and fairness in the redress process, reducing the risk of human error or bias.
6. Identification of vulnerable customers:
AI capability can be utilised by complaints and case management systems to help identify vulnerable customers by analysing various data points, such as:
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Demographic information (age, gender, location)
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Financial information (income, assets, debt)
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Health information (medical conditions, disabilities)
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Life events (divorce, bereavement, job loss)
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Customer feedback and satisfaction data.
By analysing these data points, AI-powered systems can help firms identify customers who may be vulnerable and prioritise their complaints accordingly.
7. Personalised complaint handling:
AI can be used to provide personalised complaint handling for vulnerable customers by tailoring the communication style, language, and approach to ensure that the customer fully understands and is comfortable throughout the complaint handling process. This can involve:
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Adapting the communication style to the customer's preferred method (e.g., phone, email, chat)
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Using plain language and avoiding jargon or technical terms
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Providing additional support or resources, such as signposting to relevant organisations or providing information on financial assistance
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Offering flexible communication times or formats to accommodate the customer's needs.
By providing personalised complaint handling, firms can improve the customer experience and satisfaction levels for vulnerable customers.
8. Emotional intelligence:
AI-powered systems can be trained to recognise and respond to emotional cues in customer communications, such as anxiety, frustration, or distress. This can help firms provide more compassionate and empathetic responses to vulnerable customers, improving their overall experience and satisfaction with the complaint handling process. For example:
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Using natural language processing to identify emotional cues in customer communications
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Providing empathetic responses and acknowledging the customer's feelings
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Offering additional support or resources to help the customer manage their emotions or stress levels.
Providing regular updates and follow-ups to ensure that the customer is feeling supported and understood.
These are just some of the areas the iCasework team at Civica have been exploring. It is clear that by incorporating AI into the iCasework complaints and case management system, our clients can enhance their ability to handle complaints effectively, improve customer satisfaction, reduce operating costs and better deliver products and services to their customers.
For further information about how Civica can help your organisation, please contact the team at Case Management software powered by iCasework | Civica.