| The mortgage liquidity crisis has hit independent | | | | alliances, internet lead companies are not only |
| mortgage brokers hard. Fewer consumers are | | | | accessing databases to verify the accuracy of |
| qualifying for loans, and those who do are requiring | | | | consumer information, but they also are appending |
| more time to do so. In addition, home sales are | | | | queried data to their leads to make them more |
| declining in most areas, so the number of new home | | | | valuable to mortgage brokers. For example, of |
| loans is down. All of this means fewer clients and less | | | | Newport Beach, California, has aligned with First |
| business for the average mortgage broker. | | | | American Financial CoreLogic to append detailed |
| Fortunately, new developments in the internet lead | | | | property and loan data to its mortgage leads at no |
| market are helping some brokers thrive, even in the | | | | additional charge. Instead of receiving a short-form |
| credit crunch. | | | | lead containing only the basics about the consumer, |
| Traditional internet mortgage leads are gathered from | | | | brokers buying leads from obtain a long-form lead |
| consumers who go online and request a quote for | | | | that includes detailed information such as property |
| any kind home loan: new, refinance, second, home | | | | size, APN code, the original lender, appraised value, |
| improvement, and debt consolidation. The completed | | | | and first and second mortgage amounts. With this |
| form-with the consumer's name, address, phone | | | | information in hand, the broker can evaluate the |
| number, and other data-is sold to a broker as a sales | | | | prospect and select the appropriate product before |
| lead. The company generating the lead "scrubs" the | | | | making the call. |
| data to prevent bogus information from reaching the | | | | The data appends solve another problem that has |
| broker. The lead generator accomplishes the | | | | vexed the internet lead industry: consumer |
| validation by "pinging" the data against various | | | | inaccuracy. A study by reveals that 34% of |
| databases. The process is automated, so it takes | | | | consumers do not even know what type of loan |
| only seconds to verify the accuracy of the lead. | | | | they have. Others know the type, but not details |
| Because the validation process is instantaneous and | | | | about interest rates or loan balances. As a result, the |
| the leads are immediately emailed to the broker, | | | | information they provide often turns out to be |
| internet-generated mortgage leads are often | | | | inaccurate. Long-form leads with appended data take |
| marketed as "real time" leads. | | | | the guesswork out of the process. They replace |
| For the past decade, the industry has made only | | | | erroneous consumer input with accurate data. This |
| incremental improvements in lead validation and | | | | eliminates time-consuming question-and-answer |
| delivery. A few years ago lead generation companies | | | | sessions on the phone, allowing the broker to make |
| introduced "live transfer" leads in which they call the | | | | more calls and close more deals. It also helps the |
| consumer, verify interest in the loan, then transfer | | | | broker proceed with confidence, knowing there will |
| the call to the broker. Recently, however, some lead | | | | be few if any surprises as they proceed with the |
| generation companies have changed internet | | | | loan. |
| mortgage leads in a way that can only be described | | | | Long-form mortgage leads won't solve the credit |
| as revolutionary. | | | | crisis, but they can help brokers work more |
| Taking advantage of newly formed strategic | | | | efficiently and profitably. |