Seldon Case Studies How Covéa plan to save £1 million detecting fraudulent insurance policies

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	How Covéa plan to save £1 million detecting fraudulent insurance policies Seldon

How Covéa plan to save £1 million detecting fraudulent insurance policies

Seldon

Technology Category	Analytics & Modeling - Machine Learning Application Infrastructure & Middleware - API Integration & Management
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Use Cases	Fraud Detection
Services	Data Science Services
Challenge	Covéa Insurance Plc, the UK underwriting business of leading French mutual insurance group Covéa, serves two million policyholders and generated over £725.7 million in premiums in 2020. The company is facing a significant challenge in the form of insurance fraud, which is costing the industry over £1bn a year. One of the most complex and hard-to-detect types of fraud they face is Ghost broking. This is when a policy is purchased by a middle person for a customer using false or stolen information to reduce the premiums. In the event of a claim, these policies would be legal and Covéa would have to pay out. As Covéa is mainly an underwriter, they often do not deal with the policy holder directly, so they had less data to work with to detect fraud. The call handling team were doing manual searches and checks on over two million new quotes per day. The scale was far too much to deal with in an efficient timeframe. Read More
About Customer	Covéa Insurance Plc is the UK underwriting business of leading French mutual insurance group Covéa. The company offers commercial, motor, high net worth, property and protection insurance through its Standard & Poor’s A+ stable rating. Covéa Insurance serves two million policyholders and generated over £725.7 million in premiums in 2020. Their goal is to become the most advanced AI factory in the industry and to deliver value to customers and partners through efficiency and personalisation. Read More
Solution	Tom and his data science team at Covéa developed a solution that targets ghost brokered policies, using the capabilities of Artificial Intelligence (AI) with a “human on the loop” system to spot fraudulent activity patterns. They needed to put an ML pipeline into place quickly. They had the Python and Kubeflow skills in-house. They needed to be able to deploy models quickly and, most importantly, they had to be able to explain the decisions their models were making for the high standards of regulatory compliance within Financial Services. After a number of trials and proof of concepts, Tom chose Seldon Deploy as his team’s model serving and explainability tool. The models were put into production by a team of just four people using Seldon Deploy. The models were able to recommend over 1,000 existing policies to be reviewed by the Policy Validation Team. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Application Infrastructure & Middleware - API Integration & Management

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Services

Data Science Services

Challenge

Covéa Insurance Plc, the UK underwriting business of leading French mutual insurance group Covéa, serves two million policyholders and generated over £725.7 million in premiums in 2020. The company is facing a significant challenge in the form of insurance fraud, which is costing the industry over £1bn a year. One of the most complex and hard-to-detect types of fraud they face is Ghost broking. This is when a policy is purchased by a middle person for a customer using false or stolen information to reduce the premiums. In the event of a claim, these policies would be legal and Covéa would have to pay out. As Covéa is mainly an underwriter, they often do not deal with the policy holder directly, so they had less data to work with to detect fraud. The call handling team were doing manual searches and checks on over two million new quotes per day. The scale was far too much to deal with in an efficient timeframe.

About Customer

Covéa Insurance Plc is the UK underwriting business of leading French mutual insurance group Covéa. The company offers commercial, motor, high net worth, property and protection insurance through its Standard & Poor’s A+ stable rating. Covéa Insurance serves two million policyholders and generated over £725.7 million in premiums in 2020. Their goal is to become the most advanced AI factory in the industry and to deliver value to customers and partners through efficiency and personalisation.

Solution

Tom and his data science team at Covéa developed a solution that targets ghost brokered policies, using the capabilities of Artificial Intelligence (AI) with a “human on the loop” system to spot fraudulent activity patterns. They needed to put an ML pipeline into place quickly. They had the Python and Kubeflow skills in-house. They needed to be able to deploy models quickly and, most importantly, they had to be able to explain the decisions their models were making for the high standards of regulatory compliance within Financial Services. After a number of trials and proof of concepts, Tom chose Seldon Deploy as his team’s model serving and explainability tool. The models were put into production by a team of just four people using Seldon Deploy. The models were able to recommend over 1,000 existing policies to be reviewed by the Policy Validation Team.

Impact #1	The models were able to recommend over 1,000 existing policies to be reviewed by the Policy Validation Team, saving £350,000 in the first four months of 2022.
Impact #2	Covéa has won The Insurance Times Claims Excellence awards 2022 – Fraud Solution of the Year and have been nominated for The British Claims Awards 2022 – Counter Fraud Initiative.

Impact #1

The models were able to recommend over 1,000 existing policies to be reviewed by the Policy Validation Team, saving £350,000 in the first four months of 2022.

Impact #2

Covéa has won The Insurance Times Claims Excellence awards 2022 – Fraud Solution of the Year and have been nominated for The British Claims Awards 2022 – Counter Fraud Initiative.

Benefit #1	Saved £350,000 in the first four months of 2022 by identifying over 1,000 existing policies for review.
Benefit #2	Won The Insurance Times Claims Excellence awards 2022 – Fraud Solution of the Year.

Benefit #1

Saved £350,000 in the first four months of 2022 by identifying over 1,000 existing policies for review.

Benefit #2

Won The Insurance Times Claims Excellence awards 2022 – Fraud Solution of the Year.

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Overview

How Covéa plan to save £1 million detecting fraudulent insurance policies

Operational Impact

Quantitative Benefit