AIC - CH. 6

Cluster analysis

A model that determines previously unknown groupings of data.

Internet of Things (IoT)

A network of objects that transmit data to and from each other without human interaction.

Staged accident

An accident deliberately caused by a person who intends to feign injury and collect on the ensuing claim.

K-means

An algorithm in which "k" indicates the number of clusters and "means" represents the cluster centroids.

Centroid

The center of a cluster.

Describe the concept of padding in regard to insurance fraud.

When insureds increase the amount of a claim to make up for deductibles or past premiums paid.

Concealment

An intentional failure to disclose a material fact.

Describe the elements that constitute fraud.

1. An individual or an organization intentionally makes an untrue representation. 2. The untrue representation concerns an important or a material fact or event 3. The untrue representation is knowingly made 4. The untrue representation is intended to deceive. 5. The victim relies on and acts on the untrue representation 6. The victim suffers some detriment such as loss money and or property as a result of relying upon and acting on the untrue representation.

List four questions a claims representatives can ask to frame a balanced claim investigation when fraud is suspected.

1. Given the circumstances of the loss, what are reasonable or expected actions/responses of the affected party? 2. Is part of the reasonable action or response missing? 3. Has something been added to the reasonable action or response? 4. Is there physical evidence to support the reported version of the loss?

LIst six indicators of possible fraud.

1. Parties involved supply vague information. 2. Conflicting information appears in documentation or witness accounts. 3. Known attorney/medical provider combination is present. 4. Databases indicate multiplet similar losses for the same individual. 5. Loss occurs soon after policy interception. 6. Insured or claimant is uncooperative or evasive.

Describe the broader framework of fraud detection beyond the claims representatives investigation.

A claims representatives detection of fraud fits into a broader framework of efforts on the part of government, the insurance industry, and the public to detect and prevent insurance fraud.

Special investigation unit (SIU)

A division set up to investigate suspicious claims, premium fraud or application fraud.

Material fact

A fact that is significant to a decision or matter at hand.

Misrepresentation

A false statement of a material fact on which a party relies.

Identify a limitation of using fraud indicators to identify fraud.

A limitation of using fraud indicators, the traditional approach to identifying fraud is that doing so means depending on fraud that has happened in the past. Intelligent and innovative fraudsters will change their approaches and patterns, limiting the usefulness of these indicators. The traditional approach to detecting fraud is also highly subjective and depends on claims reps experience in the field.

Unsupervised learning

A type of model creation, derived from the field of machine learning, that does not have a defined target variable.

Hard fraud

Actions that are undertaken deliberately to defraud.

Insurance fraud

Any deliberate deception committed against an insurer or an insurance producer for the purpose of unwarranted financial gain.

Describe what claims representatives must balance in their investigation when they suspect fraud.

Claims representatives must balance a suspicion of fraud with the possibility that a claim is legitimate despite the presence of one or more indicators of possible fraud.

Define what a false claim is.

False claims arise when an insured pursues a claim for property damage or injury that has not actually occurred.

Soft fraud (opportunity fraud)

Fraud that occurs when a legitimate claim is exaggerated.

Explain how insurers use computers to detect indicators of possible insurance fraud.

Many insurers now use computer programs to detect characteristics that are common to fraudulent claims. Such programs can analyze vast amounts of data across different lines of insurance to identify claim patterns and other similarities that may indicate fraud. Several organizations, such as Insurance Service Office (ISO), offer electronic anti fraud databases that contain claim-related records or provide access to public records that may be used to gather evidence of fraud.

Describe what the International Association of Special Investigation Units (IASIU) offers special investigators.

OFfers professional development for special investigations. In addition to organizing an annual education conference, the IASIU created and administers the Certified Insurance Fraud Investigator (CIFI) certification.

Describe the advantages of pre-inspection program that requires insurers to physically inspect vehicles as a prerequisite to providing insurance.

Pre-inspection programs are effective in reducing theft claims for nonexistent or phantom vehicles. Pre-inspection can also deter inaccurate reporting of drivers and vehicle garaging locations that results in lower-than-adequate premium.

Describe the problems inherent in predictive models and identify a solution.

Predictive models are based on historical information and fraud is ever evolving. A solution to the problem is unsupervised learning by means of a cluster analysis.

Describe two protections commonly found in the laws for claims representatives who are investigating suspected fraud.

THe first protection in the laws for claims representatives who are investigating suspected fraud involves extending the time limit within which an insurers investigation of a claim must be completed and the claim must either be accepted or denied. The second protection allows an insurer not to disclose to an insured that fraud is suspected if there is evidence that the insured has commited fraud.

Identify the two costliest white-collar crimes in the US.

Tax evasion is the most costly and US insurance fraud is the second.

Explain why soft fraud is also known as opportunity fraud.

The perpetrator of soft fraud uses the "opportunity" of a legitimate claim to obtain unwarranted personal gain.

Data mining

The study of large amounts of data to find new relationships and patterns that will assist in developing business solutions.

Social network analysis

The study of the connections and relationships among people in a network.

Telematics

The use of technological devices to transmit data via wireless communication and GPA's tracking.