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FORECLOSURE ACTIVITY IN FIRST HALF OF 2024 DOWN FROM PREVIOUS YEAR

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U.S. Foreclosure Starts Decrease 3.5 Percent in First Six Months of 2024; Average Days to Complete a Foreclosure Up Second Quarter in a Row; June and Q2 2024 Foreclosure Activity Post Annual Declines

IRVINE, Calif., July 11, 2024 /PRNewswire/ — ATTOM, a leading curator of land, property and real estate data, today released its Midyear 2024 U.S. Foreclosure Market Report, which shows there were a total of 177,431 U.S. properties with foreclosure filings — default notices, scheduled auctions or bank repossessions — in the first six months of 2024. That figure is down 4.4 percent from the same time period a year ago but up 7.8 percent from the same time period two years ago.

Historical First Half US Foreclosure Activity Chart

“In contrast to the first half of 2023, foreclosure activity across the United States experienced a decline in the first half of 2024,” stated Rob Barber, CEO for ATTOM. “In addition, U.S. foreclosure starts also decreased by 3 percent in the first six months of 2024. These shifts could suggest a potential stabilization in the housing market; however, monitoring these evolving patterns remains crucial to understanding the full impact on the real estate sector.”

States that saw the greatest increases in foreclosure activity compared to a year ago in the first half of 2024 included South Dakota (up 93 percent); North Dakota (up 86 percent); Kentucky (up 73 percent); Massachusetts (up 46 percent); and Idaho (up 30 percent).

New Jersey, Illinois, and Florida post highest state foreclosure rates
Nationwide, 0.13 percent of all housing units (one in every 794) had a foreclosure filing in the first half of 2024.

States with the highest foreclosure rates in the first half of 2024 were New Jersey (0.21 percent of housing units with a foreclosure filing); Illinois (0.21 percent); Florida (0.20 percent); Nevada (0.19 percent); and South Carolina (0.19 percent).

Other states with first-half foreclosure rates among the 10 highest nationwide were Maryland (0.19 percent); Connecticut (0.19 percent); Delaware (0.18 percent); Ohio (0.18 percent); and Indiana (0.16 percent).

Highest metro foreclosure rates in Lakeland, Columbia, and Atlantic City
Among the 224 metropolitan statistical areas with a population of at least 200,000, those with the highest foreclosure rates in the first half of 2024 were Lakeland, Florida (0.32 percent of housing units with foreclosure filings); Columbia, South Carolina (0.31 percent); Atlantic City, New Jersey (0.28 percent); Cleveland, Ohio (0.27 percent); and Spartanburg, South Carolina (0.27 percent).

Other major metro areas with foreclosure rates ranking among the top 10 highest in the first half of 2024 were Jacksonville, Florida (0.25 percent of housing units with a foreclosure filing); Bakersfield, California (0.25 percent); Elkhart, Indiana (0.24 percent); Orlando, Florida (0.24 percent); and Chicago, Illinois (0.24 percent).

Foreclosure starts down 3.5 percent from last year
A total of 130,369 U.S. properties started the foreclosure process in the first six months of 2024, down 3.5 percent from the first half of last year and down 32 percent from the first half of 2020.

States that saw the greatest number of foreclosures starts in the first half of 2024 included Texas (15,375 foreclosure starts); Florida (15,251 foreclosure starts); California (14,964 foreclosure starts); New York (7,523 foreclosure starts); and Illinois (7,240 foreclosure starts).

Bank repossessions decline in first half of 2024 from last year
Lenders foreclosed (REO) on a total of 18,726 U.S. properties in the first six months of 2024, down 17 percent from the first half of 2023 and down 10 percent from the first half of 2022, but up 92 percent from the first half of 2021.

States that posted the greatest number of REOs in the first half of 2024 included California (1,575 REOs); Pennsylvania (1,568 REOs); Illinois (1,540 REOs); Michigan (1,432 REOs); and Texas (1,197 REOs).

Q2 2024 foreclosure activity below pre-recession averages in 79 percent of major markets
There were a total of 89,466 U.S. properties with a foreclosure filings during the second quarter of 2024, down 6 percent from the previous quarter and down 8 percent from a year ago.

The national foreclosure activity total in Q2 2024 was 68 percent below the pre-recession average of 278,912 per quarter from Q1 2006 to Q3 2007.

Second quarter foreclosure activity was below pre-recession averages in 177 out 224 (79 percent) metropolitan statistical areas with a population of at least 200,000 and sufficient historical foreclosure data, including New York, Los Angeles, Chicago, Dallas, Houston, Miami, Atlanta, San Francisco, Riverside–San Bernardino, Phoenix, and Detroit.

Metro areas with second quarter foreclosure activity above pre-recession averages included Honolulu, HI; Richmond, VA; Baltimore, MD; Virginia-Beach, VA; Albany, New York; and Montgomery, AL.

Average time to foreclose increases for second quarter in a row
Properties foreclosed in Q2 2024 had been in the foreclosure process an average of 815 days. That figure was up 11 percent from the previous quarter and down 33 percent from Q2 2023.

Average Days to Complete Foreclosure

States with the longest average foreclosure timelines for homes foreclosed in Q2 2024 were Louisiana (3,686 days); Hawaii (2,597 days); New York (2,034 days); Georgia (1,929 days); and Nevada (1,852 days).

States with the shortest average foreclosure timelines for homes foreclosed in Q2 2024 were New Hampshire (82 days); Texas (147 days); Minnesota (151 days); Oregon (206 days); and Montana (212 days).

June 2024 Foreclosure Activity High-Level Takeaways

Nationwide in June 2024, one in every 5,071 properties had a foreclosure filing.States with the highest foreclosure rates in June 2024 were Illinois (one in every 3,041 housing units with a foreclosure filing); New Jersey (one in every 3,042 housing units); Florida (one in every 3,202 housing units); South Carolina (one in every 3,346 housing units); and Maryland (one in every 3,486 housing units).18,574 U.S. properties started the foreclosure process in June 2024, down 17 percent from the previous month and down 22.7 percent from June 2023.Lenders completed the foreclosure process on 2,891 U.S. properties in June 2024, up .4 percent from the previous month and down 10 percent from June 2023.

U.S. Foreclosure Market Data by State – Jan to Jun 2024

Rate
Rank

State Name

Total Properties w/
FC Filings

% Housing
Units

1/Every X
HU

%∆ from
Jan-June 23

%∆ from
Jan-June 22

U.S. Total

177,431

0.13

794

-4.39

7.81

19

Alabama

2,565

0.11

895

14.56

3.64

36

Alaska

207

0.07

1,534

-33.65

29.38

23

Arizona

3,052

0.10

1,015

-0.84

-4.83

26

Arkansas

1,130

0.08

1,214

-17.46

41.96

13

California

19,013

0.13

759

6.13

16.36

34

Colorado

1,784

0.07

1,401

-18.13

-23.17

7

Connecticut

2,860

0.19

535

17.36

44.52

8

Delaware

826

0.18

547

-17.73

-8.53

District of
Columbia

659

0.19

532

32.86

565.66

3

Florida

20,090

0.20

494

8.42

13.99

15

Georgia

5,289

0.12

837

-16.15

-7.71

33

Hawaii

408

0.07

1,375

-21.08

4.08

30

Idaho

596

0.08

1,273

29.57

96.05

2

Illinois

11,336

0.21

479

-16.76

-19.52

10

Indiana

4,778

0.16

614

-9.06

-0.91

18

Iowa

1,611

0.11

880

-13.39

2.55

47

Kansas

485

0.04

2,636

-19.57

6.83

27

Kentucky

1,644

0.08

1,216

72.51

100.49

20

Louisiana

2,224

0.11

935

1.23

18.74

28

Maine

600

0.08

1,236

8.11

-14.77

6

Maryland

4,762

0.19

532

-18.71

62.30

17

Massachusetts

3,411

0.11

879

45.64

74.56

16

Michigan

5,210

0.11

879

-26.50

-11.89

25

Minnesota

2,153

0.09

1,158

-7.56

1.27

39

Mississippi

811

0.06

1,634

-22.84

-14.18

38

Missouri

1,730

0.06

1,616

-19.08

-33.36

48

Montana

141

0.03

3,670

-30.54

-27.32

43

Nebraska

446

0.05

1,901

-30.64

-23.76

4

Nevada

2,495

0.19

516

3.87

10.45

35

New Hampshire

424

0.07

1,510

-6.19

5.74

1

New Jersey

8,076

0.21

465

-11.19

-12.00

29

New Mexico

741

0.08

1,273

-33.42

-3.52

12

New York

11,312

0.13

751

-7.23

47.43

24

North Carolina

4,530

0.10

1,046

-20.87

-7.87

45

North Dakota

192

0.05

1,939

86.41

131.33

9

Ohio

9,236

0.18

569

-12.42

-16.25

22

Oklahoma

1,734

0.10

1,010

-23.71

-18.21

41

Oregon

1,002

0.06

1,815

-22.80

53.68

14

Pennsylvania

7,141

0.12

806

0.92

29.11

44

Rhode Island

253

0.05

1,909

-29.92

-18.39

5

South Carolina

4,568

0.19

517

1.26

0.00

50

South Dakota

85

0.02

4,625

93.18

97.67

31

Tennessee

2,329

0.08

1,310

-7.62

17.39

11

Texas

15,610

0.13

747

12.55

35.42

21

Utah

1,214

0.10

958

16.17

18.79

49

Vermont

89

0.03

3,766

25.35

102.27

32

Virginia

2,747

0.08

1,320

-18.99

-7.97

42

Washington

1,761

0.05

1,826

13.54

32.01

46

West Virginia

353

0.04

2,434

-18.10

49.58

40

Wisconsin

1,543

0.06

1,772

-11.07

-14.99

37

Wyoming

175

0.06

1,562

-26.78

-10.26

Report methodology
The ATTOM U.S. Foreclosure Market Report provides a count of the total number of properties with at least one foreclosure filing entered into the ATTOM Data Warehouse during the month and quarter. Some foreclosure filings entered into the database during the quarter may have been recorded in the previous quarter. Data is collected from more than 3,000 counties nationwide, and those counties account for more than 99 percent of the U.S. population. ATTOM’s report incorporates documents filed in all three phases of foreclosure: Default — Notice of Default (NOD) and Lis Pendens (LIS); Auction — Notice of Trustee Sale and Notice of Foreclosure Sale (NTS and NFS); and Real Estate Owned, or REO properties (that have been foreclosed on and repurchased by a bank). For the annual, midyear and quarterly reports, if more than one type of foreclosure document is received for a property during the timeframe, only the most recent filing is counted in the report. The annual, midyear, quarterly and monthly reports all check if the same type of document was filed against a property previously. If so, and if that previous filing occurred within the estimated foreclosure timeframe for the state where the property is located, the report does not count the property in the current year, quarter or month.

About ATTOM
ATTOM provides premium property data to power products that improve transparency, innovation, efficiency, and disruption in a data-driven economy. ATTOM multi-sources property tax, deed, mortgage, foreclosure, environmental risk, natural hazard, and neighborhood data for more than 155 million U.S. residential and commercial properties covering 99 percent of the nation’s population. A rigorous data management process involving more than 20 steps validates, standardizes, and enhances the real estate data collected by ATTOM, assigning each property record with a persistent, unique ID — the ATTOM ID. The 30TB ATTOM Data Warehouse fuels innovation in many industries including mortgage, real estate, insurance, marketing, government and more through flexible data delivery solutions that include ATTOM Cloud, bulk file licenses, property data APIs, real estate market trends, property navigator and more. Also, introducing our newest innovative solution, making property data more readily accessible and optimized for AI applications– AI-Ready Solutions. 

Media Contact:
Megan Hunt
megan.hunt@attomdata.com 

Data and Report Licensing:
datareports@attomdata.com

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SOURCE ATTOM

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Beghou Expands Pune Office, Strengthening Data, Analytics, and AI Capabilities

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The expanded office brings together multidisciplinary teams to solve increasingly complex life sciences commercialization challenges 

PUNE, India, Nov. 11, 2026 /PRNewswire/ — Beghou, a life sciences commercialization consulting and technology company, today announced the expansion of its Pune office. Opened on October 7 to foster cross-team collaboration, the new space reflects Beghou’s growing global delivery and innovation model. The Pune office is home to consulting and product teams with expertise spanning analytics, data engineering, technology, and AI. Beghou has also expanded its offices in Hyderabad and Bengaluru this year as its workforce continues to scale. The larger Pune space makes room for that growth, along with expanded leadership opportunities, specialist capabilities, and global client exposure for teams based there. 

“There’s a real sense of momentum at Beghou right now, and it’s exciting to see that reflected in our global expansion. We’re growing across markets, expanding the capabilities we bring to clients, and investing in the people and technology behind that work,” said Adrienne Lovink, CEO, Beghou. 

Commercialization challenges rarely sit within a single discipline, and Beghou’s model is built around that reality. Teams work together to move from identifying a business question to designing, building, and implementing the solution. The new office gives them dedicated space to collaborate, share knowledge, and learn from one another. 

“It is incredibly fulfilling to see the growth of our India organization and the world-class talent and capabilities we have built over the years. I see this growth as a stepping stone to something much bigger – not just scaling, but driving innovation, developing differentiated offerings, and solving increasingly complex commercialization challenges for our clients. Our new office reflects this ambition, bringing together diverse expertise and creating more opportunities for our teams to collaborate, innovate, and build meaningful solutions,” said Sonam Dubey, India Head, Beghou. 

The office is also a key hub for Beghou’s AI and product innovation, with teams working to embed AI in the solutions clients use across planning, analysis, and execution. They are also helping to develop new products that pair Beghou’s commercialization expertise with modern data capabilities. 

“We are at an exciting point in Beghou’s journey. I see this office as a melting pot of deep commercial expertise, technology, product thinking, and AI, the capabilities that will shape our next phase of growth. The opportunity is to combine those strengths to build differentiated solutions that solve real client problems and scale our impact,” said Abhigya Jain, Partner, Beghou. 

About Beghou 

Beghou drives commercialization that works for life sciences. For over 30 years, Beghou has been a long-term consulting and technology partner to more than 250 life sciences clients. We connect the dots between strategy, data, technology, and teams, helping clients accelerate launches, deepen customer engagement, and advance patient access. Whether a company is pre-commercial and building from scratch or refining an existing commercial strategy, Beghou provides fresh ideas and pragmatic, technology-enabled solutions to help organizations adapt and thrive in an increasingly complex environment. 

We build enduring partnerships by remaining engaged and accountable beyond project delivery to help ensure solutions take hold and deliver results. Combining strategic thinking, technical expertise, and hands-on execution, we help clients achieve faster outcomes and lasting impact. 

Find out more at www.beghou.com.

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TIER IV unveils end-to-end autonomous driving adaptable to map information and sensor configurations

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Multiple open-source AI models are available with Autoware

TOKYO, Nov. 11, 2026 /PRNewswire/ — TIER IV, the pioneering force behind Autoware, open-source software for autonomous driving, today announced the development and open-source release of multiple end-to-end (E2E) autonomous driving AI models that support different system requirements, including map information and sensor configurations. The models offer flexible options ranging from camera-only configurations to those incorporating LiDAR, radar and high-definition (HD) maps, enabling developers to select AI models suited to their performance requirements. Through Autoware, TIER IV provides a development environment for optimizing these models and integrating them into vehicle systems, helping automakers and technology partners develop and deploy their own autonomous driving stack.

Overview of the Autoware 2.0 Architecture

TIER IV is leading the development of Autoware 2.0, the next-generation architecture of Autoware. Autoware 2.0 is a scalable and adaptable architecture that flexibly combines AI models with conventional rule-based technologies. By supporting different AI models and sensor configurations, it enables autonomous driving systems to be built for a range of applications and system requirements. The E2E autonomous driving AI models announced today are concrete technological outcomes designed to leverage this architecture.

NVIDIA Alpamayo 2 Edge

As part of its collaboration with NVIDIA announced in March 2026 , TIER IV has been evaluating the performance of NVIDIA Alpamayo, a vision-language-action (VLA) foundation model, and integrating it with Autoware. The latest model, Alpamayo 2 Edge, is an E2E autonomous driving AI model that takes only camera images as input and uses reasoning to generate driving trajectories. With 2 billion parameters, compared with 34 billion in Alpamayo 2 Super, it is substantially smaller and offers promise for practical deployment in vehicles. TIER IV is currently optimizing the model and adapting it to real vehicles, while having completed its integration with Autoware.

GitHub (source code): https://github.com/autowarefoundation/alpamayo-autowareHugging Face (AI model): https://huggingface.co/nvidia/Alpamayo2-Edge

AutoE2E

AutoE2E, whose development is led by the Autoware Foundation (AWF) and TIER IV, is an E2E autonomous driving AI model capable of running on computing platforms beyond NVIDIA hardware. It adopts a Fast–Slow architecture combining a Reactive Model for real-time driving decisions, a World Model for predicting future changes in the surrounding environment, and a Reasoning Model that supports driving decisions. It can accommodate configurations ranging from cameras alone to those incorporating LiDAR and radar sensor data. With 79.9 million parameters, it is lighter than Alpamayo 2 Edge. The Reactive Model has been released, while development of the World Model and Reasoning Model continues, alongside consideration of commercialization for robotaxi applications. Integration of the Reactive Model with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/auto_e2eHugging Face (AI model): https://huggingface.co/AutowareFoundation/auto_e2e

METEOR

Developed independently by TIER IV, METEOR is a lightweight, multitask E2E autonomous driving AI model primarily intended for privately owned passenger vehicles. Built on a convolutional neural network (CNN) architecture, it uses a bird’s-eye-view (BEV) representation to perform everything from perception of the surrounding environment to driving trajectory generation within a single neural network, without relying on high-definition maps. It supports configurations using images from one to eight cameras and can also incorporate LiDAR and radar sensor data. With 16 million parameters, it is even lighter than AutoE2E and supports operation across different semiconductor platforms, including NVIDIA and Renesas. TIER IV also uses CoMET, the automated labeling platform within Co-MLOps, together with agentic AI to automate data labeling and model training, evaluation, and improvement, eliminating the need for manual coding and labeling. Automakers and component suppliers can optimize the open-source model to meet their own vehicle specifications and performance requirements.

GitHub (source code): https://github.com/tier4/METEORHugging Face (AI model): https://huggingface.co/AutowareFoundation/meteor

OnePlanner

OnePlanner is an E2E autonomous driving AI model that integrates perception of the surrounding environment with motion planning. It currently uses BEVFusion, which generates a BEV representation from LiDAR point-cloud data, with a planned transition to PTv3. Its flexible architecture allows the perception model to be replaced while directly using features extracted during perception for motion planning. Conventional autonomous driving systems convert perception results into information such as object positions and velocities before passing them to the planner. OnePlanner reduces these intermediate conversions, enabling richer use of information about the surrounding environment. It also incorporates HD maps, route information, traffic-signal states, and vehicle motion states to generate driving trajectories for the next six seconds. Integration with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/autoware_oneplannerHugging Face (AI model): https://huggingface.co/AutowareFoundation/oneplanner

LatentDrive

LatentDrive is an E2E autonomous driving AI model that uses a world model to integrate predictions of the surrounding environment with motion planning. Using V-JEPA, a self-supervised learning approach, it represents features of the surrounding environment extracted from camera video in a latent space and uses these features to generate vehicle trajectories. Its distinguishing feature is that it directly leverages information from video for motion planning without intermediate processes such as object detection and tracking. It does not require HD maps and generates trajectories for the next four seconds using camera video, route information, and vehicle motion states. It supports configurations with either one or three cameras, and work is underway on integration with Autoware and validation in an in-vehicle environment.

GitHub (source code): https://github.com/autowarefoundation/autoware_latent_driveHugging Face (AI model): https://huggingface.co/AutowareFoundation/latent_drive

“Advances in E2E autonomous driving are fundamentally changing how autonomous driving systems are developed.” said Shinpei Kato, founder and CEO of TIER IV. “For automakers and component suppliers to incorporate AI technology into their own products, however, it is essential that they be able to internalize technologies according to their applications and performance requirements, without depending on a particular AI model or semiconductor platform. By releasing multiple AI models developed under the leadership of TIER IV and the Autoware Foundation, alongside the results of our collaboration with NVIDIA, we have significantly expanded those choices. We will continue to advance the open-source ecosystem centered on Autoware and work with partners around the world to democratize autonomous driving.”

“Advancing autonomous driving requires AI that can reason through complex situations and run efficiently in the car.” said Ali Kani, vice president of automotive at NVIDIA. “TIER IV’s integration of NVIDIA Alpamayo 2 Edge with Autoware gives developers an open foundation to bring that intelligence from research into their own vehicles.”

“The advancement of autonomous driving technology depends on an ecosystem in which diverse AI models can be developed and evaluated openly, then applied according to their respective use cases.” said Muhammad Zain Khawaja, President of the Autoware Foundation. “The AI models released today are an important demonstration of how Autoware is evolving into a flexible development platform that is not tied to any particular technology or hardware. We welcome TIER IV’s continued technology development and its collaboration with partners including NVIDIA. The Autoware Foundation will continue working with the global open-source community to make advanced autonomous driving technology accessible to everyone.”

Next Steps

TIER IV will continue improving the performance of the AI models released today and optimizing them for in-vehicle environments, while promoting the development and commercialization of E2E autonomous driving technology by automakers and partners through Autoware. TIER IV will also strengthen collaboration with the global open-source community and work to expand the adoption of autonomous driving systems across diverse vehicle types and applications.

About TIER IV

TIER IV stands at the forefront of deep tech innovation, pioneering Autoware, open-source software for autonomous driving. With a comprehensive suite of platforms and services built around Autoware, TIER IV provides everything from software development and vehicle procurement to operational support. Through the Autoware ecosystem, TIER IV works with partners worldwide to shape the future of intelligent vehicles with open-source software, aiming to create mobility that is safer, more sustainable, and accessible to all.

The word marks and logos of TIER IV are trademarks or registered trademarks of TIER IV, Inc. in Japan and other countries. All other company names, product names, service names, and logos referenced herein are trademarks or registered trademarks of their respective owners.

Autoware is a registered trademark of the Autoware Foundation.

Media contact
pr@tier4.jp 

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Dingdong to Report Third Quarter 2026 Financial Results on November 12, 2026

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SHANGHAI, Nov. 10, 2026 /PRNewswire/ — Dingdong (Cayman) Limited (“Dingdong” or the “Company”) (NYSE: DDL), a leading fresh grocery e-commerce company in China, with advanced supply chain capabilities, today announced that it will report its unaudited financial results for the third quarter ended September 30, 2026, before U.S. markets open on November 12, 2026.

About Dingdong (Cayman) Limited

Dingdong is the leading fresh grocery e-commerce company in mainland China, with sustainable long-term growth. The Company directly provides users and households with fresh groceries, prepared food, and other food products through delivering a convenient and excellent shopping experience supported by an extensive self-operated frontline fulfillment grid. Leveraging its deep insights into consumers’ evolving needs and its strong food innovation capabilities, Dingdong has successfully launched a series of private label products spanning a variety of food categories. Many of Dingdong’s private label products are produced at its own production plants, allowing it to more efficiently produce and offer safe and high-quality food products. Dingdong aims to be the first choice for fresh and food shopping.

For more information, please visit: https://ir.100.me.

 

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SOURCE Dingdong (Cayman) Limited

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