Historical Pattern of Fraudulent Claims During Economic Recessions
Over the past 40 years, every time there has been an economic recession in the UK it has been followed by an increase in fraudulent claims. This can be seen in the historical statistics held by the Association of British Insurers.
It is no surprise then that the same pattern is emerging amidst the current economic turmoil. Increased numbers of otherwise law-abiding citizens are turning to opportunistic fraud to ease financial hardships as the cost-of-living crisis continues.
Recent Warnings and Trends in Fraudulent Activities
In 2022, the National Fraud Intelligence Bureau (NFIB) – part of the City of London Police - and the Financial Conduct Authority (FCA) warned about the risk of ‘cost-of-living enabled fraud’ becoming more prevalent. The most recent statistics released by the City of London Police’s Insurance Fraud Enforcement Department [IFED] have seen those predictions materialised.
Statistical Insight: Rise in Opportunistic Fraud Cases
IFED recently confirmed that reported cases of opportunistic fraud from March 2022 to April 2023 rose by 61 percent from the previous period. Motor insurance fraud was the most common type of opportunistic fraud referred to IFED from March 2022 to April 2023, accounting for 51 percent of the cases the unit received. Property insurance fraud was the second highest, accounting for 29 percent of cases received.
ABI Fraud Statistics for 2023
The latest ABI fraud statistics, released August 2023, report a 19% drop in the number of fraudulent claims detected in 2022, compared to 2021. Despite the drop in volume, the total value of claims fraud fell by just 4% and the value of opportunistic fraud increased by 2%, with a total cost to the industry of £1.1billion. The average fraud, rose to a record £15,000, up 20% compared to 2021.
Understanding Opportunistic Insurance Fraud
Opportunistic insurance fraud occurs when somebody provides false information when applying for insurance, knowingly submits a false claim or takes advantage of an otherwise legitimate situation to exaggerate a claim for financial gain.
Examples could include manipulating data to achieve a cheaper insurance quote, faking an injury following a genuine road traffic accident or claiming twice on insurance after losing an item of jewellery.
Insurers' Response to Fraudulent Claims and Public Expectation
Insurers recognise that many households continue to battle the cost-of-living crisis and strive to pay legitimate claims as quickly as possible. Meanwhile, genuine customers expect insurers to clamp down on insurance fraud, realising it is not a victimless crime. The cost of fraud pushes everyone’s premiums up and all customers end up paying for the dishonesty of some.
A Real-world Case
In August 2023, a ghost broker who charged more than 900 unsuspecting motorists £300 each for fraudulent motor insurance policies was sentenced to 24 months imprisonment. Motorists buying fraudulent policies face the prospect of fines, points on their licence, or their cars being seized and crushed.
The Importance of Accurate Policy Pricing and Fraud Detection
Accurate policy pricing based on true risk calculation and early fraud detection are key for both consumers and insurers. Trusted data has to be the fundamental underlying principle of how insurers tackle opportunistic fraud. That same data can also help insurers to validate insurance applications and legitimate claims, meaning genuine customers get a swifter onboarding process and claim settlements can be expedited.
Customer Expectations and the Role of Integrated Data and Analytics
Today’s customers expect a swift, seamless insurance service. This means that the data and analytics that help insurers to detect and prevent opportunistic fraud must be easily integrated and not cause process delays. CRIF has a suite of data intelligence solutions that can rapidly and seamlessly assist insurers in identifying and investigating fraud.
CRIF's Solutions for Fraud Detection and Prevention
- RADAR is a high-volume screening tool which draws from multiple external data sources, enriching insurers’ internal data, and enabling verification of an applicant’s disclosed claims history, identity, vehicle or property. It delivers results in a sub-second environment for point of quote processing, and helps insurers to detect fraud at the earliest stage.
- The CACHE suite of services comprises shared databases of insurance claims that help insurers to verify an individual's claims history. CACHE-CUE can automatically detect cases where further investigation is required at all stages of the insurance lifecycle, including quotation, policy acceptance, renewal and claims.
- Vehicle Check provides real time screening for any vehicle in the UK allowing insurers to check if the vehicle has a hidden past, if the subject is the rightful owner or if it is registered under a false identity.
- ID Check provides real time screening of personal details, prior to onboarding a customer.
- Sherlock Detection supports insurers when a claim requires further investigation. Designed to deliver counter-fraud intelligence to the investigator, it reduces the time to collect and integrate key information. Actionable insights include: hidden claims connections between parties of past and present claims whether motor, home or personal injury; previously unknown phone numbers or different addresses associated with existing numbers; non-disclosed claims histories at previous linked addresses; inconsistent property attributes, driveway or garage not actually present; previously written off vehicles or outstanding finance on vehicles.
- Scoring and Analytics provide advanced risk profiling capabilities and transform structured and unstructured data into predictive risk insights and powerful pricing tools.
