Zelros AI
in Action

case 01

Increasing life insurance cross-sales on inbound and outbound contacts

Young girl connecting with nature
Context
Large Mutual Insurer
Life insurance business line
2500 advisors targeted (face to face/phone)
Objectives
Get a better understanding of customer needs
Improve the quality of advice regarding policies’ content
Increase cross-selling and up-selling
Solution
Plug-ins to both structured and unstructured data sources
Prediction of key life events
Recommendations on relevant insurance policies along with personalized selling points

Results

Increased empathy

0.4 additional quotes converted per day per advisor

40% increase in number of quotes

Decrease in junior advisor training time

When did this happen?

case 02

Optimizing sales efficiency to support a new Home Insurance policy launch

Context
Large Mutual Insurer
Home P&C insurance business line
100 advisors (face to face/phone), scaling to 2500
Objectives
Get better insights on customer needs and provide the best advice regarding policies’ content
Secure the successful launch of a new Home Insurance policy and increase up-selling
Solution
Plug-ins to both structured and unstructured data sources
Prediction of key life events
Recommendations on relevant insurance policies along with personalized selling points.
Automated prioritization of products based on business priorities (AI Cockpit)

Results

5-20% increase in quotes conversion rate

20-55% increase in number of quotes

case 03

Medical selection automation for Life Disability Insurance

stories_CS_Case1
Context
Tier 1 bancassurer
Life disability insurance cover
100,000 subscriptions per year
Objectives
Increase the number of subscriptions automatically accepted, and reduce decision time to avoid customer drop out
Complement existing basic decision rules with advanced machine learning decisions
Use AI to assist underwriting doctors in making decisions on complex cases
Solution
Explainable machine learning model trained on Zelros platform on a history of 40,000 anonymized cases
IT integration through API for automation
Zelros App for underwriting doctors

Results

4x increase in the subscription automation rate

93% accuracy in decision

Improved customer satisfaction and operational efficiency

Boy and Dog in Toy Racing Car

case 04

Automating and accelerating the motor insurance underwriting process

Context
Leading French digital broker
Car insurance product
Customer Service agents process hundreds of underwriting documents every day
Objectives
Transform and accelerate the underwriting processes by automating document reading and analysis, including fraud detection
Free agents' time from repetitive tasks and enable them to focusing on the quality of customer service
Solution
AI reading, analysis and extraction of key fields from car insurance specific documents
Injection of the data into the client database for process automation
Processed documents include passports, ID, driving licence, car registration documents, subscription forms, accident reports etc

Results

40%+ subscriptions already automated

Ambition to move to 100% digital underwriting process and 100% focus on customer experience

Processing time for vehicle registration document decreased from 3 minutes to few seconds