Organizations across all industries are eagerly exploring the many ways AI technologies can help them increase efficiencies, serve customers better, and introduce groundbreaking new innovations.
Aviva is one of them. We have AI initiatives in areas like pricing, claims and personal insurance and are gradually expanding our data science footprint across the organization. We are thoughtfully integrating AI capabilities in ways that will improve our customer experience while enhancing our internal operating model.
Aviva’s AI projects
We currently have several AI-powered projects in a variety of stages, from ideation to proof of concept to implementation. Here are some of the initiatives we’re working on:
1. GCS proof of concept: The compounding cost of inefficiencies
The quoting journey can be a long and arduous process. Multiple parties — typically a broker, underwriter, and risk teams — can all review an initial new business submission report which can be up to 100 pages.
Reports are rarely formatted the same way and can have missing information, making it difficult to find relevant details causing a lot of back and forth in the quoting process. Unfortunately, this results in lengthy delays for the customer.
We are testing a GenAI system that can scan documents, detect missing information and extract and source important information. Those highlights can be summarized so the underwriting team doesn’t have to comb through all pages of each document and can instead focus on relevant data points to create a quote.
If there is missing information, they can quickly identify it and ask the broker to complete the elements so they can come up with a final decision faster. This system decreases processing time, provides a better customer experience, increases our capacity to handle quotes and offers net-new data insights.
2. Claims: Total loss at First Notification of Loss
Reaching the final decision to repair or declare a vehicle a total loss after an accident is time-consuming and expensive. Using predictive modeling, we can speed up the decision process to serve customers better and reduce costs.
We developed an AI model that can review historical data and identify trends related to economic factors associated with accidents. These include:
- Cause of loss
- Repair cost
- Relevant vehicle details, e.g. make, model, age and current value
With this information, the model can determine whether it’s prudent to repair or declare a damaged vehicle a total loss after an accident.
This means the customer could get a clear answer immediately and costs incurred for both getting the vehicle assessed and providing a rental car can be minimized.
Although AI is the tool, Aviva’s principle is to put the human at the heart of the decision. When the model makes a prediction, a claims adjuster will always make the final call as they may have insights that the model does not.
3. Enterprise-wide: Managing fraud at Aviva
Fraud has a ripple effect across an organization. It leads to higher premiums, extended waiting time for legitimate policyholders and poorer financial outcomes for our business.
We’re looking to transform fraud management using an algorithmic process. Our ambition is to screen every customer transaction for fraud purposes in both real-time and batch runs - we’ll have a better line of sight to fraud before it happens and improve our processes when managing it.
To achieve this, the fraud engine will hold a fair balance of rule- based alerts, machine learning models and will tap into third- party services to optimize the quality of results. The solution also blends human intervention with risk mitigation processes to minimize losses where possible.
This screening process will be replicated for every decision point across the customer lifecycle and will have active monitoring in place to increase the engine’s level of sophistication over time.
How does AI benefit our customers?
As we continue to develop and roll out AI models to help us inform and carry out the work across the organization, we anticipate several benefits for our customers over time.
- Faster turnaround times due to more efficient workflows
- Cost savings in the prevention of fraud to ensure risks are fairly priced
- Better recommendations based on historical experience
- Standardized decisions for consistent service
We’re hopeful about the future of AI and its capacity to help us bring business efficiencies and serve our customers even better. We’re also aware that our business partners are likely innovating with AI as well, and that the resulting solutions will “talk to each other”, which will inform the way we proceed.
Want to learn more?
Reach out to our Global Corporate and Specialty team at gcs.ca@aviva.com
