Insurance fraud amounts to $308.6 billion every year for the insurance industry of the United States, exceeding the GDPs of many nations. For property and casualty companies, insurance fraud accounts for roughly 10% of their loss ratio, representing $122 billion per year. This translates to $900 more in insurance premiums added to the average American policyholder’s annual insurance costs.
The problem is becoming increasingly difficult to uncover as technology has evolved, with fraudsters using generative AI to forge evidence, including photographs of damage, fake medical reports, and fabricated invoices. From 2022 to 2025, AI-assisted insurance fraud increased fourfold, while one fraud-detection company reported a 475% spike in synthetic-voice attacks targeting insurers in 2024.
Insurers, however, need to balance fraud detection with serving customers with speed. In 2024, claims handling was responsible for 65.2% of all closed complaints; in particular, delays were 22.2% of the complaints. The problem is complicated by the fraud risk management task: How can insurers successfully screen claims without adversely affecting their loss ratio?
This article provides an overview of fraud risk management. First, the concept is defined for those familiar with the claims-handling process. Then we describe the role of fraud screening within the claims-processing framework. The difference between true signs of fraud and false-positive triggers is highlighted, and the necessity of insurance expertise to screen claims is emphasized.
What is fraud risk management?
The Fraud Risk Management process in insurance involves identifying, screening, and escalating fraudulent claims prior to the payment-settlement decision-making phase. This process includes evaluating supporting documents for a claim, detecting anomalies related to indicators of fraud, and preparing files for the SIU. The crucial point is that the determination of fraud falls beyond this process.
The range of activities within Fraud Risk Management entails claims intake, screening, document validation, anomaly detection, risk classification, and SIU referral preparation. This process can be perceived as an evaluation stage positioned between filing a claim and its approval or referral to the SIU.
The key question: Balancing fraud screening versus settlement speed
Here is the dilemma that insurance companies understand yet do not openly discuss. Fraud detection mechanisms, when used universally, can lead to delays in processing genuine claims, since adjusters end up buried under paperwork; low-risk claims get queued together with the high-risk ones; policyholders resort to calling complaint hotlines; and regulators pay attention.
According to data collected by the National Association of Insurance Commissioners (NAIC), delays in processing claims have consistently been among the top reasons for consumer complaints about their insurance companies. As a result, the company that applies the utmost scrutiny to all claims as part of fraud prevention ends up receiving the very complaints it sought to prevent.
This does not imply that the solution is in less fraud screening. The right approach is risk-based screening, which means that in-depth scrutiny should be applied only to cases with appropriate warning signals, and that low-risk claims should receive prompt attention.
How fraud risk screening fits into the claims workflow
A well-designed fraud screening process does not replace your SIU or override adjuster decisions. It prepares better information, faster, so that the right calls get made by the right people. Here is how the process works, step by step.
Step 1: Claim intake documentation review
The first step is a consistency check at intake. Trained reviewers compare the incoming claim against policy data, claimant history, and prior claims records. Does the coverage match the event being claimed? Is the claimant’s history consistent? Are there prior claims with similar characteristics? This initial pass catches basic inconsistencies before they move further into the pipeline.
Step 2: Pattern and anomaly flagging
Fraud indicators are compared to information in claims. Staging patterns, exaggerated damage estimates, discrepancies in the timeline of events, and timing of filing the claim close to the issuance of the policy are some indicators of possible insurance fraud. The task does not replace predictive analytics but works in tandem with such tools to improve their performance. Computer algorithms excel at detecting statistical anomalies. Human review provides insights into patterns of fraud or unusual claims documentation.
Step 3: Documentation verification
This is where items such as receipts, medical records, repair estimates, and photos will be compared for consistency. Repair estimates that don’t line up with any obvious damages depicted in a photo are an indication that something may be wrong. A medical record listing a treatment date prior to the event itself is a clear red flag.
Step 4: Risk scoring and categorization
Once the documentation review is complete, claims are sorted into low, medium, and high-risk categories. This categorization determines the level of review that follows. Low-risk claims move forward. Medium-risk claims get additional scrutiny. High-risk claims are prepared for SIU referral. This prevents adjusters from spending the same amount of time on a routine fender-bender as on a potentially staged multi-vehicle accident.
Step 5: SIU referral preparation
When the criteria for escalating a case to the SIU are met, the reviewers develop an appropriate referral package. The referral package should include details on the issues raised, the documentation collected, and the timelines of events. An appropriately developed referral package will avoid the delays that SIUs usually encounter due to incomplete and inconsistent intake documentation.
Step 6: Fast-tracking verified claims
Low-risk, verified claims do not wait in a queue while high-risk ones are being investigated. They get cleared and moved forward. This is where the fraud screening process actually improves settlement speed for the majority of claims, not just for the suspicious minority. When routine claims are not held up by blanket scrutiny, the whole pipeline moves faster.
Common red flags versus false positive triggers
One of the biggest risks in fraud screening is treating every anomaly as a confirmed indicator. Some signals that look suspicious have perfectly legitimate explanations. The table below shows the most common fraud red flags, what they might indicate, and what the false positive causes often turn out to be.
The goal of trained fraud screening is to distinguish between these two columns. Blanket rules that flag every instance of a red flag signal without context create false positives that delay legitimate claims and frustrate honest policyholders.
| Signal | Likely fraud indicator | Common false positive causes |
| Claim filed shortly after policy inception | Possible staged loss | Genuine early-tenure claim |
| Inconsistent incident timeline | Conflicting statements suggest deception | Claimant confusion or memory error |
| Inflated repair estimates | Padding to increase payout | Regional cost variation in labor and parts |
| Multiple prior claims history | Pattern of suspicious activity | High-risk occupation or location exposure |
| Reluctance to provide documentation | Avoidance behavior | Privacy concerns or difficulty accessing records |
| Third-party involvement with prior fraud links | Organized fraud ring connection | Coincidental shared vendor or contractor |
Why insurance-domain expertise matters for fraud screening
A generic approach to outsourcing is inappropriate for fraud detection processes. The pure software-based approach has several drawbacks as well. Patterns of fraudulent behavior may differ depending on the type of insurance products, geography, and policies. The inability to read policy wording, exclusionary conditions, and documents required will result in too many false positives and missed actual fraud cases.
This becomes increasingly relevant because fraudsters resort to using ever more complex methods to deceive insurers. Generative artificial intelligence is currently used to produce convincing fake medical documentation, repair bills, accident reports, and other required documents. Meanwhile, agentic AI-based tools enable the simultaneous submission of multiple fraudulent claims, and only an experienced reviewer who can distinguish legitimate documents can uncover this fraud.
Three key advantages provided by trained reviewers cannot be replicated by generic staff and software:
- Product knowledge: They have sufficient experience with insurance policies, their contents, and related terminology.
- Fraud detection expertise: Trained specialists understand the specific patterns of insurance fraud.
- Judgment skills: They can assess whether a potential fraud claim requires escalation.
This expertise works best when it is embedded in your existing claims workflow, rather than applied as a standalone filter at the end of the process.
Compliance considerations in fraud risk management
Fraud screening does not operate in a regulatory vacuum. SIU reporting requirements vary by state, and some jurisdictions mandate specific timelines and documentation standards for the referral of suspicious claims to law enforcement or state insurance departments. A fraud screening process that does not account for these obligations creates compliance exposure, not just operational risk.
Structured documentation at every stage of the review process is essential. Each step in the screening workflow should produce a record that supports an audit trail. This includes the flagged anomalies, the reviewed documentation, the assigned risk categorization, and the basis for any SIU referral.
Data handling is another consideration. Claimant information processed during fraud screening is sensitive and subject to state privacy regulations. Access controls, encryption, and data retention policies need to be in place for any team handling claims documentation.
Carriers working with external fraud-screening partners should ensure those partners operate under defined protocols that meet state-specific SIU reporting standards. This protects the carrier’s audit trail and reduces exposure if a claim is later challenged in litigation or regulatory review.
Techsurance uses ISO 27001/9001-certified processes and works with teams of subject matter experts to deliver excellence in insurance operations across underwriting, claims processing, hindsighting, and back-office operations. This blend of skill and process robustness is augmented by technology to ensure that fraud detection occurs earlier, helping insurers and MGAs avoid regulatory issues and prevent customer angst.
How insurers maintain oversight when using external fraud screening support
A common concern about external fraud screening is the question of control. Who makes the final call? The answer is always the carrier or SIU. External screening teams handle documentation, categorization, flagging, and referral preparation. They do not make fraud determinations, nor do they communicate directly with claimants about the status of a review.
The carrier retains decision authority at every point. The external team’s role is to present better-organized, more thoroughly reviewed information so that those decisions are made faster and with greater confidence. Here is how oversight is maintained in practice:
- Defined scope: External reviewers work within a clearly documented scope that specifies what they flag, what they escalate, and what they pass forward without action.
- SLA-based escalation: High-risk flags are escalated within defined timeframes to prevent time-sensitive cases from being held up in review queues.
- Audit trail: Every step in the screening process is documented, giving the carrier a complete record of the review history for any claim.
- Carrier sign-off: No referral package goes to SIU without carrier review. The external team prepares; the carrier decides.
Conclusion
The trade-off between fraud screening and settlement efficiency is real, but it doesn’t have to go unmanaged. There is no need to pick sides between covering your loss ratio and covering your policyholders. Risk-based screening, coupled with knowledgeable reviewers, achieves both at once.
By incorporating screening into the claims-handling process from the beginning rather than tacking it on at the end, you build an efficient system in which low-risk claims are expedited, high-risk claims are fully prepared for submission to the SIU, and adjusters are free to focus on what really matters. Everything else is handled behind the scenes.
If suspicious-claim review is creating bottlenecks in your settlement timelines, a short workflow conversation with our team at Techsurance can help identify where targeted screening support fits into your existing process.
FAQs
What are common red flags in insurance claims?
The most common red flags include claims made immediately after the insurance policy is purchased, discrepancies between the event date and the dates on the claim forms, repair costs and/or medical expenses higher than the regional average, previous claims with similar red flags, and resistance to providing any documents. It must be noted, however, that a single red flag does not prove fraud.
How do insurers balance fraud checks with fast claims settlement?
Insurers balance fraud checks with fast claims settlement via risk-based screening. Rather than conducting an analysis that treats all claims equally, the insurer will classify claims by risk during the initial intake stage. Lower-risk claims will move through the process quickly, while medium- and higher-risk claims will undergo further investigation or be sent to SIU.
What is an SIU referral?
A Special Investigation Unit (SIU) referral is the escalation of a suspicious claim to a dedicated team of investigators with the authority to conduct a formal fraud investigation. SIU referrals are triggered when a claim shows multiple red flags that cannot be resolved through documentation review alone.
Can fraud screening be outsourced safely?
Yes, with the right safeguards in place. The critical requirements are that the external team has insurance-domain expertise, operates under defined protocols, handles data in accordance with applicable privacy regulations, and works within a model that keeps final decision authority with the carrier.
How much does insurance fraud cost the insurance industry?
Across all lines of insurance, fraud costs the industry approximately $308.6 billion per year. For property and casualty insurers specifically, the annual cost ranges from $90 billion to $122 billion. This translates to an average premium increase of roughly $900 per policyholder per year.
What is the difference between fraud detection and fraud investigation?
Fraud detection requires identifying patterns or signs that a claim needs further inspection. The process of fraud investigation is the inquiry undertaken once a case has been flagged.