Mortgage fraud can lead to long-term, widespread schemes to illegally obtain money and property.

Fraud in its simplest form is an intentional misrepresentation when one party deceives another by presenting inaccurate information or facts.

Housing or mortgage fraud can be committed by individuals who intend to occupy a property as a primary residence or by groups who commit fraud with the help of rental properties.

Considerable financial losses can occur in real estate. For instance, seven people were convicted in a scam involving $10 million in California in 2019.

There are two distinct kinds of mortgage fraud: fraud for profit and fraud for housing.

Fraud for housing is practiced by individuals who, often with the help of loan officers, misrepresent employment, income, finances, or property values with the goal of achieving real estate ownership.

Similarly, fraud for profit is committed by individuals in the industry who misrepresent or omit relevant details about themselves or their clients in order to maximize profits on a loan transaction.

Fraud for profit can be committed by any professional in the loan transaction chain, including real estate sales agents, loan officers, mortgage brokers, or insurance agents.

The most common individual mortgage fraud scams involve identity theft as well as the falsification of data concerning income or assets.

Identity theft occurs when the real buyer fraudulently obtains financing using an unwilling victim's information, including personal data.

Identity theft for mortgage purposes may also include stolen bank records and tax returns or falsified employment verification letters.

Even property ownership records can be falsified. Scammers can obtain a fraudulent mortgage on a property that they neither own nor occupy.

Fighting Mortgage Fraud

Government bodies have taken important steps to require licensing for loan officers and insurance agencies. Government monitoring is in place to ensure compliance.

In the high-tech modern era, auditing and fraud monitoring companies have powerful automation tools to identify potential theft or fraud by applying machine learning algorithms.