Increase ROI for SIU and Subrogation Teams

“Insurers that embrace the right mix of tools, staffing, training and technologies will continue to experience reduced claims costs, more accurate pricing, (and) a competitive edge...” [1]

Existing Insurance industry business models are under attack from a budding new sector of the industry called Insuretech. To keep pace, the utilization of technology and increased Return On Investment (ROI) are critical. Additionally, within the insurance industry, subrogation and fraud success rates must also be accounted for when calculating this important bottom-line figure.

ROI, in relation to insurance companies’ special investigation units (SIU), is a historically reported statistic. In the 1990s, insurers said that for every dollar they invested in anti-fraud efforts, they got up to $27 in return.[2]

These numbers have peaked, and are recently decreasing due to a multitude of factors. A major component is more complex fraud rings and the costs necessary to identify them. Insurance companies have fought back primarily with more personnel training and by using software that attempts to “red flag” these potentially fraudulent claims.

These software programs are successful in identifying more fraudulent claims, but also need continual updates to be current. Additionally, each company has a varying number of files which can be reviewed by these algorithms. These issues equal limitations.

Claims that have been “red flagged” for potential fraud are immediately transferred to a SIU for review by specially trained adjusters. Additionally, general adjusters are trained, using existing company practices and policies, to initiate and transfer claims with suspected fraud or subrogation potential to specific units for further processing.  

All of this occurs within the claims process and ultimately an adjuster must decide to settle or dispute the claim based on the information available. All of these efforts cost money.

Overall, it is important to examine and streamline the available options for an adjuster to make quick, reasonable, fact-based decisions.

When an adjuster only has the claimant’s or witness’ statement, a police report or photos to dictate claim decisions the issue becomes convoluted. Only in substantial loss or loss of life claims have insurance companies been willing to spend the money necessary to obtain objective crash data. This is changing!

The cost for the same technology never increases over time, but always decreases. This process is results driven and utilizes a proven technology.

“66% of SIU claimants, when asked for accident data or presented with adverse data, withdrew their claim.” [3] -“Black Boxes” Myths - Haight/Baker IASIU 2016

Not only can objective crash data deter fraud, support subrogation efforts, and decrease overall payouts, it supports more initial fact-based decisions adjusters. Moreover, it can prove a definitive lack of negligence or personal injury claims.

The CDC, in a 2012 published infographic, shows “that for every 1 fatality, 8 more are hospitalized and another 100 individuals are treated and released.[4] Over the last 20 years, despite vehicle and roadway design improvements, an average of 38,895 people were killed annually. It can be extrapolated that another 311,158 are hospitalized and another 3,889,471 are treated and released each year.

These numbers are astounding! One can assume that for every fatality suffered, nearly eight lawsuits will follow for medical payments - not including any pain and suffering claims.

Let’s start putting real data on the table to aid your decision-making process.

The claimants are due indemnity for the loss they incurred based upon the insurance policy, no more and no less. So why use outdated processes? Start using factually-based claim positions that no one can match without using this data.

Each insurance company has their own formula for calculating ROI. At Black Box Recovery, we use this simple ROI formula to calculate the increase in fraud success rate as a result of using our services.

$ Iapc - Sapc x % Fa = $ Lost to Fraud per Claim x 66% = $ Saved per Claim

Iapc = Indemnity (Average per Claim)

Sapc = Subrogation Return (Average per Claim)

Fa = Fraud rate (Known %)

$ Saved from Fraudulent Payments using Crash Data.

Each company must determine which figures to input into this formula, but simply put, we can increase your successful fraudulent deterrent rate. Do a good job at identifying them and we can do a great job of stopping them!

We can decrease your overall payouts by as much as 20%.

Black Box Recovery is North America’s Only Independent Accident and Crash Data Laboratory. This service is specifically designed to make crash data affordable with no conflict of interests. Join this team to reduce your costs and increase your profits!

Resource Links:

[1] - The State of Insurance Fraud Technology "A study of insurer use, strategies and plans for anti-fraud technology" November 2016

[2] - http://www.iii.org/issue-update/insurance-fraud

[3] - “66% of SIU claimants, when asked for accident data or presented with adverse data, withdrew their claim.” — Car "Black Boxes" Myths, Realities, and Fraud Fighting - By W.R "Rusty" Haight and Scott Baker

[4] - https://www.cdc.gov/vitalsigns/crash-injuries/infographic.html#graphic

David AtkinsonComment