Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Technology in Land Records
     An Interactive Session Looking at

 Yesterday, Today, Tomorrow

   2014 NACRC Annual Conference
          Long Beach, CA
         August 24, 2014
Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Session Description

    We will take a retrospective look at some of the history
    and milestones in land records technology including two
    current aspects: Auto Indexing and Redaction and how
    they have changed how a document is recorded. The
    final area of discussion will focus on how technology
    advancements like voice recognition, touch screen
    displays and virtual assistants will spark your
    imagination on how these adaptive technologies could
    change the way we do business in the future.

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Session Overview

   History of recording “technologies”
   Technologies being used today
   Technology in the future
   Wrap up

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
History – How We Got Here

 Books – handwritten  typed
 Computer indices
 Microfilm
 Imaging
 Integrated systems; receipting,
  imaging and database
 New technologies
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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Books

 1800’s … and before

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Computer indices

 1970’s

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Microfilm Records …

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
… are facing some tough times

       Redox                 Vinegar Syndrome
 Not just a technology problem, but a storage problem

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Technology in Land Records - Yesterday, Today, Tomorrow 2014 NACRC Annual Conference
Imaging

 1990’s
     Digital Scanning: Digital scanners available
      beginning 1985 (bi-tonal, flatbed, 300 dpi).
      Color & 600 dpi by mid 1990s. Prices drop.
      Today - many choices, features & price points

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20 Years of Transformative Technology

  Artificial
Intelligence       Maricopa Co                                 SIRI First
Technologies                              iPHONE
  Emerge/         eFiled first doc                            Intelligent          Autonomous
                                       Enabled Touch
   Expert                                                      assistant               Cars
  Systems

  1994     1998      1999       2002      2007         2010     2011        2013      2014      ?

                                                  Maricopa            Clark County           What’s
                                                   County            Marriage Kiosk          Next ?
                                                  Recording           Mobile Apps
                                                    Kisok

          In the continuing era of “Do More with Less”. What
          technologies will help your offices run more efficiently and
          cost effectively ?
Today’s Technologies
   eRecording
   Auto indexing
   Redaction
   Touch screen applications
   Remote kiosks/Intelligent assistants
   Full text search
   Fraud alert
   Trustworthy systems
   Cloud
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Today’s Technologies

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Auto Indexing Technologies
 First site – 2002 Arapahoe Co, CO
             Indexed 1.4 million documents since 2002
             175 Customers nationwide
 Goal of auto-indexing the reduction of key-
  strokes increases productivity
 High volume easily indexed documents, frees
  up user time to focus on more cognitively
  demanding documents.
 Has the evolution of OCR/ICR engines helped
  auto-indexing?
 Key as you see it?
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Auto Indexing Technologies that Learn
 Find the data in the document
 Extract each letter or number of data
 Organize the data how the human
  enters it. Abbreviations, hypen names

 Redaction you just need to find the Data
  and cover-up.

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Auto Indexing Technologies that Learn
 Expert systems contain a knowledge base expressed in
  IF/THEN rules and has an engine capable of drawing
  inferences from this knowledge base. These kb are
  developed by comparing result against known data.
 Most expert systems/cognitive systems express
  conclusions with a confidence factor, ranging from
  speculation to educated guess to a firm conclusion
 Machine learning and reasoning technologies than
  compare results against human provided feedback. How
  right was the learning engine.

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Today’s Technologies
Redaction
 Balancing public's right to information
  with the individual's right to privacy
 Bearing in mind the daily environment
  of potential identity theft, information
  security is of paramount concern.

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Today’s Technologies
Redaction
 PRIA’s Redaction White Paper
           PRIA’s RAPP committee collaborated to create Best
            Practices for Redaction:

 Best Practice #1
           First and foremost: custodians of land records should follow
            their specific state statutes regarding their duties to redact
            and/or provide access to the records.

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Today’s Technologies
Redaction
 Best Practice #2
           Legislators should consult their county custodians of public
            records, as well as PRIA and other like organizations such
            as NACRC, IACREOT and ALTA. These organizations and
            individuals provide a broader view of the purpose of public
            records and should be consulted during development of
            legislation

 Best Practice #3
           PRIA recommends the use of automated redaction software
            for covering up data from digital images

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Today’s Technologies
Redaction
 Best Practice #4
           PRIA recommends allowing full open access to the redacted
            version of a document, while maintaining the un-redacted
            copy as the master/legal document

 Best Practice 5
           Avoid marking on documents in such a way that it inhibits
            the OCR of that document

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Today’s Technologies
Redaction
 Best Practice #6
           When OCR is a part of the redaction process, scanning
            images at 300 DPI TIFF Group 4 is the desired format for
            best character recognition accuracy

 Best Practice #7
           Creating a methodology to test redaction accuracy results
            that meets your “Best Efforts” requirement should be
            documented. Having an accuracy methodology in place
            documents that your counties redaction efforts meet
            industry standards for “Best Efforts” practices

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Today’s Technologies
Redaction
 Best Practice #8
           Signatures should not be redacted from land records

            Cautionary Note: The redaction of property addresses will
            have unforeseen challenges when securing financing and
            acquiring title insurance to purchase property. Title
            companies cannot guarantee title if they cannot confirm
            ownership and chain of title for the property

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Today’s Technologies
Redaction
 Best Practice #9
           Only allow access to the redacted version of a document

 Best Practice #10
           Accuracy benchmarks be conducted prior to purchasing an
            automated technology solution, and applied throughout
            your use of the system to guarantee your redaction
            processes are producing expected results

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Automated Redaction
              Workflow Diagram with Human QA

             Image                                 Only 10%-20% of the
                                                documents required manual
            collection
                                                   review and redaction

                              Redaction
                             Verification
                                                          Redacted
 Images                                                   Document         Data

processed
   for
redaction                                                             Export Redacted
                                       Copies of Images with
                                        no redactions don’t           Images back to
                                       need to be saved the          Recording system
               80%-90% of images
                                          original is used           Image Repository
                have no redactions
Today’s Technologies
Touch Screen
 Recording Software
 Kiosks

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Today’s Technologies
Remote Kiosks

     Marriage Certificate Kiosk & Mobile App, Clark County, NV
        https://www.youtube.com/watch?v=-iWs9bnyP9Y

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Today’s Technologies

Remote Kiosks
 Helen Purcell, Maricopa County, AZ
           Real and virtual assistance
           Touch Screen
           Scan
           Credit Card processing
           MOU
           Printed cover page – original recorded doc

http://recorder.maricopa.gov/web/kioskvideo.aspx

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Today’s Technologies
Full Text Search
           Utilizes Google like search engines
           Returns search results faster
           Full document search versus field metadata
           Facilitates searching for potential fraud
            suspects

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Today’s Technologies
Cloud
 Physical storage spans multiple servers (and often
  locations).Typically managed by a hosting company.

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Today’s Technologies
 Fraud alert
     Add on option to recording software or service
       http://cookrecorder.com/
     Typical process: Register online or call; notified if
       your name appears as tor/tee on various doc types
    OR
     Enable constituent to search themselves for no fee
       http://ocrecorder.com/services/documents/fraud

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Today’s Technologies
 Trustworthy systems
           CA Government Code Sec 12168.7 (uniform statewide
            standards)
             2 CCR Sections 22620.1-22620.8 (8/12/12)
           Objectives:
             Protect against fraudulent changes, accidental deletion
                or loss, ensure long term accessibility and preservation,
                avoid proprietary formats
           Combination of implementing technologies along with
            internal compliance practices
             Utilizing algorithm/hash technology
             Verify image capture quality and data accuracy
           PDF/A (preferred) versus TIFF

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What Can We Expect in the Future?

 Balance/respect for the past
 Completely digital processes
   “e-everything”
 Intelligent assistants that learn

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What Can We Expect in the Future?

 Embrace new and respect the past
    Responsibility to preserve and protect
     history
    Responsibility to review processes and
     streamline as needed
    People entering the workforce likely have a
     different perspective

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What Can We Expect in the Future?

 Millenials Coming into Workforce
       Approximately 95 million – 30% of the population
        (Business Insider/Andy Kiersz, data from U.S. Census
        Bureau)
       Higher proportion of 18-24 year-olds in college now than
        any time in the past (Business Insider/Andy Kiersz, data
        from National Center for Education Statistics)
       More tech-savvy than older generations and were brought
        up with innovative technology (Pew Research Center)
       More likely than other generations to use emerging social
        media technologies to communicate and search about a
        service, product or brand (Prosper Insights & Analytics for
        the Media Behavior and Influence Study)

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What Can We Expect in the Future?

 100% e-Recording?
       CCCA discussing the possibility of 100% submission
        initiative

 e-Everything?
       CFPB eClosing pilot program
         List of vendor and creditor participants released
           8/21/14
         PRIA session scheduled for 8/27

 Communication via Social Media
       FB, Twitter, LinkedIn – what’s next?

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Millennials will expect adaptive technologies

 Intelligent Assistants that learn utilizing
  predictive intelligence: Siri, Cortana, Nina
   Phone manufacturers have commercialized
     this technolog.y
   They are “Do Engines” utilizing “Search
     Engines”.
   Virtual assistants with voice-controlled
     natural language interface that uses
     sequential inference and contextual
     awareness to help perform personal tasks.

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Wrap Up
 Embrace ever-evolving change, but respect and protect
  history
 Change comes with challenges, hurdles, and
  opportunities and rewards
 Questions?

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Your Presenters

 Larry Burtness
     Washoe County Recorder
             Lburtness@washoecounty.us
 Ann Kirkbride
     Mentis Technology Solutions
             AnnKirkbride@mentistechnology.com
 Kathy Taylor
     hal Systems Inc.
             Ktaylor@halfile.com

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Thank you for attending !!

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