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Top-100 Lender Unveils Tech for Top Teams

Homeside, a national mortgage lender,  has launched Rev, a platform designed to deliver an entrepreneurial branch model experience built specifically for top-ranking lending teams. According to the company, the objective of the technology is to increase sales and revenue, complete originations faster—and create more opportunity for the teams. Rev was designed to deliver a tool for high-producing lending teams to increase business.

Homeside says it offers more territory, selected because they are strategic, high-volume locations, with no market overcrowding. There is more independence, streamlined corporate involvement,  as well as provide more support for marketing, IT, human resources, payroll, licensing, compliance, legal and auditing. Also, branches have full control of profit and losses, and teams pay only for services used).

Homeside combines technology with a human touch to disrupt the mortgage industry. Since opening in late 2013, Homeside has grown to over 400 employees, with more than 20 locations and is recognized as a top-100 mortgage lender in the U.S.

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Homeowners Have Their Ages in Common

Homeowners have their ages in common.

In the largest metropolitan statistical areas , the average age of a homeowner is 54, according to a survey from Lending Tree that relied on Census Bureau Data to complete the rankings.

"It's no secret that young and old people gravitate toward different parts of the country," said Tendayi Kapfidze, chief economist at LendingTree. "Florida is a well-known haven for retirees, while places such as San Francisco and Austin, Texas, have emerged as millennial boomtowns over the past few years. As a result, the average age of a homeowner varies by location."

Homeowners in Florida are older than homeowners in most other states. Seven out of the top-10 metropolitan areas with the highest average homeowner age were in Florida. Homeowners in cities in Utah are among the youngest in the country.

Out of the top-10 metropolitan areas with the lowest average age for homeowners, metropolitan areas in Utah—Provo, Ogden and Salt Lake City—held the top three spots.

Metropolitan areas in America with the highest average homeowner age

North Port, Fla.
Average homeowner age: 63.3

Cape Coral, Fla.
Average homeowner age: 61.5

Deltona, Fla.
Average homeowner age: 60.2

Metropolitan areas in America with the lowest average homeowner age

Provo
Average homeowner age: 47.3

Ogden
Average homeowner age: 49.4

Salt Lake City
Average homeowner age: 50.1

Top 100 Metro Areas Ranked by Average Homeowner Age
Rank Metro Average age,
occupied
housing units
Average age,
renter-occupied
housing units
Average age,
owner-occupied
housing units
Average age
by MSA
1 North Port, Fla. 59 48.2 63.3 47.6
2 Cape Coral, Fla. 56.5 45.4 61.5 45.2
3 Deltona, Fla. 55.8 45 60.2 44.7
4 Palm Bay, Fla. 55.3 44.7 59.5 44.3
5 Lakeland, Fla. 53.5 42.8 58.5 40.6
6 Honolulu 50.8 41.8 58.1 39.2
7 Tampa, Fla. 52 42.2 57.6 41.5
8 Miami 52 44 57.4 40.6
9 Tucson, Ariz. 50.3 40.1 56.7 39.7
10 Scranton, Pa. 53.1 45.9 56.4 41.9
11 Oxnard, Calif. 51.5 43.4 56.2 38.1
12 Cleveland 51.4 43.3 55.8 40.6
13 Los Angeles 48.8 42.4 55.7 37.4
14 Springfield, Mass. 51.2 43.5 55.7 39.2
15 Dayton, Ohio 50.3 41.2 55.7 39.9
16 New York 50.4 44.8 55.7 38.9
17 New Haven, Conn. 51.2 43.9 55.6 40
18 Pittsburgh 52.1 44.1 55.6 42
19 San Francisco 49.3 41.9 55.6 39.4
20 Buffalo, N.Y. 51.3 43 55.5 40.7
21 Bridgeport, Conn. 51.7 44 55.4 39.2
22 San Diego 47.9 39.5 55.4 37.4
23 Knoxville, Tenn. 50.7 40.4 55.4 40.4
24 Winston, N.C. 50.7 41.5 55.2 39.7
25 Allentown, Pa. 52 44.6 55.1 40.6
26 Providence, R.I. 50.9 44.6 55.1 40.2
27 Akron, Ohio 50.3 41.1 55 40.1
28 Greensboro, N.C. 49.6 40.7 54.9 38.9
29 Chattanooga, Tenn. 50.7 42 54.9 40
30 Albany, N.Y. 50.4 42.3 54.9 40
31 Syracuse, N.Y. 50.8 42.6 54.8 39.5
32 Hartford, Conn. 51.2 44.1 54.8 40.2
33 Spokane, Wash. 49.5 40.3 54.7 39.3
34 Sacramento, Calif. 49.1 41.1 54.7 38.2
35 New Orleans 49.1 40.3 54.7 38.6
36 Rochester, N.Y. 50.7 42.7 54.6 40
37 Jacksonville, Fla. 49.2 39.5 54.6 38.7
38 Orlando, Fla. 48.3 38.9 54.6 38.1
39 Augusta, Ga. 49.6 39.7 54.5 38.3
40 Harrisburg, Pa. 50.7 42.6 54.5 40.2
41 Toledo, Ohio 48.8 39.2 54.5 38.6
42 Boston 49.9 42.7 54.4 39.3
43 Greenville, S.C. 49.7 40.1 54.3 38.9
44 Phoenix 48.6 39.5 54.3 37.6
45 Detroit 50.9 43.4 54.3 39.5
46 Philadelphia 50.5 42.6 54.3 39.1
47 San Jose, Calif. 48.2 40.2 54.3 37.6
48 Richmond, Va. 49.4 40.5 54.2 38.8
49 Virginia Beach, Va. 48 38.5 54.1 37.6
50 Albuquerque, N.M. 49.3 39.8 54.1 38.5
51 Fresno, Calif. 47.5 40.3 54.1 34.6
52 Memphis, Tenn. 48.2 39.3 54 36.9
53 Birmingham, Ala. 49.7 40.2 54 38.8
54 Worcester, Mass. 50.7 44.4 53.9 39.5
55 Riverside, Calif. 49.1 41.3 53.9 35.8
56 Jackson, Miss. 48.9 39 53.8 37.2
57 Baltimore 49.8 42.1 53.8 38.9
58 Durham, N.C. 47.3 37.8 53.8 38
59 Louisville, Ky. 49.5 41.1 53.8 39.1
60 St. Louis 49.9 41.3 53.7 39.3
61 Milwaukee 48.8 41.5 53.6 38.4
62 Stockton, Calif. 48.4 41.8 53.6 35.7
63 Columbia, S.C. 48.2 37.4 53.5 37.7
64 Las Vegas 47.9 41.7 53.5 37.7
65 San Antonio 47.8 38.6 53.5 36.3
66 Chicago 48.9 40.6 53.5 37.7
67 Tulsa, Okla. 48.6 39.7 53.4 37.9
68 Portland, Ore. 48.4 40.7 53.4 38.4
69 Little Rock, Ark. 48.1 38.7 53.3 37.8
70 Charleston, S.C. 47.8 37.8 53.2 38
71 Cincinnati 48.9 40.6 53.2 38.3
72 Wichita, Kan. 48.4 40 52.9 37.3
73 El Paso, Texas 47.5 39 52.8 34.7
74 Seattle 47.1 39.1 52.6 38
75 Kansas City, Mo. 48.2 40.4 52.4 37.9
76 Washington 47.7 39.7 52.4 37.3
77 Charlotte, N.C. 47.9 39.4 52.4 37.4
78 Colorado Springs, Colo. 46.4 36.3 52.3 36.4
79 Madison, Wis. 46 36.1 52.3 37.8
80 Boise City, Idaho 48 39 52.2 36.9
81 Oklahoma City 47.1 38.1 52.2 36.8
82 Baton Rouge, La. 47.4 37.2 52.2 36.9
83 Columbus, Ohio 46.8 38.5 52.1 37
84 Bakersfield, Calif. 46.7 39.4 52.1 33.9
85 Grand Rapids, Mich. 48.4 39 52.1 37.3
86 Indianapolis 47.5 39.3 52 37.2
87 Nashville, Tenn. 47.2 38.2 52 37.3
88 Atlanta 47.1 38.9 51.9 36.4
89 Dallas 46 37.7 51.6 35.6
90 Denver 46.6 38.2 51.5 37.3
91 Houston 46 37.9 51.3 35.1
92 McAllen, Texas 47.4 38.9 51.3 32.3
93 Minneapolis 47.9 40.2 51.2 37.6
94 Omaha, Neb. 47 39.1 51.2 36.8
95 Raleigh, N.C. 46.4 38.7 50.6 36.4
96 Austin, Texas 44 34.9 50.6 35.4
97 Des Moines, Iowa 46.7 38.5 50.4 36.8
98 Salt Lake City 45.6 36.6 50.1 34.1
99 Ogden, Utah 46.3 37.2 49.4 33.5
100 Provo, Utah 41.9 30.6 47.3 29.2

 

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MBA: New Home Purchase Apps Drop

New home purchases decreased 2.1 percent from a year ago, according to the Mortgage Bankers Association Application Survey for October. The performance in September increased 11 percent compared with September 2018. This change does not include any adjustment for typical seasonal patterns.

“While we have seen some monthly swings in new home sales in 2018, the year-to-date average sales pace is around seven percent higher than the same period in 2017,” said Joel Kan, associate vice president of economic and industry forecasting for the MBA. “Additionally, the average loan size for a new home purchase application, at around $332,000, was at its lowest since July 2017. This is potentially a sign that there has been some additional inventory in the new home market, and that the rapid price growth in some geographies is starting to ease.”

MBA estimates new single-family home sales were running at a seasonally adjusted annual rate of 673,000 units in October 2018, based on data from the survey. The new home sales estimate is derived using mortgage application information from the survey, as well as assumptions regarding market coverage and other factors.

The seasonally adjusted estimate for October is an increase of 4.7 percent from the September pace of 643,000 units. On an unadjusted basis, the MBA estimates that there were 53,000 new home sales in October 2018, an increase of 6 percent from 50,000 new home sales in September.

By product type, conventional loans composed 70.9 percent of loan applications, FHA loans composed 17.1 percent, RHS/USDA loans composed 0.7 percent and VA loans composed 11.2 percent. The average loan size of new homes decreased from $333,086 in September to $331,732 in October.

MBA’s Builder Application Survey tracks application volume from mortgage subsidiaries of home builders across the country. Utilizing this data, as well as data from other sources, MBA is able to provide an early estimate of new home sales volumes at the national, state, and metro level.

 

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