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Defect Risk Declines for the First Time in Eight Months, According to First American’s Loan Application Defect Index

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—The future of fraud and misrepresentation risk is tied closely to
mortgage rates, says Chief Economist Mark Fleming—

SANTA ANA, Calif.–(BUSINESS WIRE)–First
American Financial Corporation
(NYSE: FAF), a leading
global provider of title insurance, settlement services and risk
solutions for real estate transactions, today released the First
American Loan Application Defect Index
for April 2019, which
estimates the frequency of defects, fraudulence and misrepresentation in
the information submitted in mortgage loan applications. The Defect
Index reflects estimated mortgage loan defect rates over time, by
geography and loan type. It is available as an interactive
tool
that can be tailored to showcase trends by category, including
amortization type, lien position, loan purpose, property and transaction
types, and can provide state- and market-specific comparisons of
mortgage loan defect levels.

April 2019 Loan Application Defect Index

  • The frequency of defects, fraudulence and misrepresentation in the
    information submitted in mortgage loan applications decreased by 4.2
    percent compared with the previous month.
  • Compared to April 2018, the Defect Index increased by 11.0 percent.
  • The Defect Index is down 10.8 percent from the high point of risk in
    October 2013.
  • The Defect Index for refinance transactions decreased by 3.5 percent
    compared with previous month, and is up 16.9 percent compared with a
    year ago.
  • The Defect Index for purchase transactions decreased by 4.0 percent
    compared with the previous month, and is up 10.3 percent compared with
    a year ago.

Chief Economist Analysis: Lower Mortgage Rates Help Break Defect Risk
Trend

“The frequency of defects, fraudulence and misrepresentation in the
information submitted in mortgage loan applications declined 4.2 percent
compared to last month. Notably, this marks the first month-over-month
decline since July 2018, thanks to lower mortgage rates,” said Mark
Fleming, chief economist at First American. “Decreasing mortgage rates
contributed to an increase in inventory, reducing the competitive
pressure on the housing market, as well as contributing to an increase
in lower-risk refinance transactions. In line with this trend, the Loan
Application Defect Index
for purchase transactions declined for the
first time in eight months, falling 4.0 percent in April compared with
the previous month.

“The two competing trends that resulted in a flat fraud risk last month
were the increasing share of less risky refinance transactions working
to decrease overall fraud risk, and the continuation of the hot sellers’
market, motivating buyers to misrepresent information in order to
qualify for a bigger mortgage and increase overall fraud risk,” said
Fleming.

“The mix of refinance and purchase activity fluctuated within the month
of April. Refinance
activity increased
in the first half of the month as mortgage rates
declined. However, lower mortgage rates also fueled an increase in
purchase transactions, as buyers took advantage of their increased
house-buying power,” said Fleming. “In fact, purchase
applications hit their highest level in nine years
towards the end
of April. While loan application defects can happen on both purchase or
refinance transactions, there is a higher propensity for fraud and
misrepresentation with purchase transactions.

Increased Inventory Cools Misrepresentation Pressure

“However, the decline in mortgage rates had a third and even more
important consequence, which was to help alleviate some of the supply
constraints that made the housing market so competitive,” said Fleming.
“As we saw in last
month’s report
, in extremely competitive markets, there is more
motivation to misrepresent information on a loan application to qualify
for the bigger mortgage in order to win the bidding war.

“Most recently, real estate agents indicate that their buyers
are encouraged by an unexpected surge of supply
. April did see an increase
in total housing inventory
, rising to 1.83 million from 1.67 million
in March, which is a 1.7% increase year-over-year. Potential buyers feel
less inclined to misrepresent information on a loan application when
they don’t feel the pressure of a hot sellers’ market. Indeed,
misrepresentation of income and employment both fell this month, by 1.7
percent and 3.6 percent respectively,” said Fleming.

“The future of fraud and misrepresentation risk is tied closely to
mortgage rates. Increased inventory reduces competitive pressures and
misrepresentation risk, alongside the rising share of lower-risk
refinance transactions,” said Fleming. “It remains to be seen if
mortgage rates, now flirting with 4 percent, will go any lower. If so,
we may anticipate the continued downward trend in defect risk and
misrepresentation, with further increases in refinance transactions and
inventory, resulting in less pressure on the market.”

April 2019 State Highlights

  • The five states with a year-over-year increase in defect frequency
    are: New York (+37.3 percent), Nebraska (+37.0 percent), Iowa (+35.0
    percent), Hawaii (+33.7 percent), and West Virginia (+31.1 percent).
  • There are two states with the year-over-year decrease in defect
    frequency: Arkansas (-4.8 percent) and Florida (-1.1 percent).

April 2019 Local Market Highlights

  • Among the largest 50 Core Based Statistical Areas (CBSAs), the five
    markets with the greatest year-over-year increase in defect frequency
    are: Buffalo, N.Y. (+36.9 percent), Pittsburgh (+31.3 percent),
    Richmond, Va. (+30.1 percent), Cincinnati (+29.3 percent), and New
    York (+26.3 percent).
  • Among the largest 50 Core Based Statistical Areas (CBSAs), the five
    markets with year-over-year decrease in defect frequency are:
    Jacksonville, Fla. (-11.6 percent), Houston (-8.5 percent), Orlando,
    Fla. (-7.4 percent), San Diego (-4.3 percent), and Miami (-2.0
    percent).

Next Release

The next release of the First American Loan Application Defect Index
will take place the week of June 24, 2019.

Methodology

The methodology statement for the First American Loan Application Defect
Index is available at http://www.firstam.com/economics/defect-index.

Disclaimer

Opinions, estimates, forecasts and other views contained in this page
are those of First American’s chief economist, do not necessarily
represent the views of First American or its management, should not be
construed as indicating First American’s business prospects or expected
results, and are subject to change without notice. Although the First
American Economics team attempts to provide reliable, useful
information, it does not guarantee that the information is accurate,
current or suitable for any particular purpose. © 2019 by First
American. Information from this page may be used with proper attribution.

About First American

First American Financial Corporation (NYSE: FAF) is a leading
provider of title insurance, settlement services and risk solutions for
real estate transactions that traces its heritage back to 1889. First
American also provides title plant management services; title and other
real property records and images; valuation products and services; home
warranty products; property and casualty insurance; banking, trust and
wealth management services; and other related products and services.
With total revenue of $5.7 billion in 2018, the company offers its
products and services directly and through its agents throughout the
United States and abroad. In 2019, First American was named to the Fortune 100
Best Companies to Work For® list for the fourth consecutive
year. More information about the company can be found at www.firstam.com.

Contacts

Marcus Ginnaty
Corporate Communications
First American
Financial Corporation
(714) 250-3298

Cannabis

Strainprint™ Technologies Welcomes Organic Medical Cannabis Producer to Growing List of Subscribers

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Strainprint™ Technologies Ltd, the leader in cannabis data and analytics is pleased to expand their nation-wide coverage with the addition of Stewart Farms.

Stewart Farms is a late-stage applicant headquartered in Alberta that is building a 100,000 sq. ft. vertical aquaponics farm in Saint StephensNew Brunswick. They will be utilizing automation, vertical farming, and land-based aquaculture to produce medical grade organic cannabis for both recreational and medical markets in Canada. All of their products will be free of herbicides, pesticides and synthetic nutrients. At full capacity, they will reach more than 10,000 kgs per year of organically farmed cannabis and more than 200,000 kgs of organic tilapia.

Stewart Farms’ long term vision is to deliver tools and products to support  future customers and patients during their health and wellness journeys. “Through our partnership with Strainprint we gain direct access to their incomparable data and analytics tools. This will aid us in educating a wider audience on the medical benefits and best practices of cannabis-based medicine,” said Tanner Stewart, Co-founder & CEO of Stewart Farms. “We know our customers are looking to consume more than dried cannabis. We know Canadians of all legal ages are trying to sort through their personal engagement with cannabis as a medicine. What we want to know, on an ongoing basis, is what is and is not working for people. Strainprint’s patient-led data services will give us the insight needed to create custom products and further understand the benefits of our existing products. Finally, our goal is to partner with companies and teams that truly have people’s best interest at heart. Caring about a patient’s success is what makes up the core of the Strainprint team. We couldn’t be happier to move forward with them at our side.”

Stewart Farms will access the Strainprint Analytics web platform, the most sophisticated cannabis analytics platform available to improve product development. Strainprint Analytics is built on top of the largest and most granular scientific data set of its kind in the world, with more than 1.3 million anonymized, patient reported medical cannabis outcomes and more than 65 million data points on strain efficacy.

“We’re thrilled to provide our real-time, crowd sourced data to an environmentally conscious company that uses innovative, cutting edge farming technology to produce top-tier medical cannabis,” said Strainprint CEO, Andrew Muroff. “Our organizations are equally committed to improving lives using cannabis therapy, and our shared core motivation is to provide guidance and support to help cannabis patients achieve their health goals.”

 

SOURCE Strainprint Technologies Ltd.

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Field Trip Ventures Inc. Retains KCSA Strategic Communications as Public Relations Counsel

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Greenery Map, the world’s first and only cannabis search engine to allow users to search for cannabis products based on their desired mood, medicinal use, and method of consumption, is now offering users – both businesses and consumers – the opportunity to register and connect to the app in an entirely mobile way. Previously, businesses were required to access GreeneryMap.com from a desktop in order to manage accounts and connect to the inventory API system, but that road block has been removed, allowing for an entirely mobile experience through the Greenery Map app.

App users turn to Greenery Map to help them decide on the strain of Cannabis and product that is right for them depending on their desired mood or medicinal effect. Following the matching, consumers are given a detailed history and description of the strain so that they can make educated purchases, cutting down on time that budtenders need to spend with patrons and speeding up the purchase process. Consumers can then see all of the ways to purchase said product, including the nearby dispensaries that have it in stock, online options, and even delivery options through the app. Greenery Map fully integrates with a dispensary’s inventory API system to update in real-time and give consumers real-time information on dispensary stock for the item they are looking for. The Greenery Map system also provides cannabis businesses in both the B2B and B2C sectors a private database to share and sell information and products. For Cannabis businesses, Greenery Map also offers the opportunity to open bank and merchant accounts through their partnership with PayHouse Consulting Group.

 

SOURCE Greenery Map

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WeBank, IBM and Other Organizations Jointly Held the 1st International Workshop on Federated Machine Learning in conjunction with IJCAI 2019

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Once a concept, AI is now ushering in a key stage of application. What’s the solution to the data silos among businesses? Given the enhanced regulation on data at home and abroad, what’s the solution to data privacy and security concerns? What’s the status quo of Federated Machine Learning and how to establish an ecosystem for FML in the future?

WeBank, IBM and other organizations jointly held the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19) in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) on Aug. 12, 2019, to further discussion on these issues.

President of IJCAI, Chair of FML Steering Committee, Chief AI Officer of WeBank Professor Qiang Yang delivered opening remarks at the workshop. Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google presented keynote addresses. In the panel discussion, top scholars from WeBank, Bar-Ilan University, IBM, Squirrel AI, Google, Huawei, Clustar, Sinovation Ventures and many other renowned enterprises and universities shared and discussed their findings and experience in FML as an emerging AI technology.

This workshop received 40 papers, of which 12 were presented during the workshop, 19 presented via poster. Awards include Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award, Best Presentation Award. Selected high quality papers will be invited for publication in a special issue in the IEEE Intelligent Systems journal. All these attracted numerous scholars to engage in discussions and join efforts for building the FML ecosystem.

Experts from IBM and Google Share Groundbreaking Findings with a Focus on the Theory and Application of FML

Privacy and security are becoming a key concern in our digital age. On 25th May last year, the implementation of General Data Protection Regulation (GDPR) by the EU, the toughest Act on data privacy protection, stressed that user data collection must be open and transparent. A series of laws and regulations from China and overseas also pose new challenges to the traditional way of handling data and model for cooperation. Seeking ways for AI to adapt to this new reality became top priority, a demand that led to this workshop on FML.

A wealth of solutions and breakthroughs were shared by Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google in their speech on FML.

Besides how FML can help tackle challenges in the business world, Dr. Shahrokh Daijavad also shared the concept of Fusion AI, which means to train models on widely distributed data sets, but fuse them to produce one equivalent to what centralized training would yield. “Unlike traditional machine learning, in Fusion AI, model parameters are shared and data is not transferred, which makes Fusion AI model better than models that moving data centrally.” Given the widely distributed data, the development of Fusion AI and FML became ever important and imminent.

“FML enables machine learning engineers and data scientists to work productively with decentralized data with privacy by default,” said Dr. Jakub Konečný from Google. He also shared with us how FML works and its use cases at Google. In the case of Gboard, as on-device data is privacy sensitive or large or is more relevant than server-side proxy data, and labels can be inferred naturally via user interaction, the application of Federated RNN compared to prior n-gram model can increase the accuracy of next-word prediction by 24%, and the click rate of prediction strip by 10%.

Major Figure Panelists Discuss the Way Ahead for FML

The moderator of the panel discussion, AI Principal Scientist of WeBank Dr. Lixin Fan joined panelists including Professor Benny Pinkas from Bar-Ilan University, Dr. Shahrokh Daijavad of IBM Academy of Technology, Chief Architect of Squirrel AI Dr. Richard Tong, Research Scientist of Google Dr. Jakub Konečný, Dr. Baofeng Zhang from CTO Office of CBG Software in Huawei, Executive VP of Clustar Dr. Junxue Zhang, VP of AI Institute in Sinovation Ventures Dr. Ji Feng and other experts in a host of in-depth exchanges with attendees, to shed light on the way ahead for FML.

Experts shared thoughts in the panel discussion on questions including but not limited to: How to meet the security and compliance requirements? Is there a way to extend the value of data while observing user privacy and data security? Given the classic trade-off between data regulation and development of AI, how to achieve the long-term goal of establishing a stable and win-win business ecosystem?

List of Award-Winners

Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award and Best Presentation Award selected by all attendees were announced at the closing of the workshop.

Best Theory Paper Award: 
Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning? By Huadi Zheng, Haibo Hu & Ziyang Han;

Best Application Paper Award: 
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. By Yiqiang ChenJindong WangChaohui YuWen Gao & Xin Qin;

Best Student Paper Award: 
Quantifying the Performance of Federated Transfer Learning. By Qinghe JingWeiyan Wang, Junxue Zhang, Han Tian & Kai Chen;

Best Presentation Award: 
Federated Generative Privacy. By Aleksei Triastcyn and Boi Faltings.

President of IJCAI, Chief AI Officer of WeBank Professor Qiang Yang, Chief Architect of Squirrel AI Dr. Richard TongandVP of AI Institute in Sinovation Ventures Dr. Ji Feng presented the awards.

“The mission of this International Federated Machine Learning Workshop is to facilitate further understanding in the academia, business community as well as legal and regulatory institutions by promoting the establishment of FML ecosystem in the hope that more businesses will join and build a platform for students aspired to work in FML to find research teams that suit them,” said Professor Qiang Yang.

Held Aug. 10-16, 2019 in Macao, China, IJCAI-19 is one of the leading International Academic Conference on AI, attracting over 3000 AI research personnel and experts. The 1st International Workshop on Federated Machine Learning (FML’19) was a highlight for experts joining this event. Visionaries in the academia and industrial sector expressed the willingness to be part of the effort for academic research, application of FML in the future, and the development and boom of AI ecosystem.

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