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