Banking and Finance, Fintech, Insights, Insurance, Retail and Consumer Goods, Use Cases

Learning from customer’s complaints, banks can identify where the wearing down risk is highest so they can take necessary actions. However, receiving thousands of feedbacks and complaints every week, banks don’t have the resources to understand and extract business value from these data, which takes weeks and leads to slow action.

In addition, customers expect banks and financial institutions to anticipate their needs and response to their complaints immediately. Traditionally, complaint management acts after the problem becomes persistent and customer finally reaches out, which may be too late to satisfy and retain unhappy customers.

How can TurinTech help?

TurinTech visualises customer complaints data using understandable graphs, so banks can obtain business insights (e.g the most common complaints) within minutes.

With TurinTech, banks can build smart models on their customer complaints data to auto-tagging complaints by priorities. For example, placing super-annoyed customers in the negative category to ensure zero lag response and minimise negative impacts.

TurinTech also allows banks to build AI to learn from the pattern of cases, auto-monitoring and auto-responding to certain cases with confidence. Models can efficiently predict if something is bothering a customer and recommend a quick remedy to that even before customers reach out.

  • Faster Action. Reduces the average time for the customer service team to response to complaints.
  • Higher Productivity.Relieve customer service team from repetitive tasks, enabling them to focus on more complex complaints cases and take proactive actions.
  • Greater Customer Satisfaction. Provide customers with responses they need efficiently and automatically to delight them.