12 February 2020
This Insurance company engages in the provision of a range of property insurance, life insurance, retirement products, and other financial services to commercial and individual customers. It operates through the following segments: General Insurance, Life and Retirement, Other Operations, and Legacy Portfolio.
On account of the multitude of products the complexity of queries and grievances of customers was compounded with the severity & constant enhancements to the processes .
- The customer service transaction volume in the customer service department , the agent’s knowledge had a direct correlation to the NPS ( Net promoter score) .
- The call & email volumes were unpredictable & dependent on the seasonality , issues faced.
- Customers were not quick to adopt self serve & hence would reach the 1800 number for solution.
- Customer complaints were not prioritised on account of the increasing complexity
The need was to create an automated, self serve & deflect customer service volumes to self serve . Also model an enhanced workflow which would predict if any customers were in distress where they could have helped prevent the issue.
- Proactively address customer complaints using a machine learning model which would determine the incoming issues & usage of self serve.
- For each customer , the system would trigger a probably score rating the issue , prioritising the queue .
- The scoring mechanism would also determine if the customer would complain on social media
- Implemented an Integrated Net Promoter Score (NPS) can measure customer engagement.
- Right Escalation management: Automate routing of issues to specific queues in order to filter issues that require escalation management into a unique queue where executives with that particular specialisation can work upon it.
- Prioritising cases using ML considering case history, complaint opportunity, severity & resolution path
Configuration and Deployment timeline - 2 Months Study, 3 Months Deployment, 1 Months Transition Time to Go Live- 5 Months from Contract
- 42% increase in positive feedback by customers