https://www.scientificamerican.com/article/what-is-the-memory-capacity/

Big Data? FNMA; FFIEC, TAF, AARO and State Regulators y’all don’t have a clue what really “Big Data” is. Every single appraiser in the country is walking around with far more Big Data storage than any software designer ever imagined. It’s application is no less scientific than any arbitrarily ‘scrubbed’ data.

It really would make a good article. Interesting aside. USPAP requires that we support our adjustments and conclusions. Some purveyors of magical ePixie dust & Big Data solutions suggest that we can / should now be able to prove our adjustments and conclusions. All via the God of Science.

Few remember that the human brain is and always has been the best computer ever created. It has a life long accumulation of data that it reconciles on a daily basis, with or without our direction. It’s a bad & arbitrary mistake for our regulators to dismiss it (life & professional experience) out of hand for “science” that has also been arbitrarily tweaked and massaged.

Thank you Mike.

That might make a good article, thinking about it. Everyone is tossing around big tech language lately, but often I wonder if they really actually understand what they’re talking about. They’re good at arguing about it but do they actually understand the details of the subject matter. Individual casino dealers are subject to more oversight than these tech nerds, and they’re only half as dangerous.

Letter submitted today. Something about consumer protection, something something.

Thank you.

Now copy and paste that educational post into your letter to the Feds on deminimis Baggs!

You just explained why snake oil is snake oil. All most of the rest of us know is that snake oil isn’t good.

Exactly. There is no way they can better replace market experience with big data. Unfortunately it’s a race to the top who will be the one stop shop for lenders. Yes they better have a great insurance plan.

They’re probably going to need a brand new special insurance and regulatory structure for that. Ha! The results of new and influential business structures in our modern government is predictable, inevitable regulation. It would just be easier to skip all that and continue to use traditional full service non integrated appraisal services. They’ve invested ten hundred million man hours and one hundred quadrillion trillion computational hours to trying to accomplish what we do in our sleep. lol!

I still can’t find a cell phone I like. I’m holding on to this 7 pro like my life depends on it. This analog call blocker has a 10,000 number capacity. When I’m away from the desk I am not consumed by tech. Life is good.

Baggins,

Your more tech. than most as you looked it up on WIKI.

Too bad wiki didn’t have an appraisal dictionary which says the same thing (Good Comp v Bad comp).

The AVA’s will suffer their reputation and demise naturally. When Appraisers use both anecdotal comparison and statistics our credibility will improve, as well as our necessity

whenever we fit the data, we should expect 2 types of errors 1) reducible errors 2) irreducible errors

reducible errors: this is encountered due to either “squared bias” or “squared variance”. (refer to bias variance trade-offs for supervised learning for more details)

irreducible errors: it is an error that we cannot reduce by choosing a better model. it is due to randomness or natural variability in a system.

https://en.wikipedia.org/wiki/Theory_of_computation

I might have confused reducible and irreducible in the post language. Oh well, I’m not a tech guy, but I’m sure you’ll understand. Cheers.

OH Yeah! Detailed tech topics!? That’s a treat for this forum. Please allow me to bridge this gap with best of ability efforts.

AI is a popular buzzword of the day, the race to automated superiority. AI is the necessary ingredient right? Presumably because the people who code can’t get there on their own with programmed parameters and we need a higher intellect with more computational power than the most advanced computer on the planet, the human brain, to reconcile all this data? Perhaps the tech guys are taking weekends off, have a 30 hour workweek, just can’t find the time. Or perhaps the dream of complete automation in real estate is a wingnut theory in the first place. Big tech and big data is suffering the publish or perish symptoms right now. They claimed a massive market stake and now are seeking to justify their presence in a more legally compliant and more widely applicable setting after the fact.

Appraisers are suffering from a similar identity crisis where individual appraisers have confused themselves with wall street investors and tech companies, promoting automation, absent of the fundamental understanding of how the tech works in the first place. Reaching beyond the appraisers appropriately limited scope of work participation as a check to the balance and independent analyst point, operating apart and independent from the larger integrated mechanics of the interested companies. The push to use integrated systems is synonymous with abdicating our role as independent checks to the balance.

Big data systems like Zillow rely on the theory of computation. This is reliant on 3 parts, language theory, computability theory, and computational complexity theory. The problem with real estate integration and big data is the human factor. It remains impossible to accurately move to complexity theory application (3rd stage), when during the assimilation of data through computation (2nd stage), after hopefully interpreting and mapping the language correctly (1st stage), the human and real property behaviors remains largely unpredictable without updated data on that behavior and states of condition. Don’t believe the hype, without human presence the data modeling systems will never work in real estate. A human must be there to input current data otherwise the complex calculations will be based on inadequate or fictitious data, aka in appraisal; stale data. The rush to AI and big data is a consequence of a myopic understanding of how tech works, as the majority of decision makers hefting tech around left and right do not actually understand coding themselves. Constantly dressing the same old tech up in a new package, perhaps with some clever new coding but really never properly managing the question of what is reducible data and what is irreducible data.

Right now, somewhere, a tech programmer is hunched over his pc smoking the keyboard with code entries, while some corporate ceo is whipping him in the back telling him to get it done if he wants a job tomorrow. Not surprisingly, he is able to dress something up, integrate language, slap a graphic on it, and even publish that work, all the while never actually having to withstand adequate measures of peer review prior to or after publishing. (Who has time for peer review of tech with this much demand?) It appears Zillow and their counterpart companies spends more time and money on pr and image control than R&D, actually tacking the question of how to have adequate computability without actually having a current measurement.

The hubris of tech companies and those whom promote such, is the notion that the available public record and sales data is good enough, no human appraiser is necessary, believing firmly that success is achievable through reactive principals of available data interpolation tools. They believe their systems can be programmed to be reactive to apparently reducible data, therefore make more accurate predictions after that data is present in the computation stream. The problem with that in real estate is that because the data is stale and early results will be calculated prior to reducible data cleaning or correcting, someone would have to lose before the next party could theoretically benefit from cleaned up interpolated data. And it’s a recurring systemic concern which cumulates with time as all data will eventually become stale, often with exponential unpredictable differences regarding how long that data takes to become stale, aka the X factor of human behavior. It is truly remarkable that FNMA is not grasping these concepts in their race to advocate on behalf of institutional investors, and have apparently abdicated their duty to demand irreducible data, aka; full service human appraisal inspection. It will be painfully entertaining to see what gimmicks they come up with on the new forms to try and solve this unsolvable problem which is the fact that human behavior and real property conditions constantly evolve and change as swiftly as new technology and building and lending tools are made available.

Welcome to the brave new world of the digital age. It ain’t your grandpa’s vcr anymore, even if that seemed new to us at the time and we still remember that. It’s ancient history as computational power steams forward. I’m like John Henry over here, scribbling notes with pencils and form filling manually while everyone is telling me to automate. Not going to happen. Knowledge is power. We’re not there yet, not even close. If anyone bothered to listen to Elon Musk on the matter, it would be a wise decision to slow this all down and let tech systems develop for a very long time in less consequential fields before we attempt to implement them into such crucial social infrastructures.

It’s a great example! It’s also a multiple flipped property since 2015 I’ll assume the first $520k sale may be a fixer, selling for $620K 4 months. Then only a couple years or so later it flips again for $760k on 7/30/2018.

Nothing remarkable about that for SoCal RE EXCEPT CoreLogic’s own market trend data shows the median price in its area DECLINING steadily over the past 2-3+ years. PS-SF is now 932 in CoreLogic’s Realist, and it looks like a pool in the aerial Bing photo.

RealValue (Corelogic) is $799,023 as of 7/18/2018 in a range of from $695,000 to over $902,000 I rounded. CL is even more accurate than what I wrote. “Tight!” From a low end of range  8 1/2% LESS than it sold only two weeks later, to a point value 5+% ABOVE what it sold for, to a high end of range more than 18% above its actual sale price.

Make sense of THOSE numbers, lenders and regulators! Oh, and definitely qualify it for a PIW – after all it sold FHA for $620k back in 12/2015 about 4 months after it sold for $520k in 08/2015.

To each and every single regulator that thinks PIWS and AVMs are “ok” I have only one thing to say:

“Asshat”.

Great post Alan.

I do pay attention to CoreLogic. Just as I paid attention to FNMA’s fatally flawed Collateral Underwriter Process since its patent application was submitted, and before it was adopted as policy in January 2015.

CoreLogic is INFAMOUS for providing both incorrect and conflicting data concerning physical attributes of property. Even when the conflicting data is from their own alternate products!

One of the earliest computer axioms still applies today.

GIGO “Garbage In-Garbage Out.” What they are really doing today in many so called “AI” scenarios is lowering the bar of acceptable accuracy, and then pretending that subjectively scrubbing the data to produce the desired results still maintains scientific reliability.

There is no such thing as cognitive ability in computers-yet. All they do is say yes or no very, very, very fast to many sequential questions.

Does anyone know if Mercury and all other portal softwares will implement a shelf life limitation for stored data? It occurred to me that I’m still able to look into full detail for reports completed something like ten years ago…  Suddenly it’s not fun to use these third party systems anymore. Eventually an appraiser is going to argue the right to be forgotten, like that’s where this is headed in the bigger longer term picture.

Tech is so amazing, I’m glad we outsourced all these jobs overseas, crushed domestic production facilities, pushed a literal continent of ewaste forward, compromised privacy on an epic unheard of scale, and bred an entire generation of people with no manual labor skills whom prioritize convenience over liberty. What could go wrong? I guess now we’re supposed to debate the merits of it, how specifically to best use it, or what exactly is happening here? I’ll take an appraiser who knows how a furnace and electrical box works anyday over someone who understands coefficient application and subscribes to big data systems. We need a new stereotype, or something, whatever. Learn to code.

It was an awesome article, Woody is the man. I just shortcut the argument by entering unique data for each and every comp, every time, even if I have used it before. What makes the entry consistently unique is the entry is relative to the subject, and therefore is irrelevant when compared contrasted or applied elsewhere. Typing fast is so easy, the manual comparison and subsequent analysis can be the most defensible point for an appraisers analysis, I fail to understand how appraisers benefit in terms of quality work product by cutting out the most essential part of analysis, relevant and direct comparisons of comps vs subject. This knowledge gained from only a half hour of manual type up, photo and mls review, and cross referenced data of gridded comps often provides the best framework for all other analysis points. Or just outsource the duties of typing and data entry so you can get back to ‘appraising more’, whatever that means, nonsensical jargon from the tech crew… 

I suppose if one does not understand the underlying process and function, the infinitely repackaged tech may certainly still hold some sort of wondrous amazing power to the laymen. I prefer my tech to be painfully static and managed by people whom can not actually write code, with cleverly applied permissions structures so I can feel good about subscribing indefinitely and never receive a finished product. Do you offer that in analog?

Well… I type 100wpm or faster which was a quite easy skill to develop with fun old Typershark online gaming, and never get any calls from amc’s. 

Now, on to the actual problems which are not self imposed. The problem with big data systems is that it’s easy to set them up but increasingly difficult to maintain cohesive current data as time passes. Was at the hospital today and although we’re under totally different insurance, their complex data systems still notes our old employer, even though we’re covered by the new one. Sure, update that data, again, and again, and again, maybe one day it will actually happen. Big data is not just a central repository of data, it’s mirrored and segregated and mirrored again on a vast network of servers that are unlikely to be in the same location or under cohesive management in the first place…  Until they have D-Wave computers managing all of that, such persistent inconsistency will continue because administrators will never have an adequate hierarchy or agreement regarding who’s data is most current, who’s servers are most secure, and where updated and introductory data flow must through because they seek to avoid bottlenecking and bus overload. There are after all, as many entry points for data input as their are data points themselves. 

Big data. Big joke. Put a call in to test the alamode systems at the next whitehat gathering and watch how easy they make it look, it’s a rule of thumb these days. Computers are not some grand mystery, they’re just tools and like any tool, in the hands of an inexperienced mechanic they can do more harm than good.

I’d bet not a single licensed appraiser or lender or amc manager whom promotes these items knows how to code themselves. Tech people are not as smart as generally given credit for, they stand on the shoulders of giants and we’re approaching ‘idiocracy’ at a breathtaking accelerating pace. 

Where is that time machine again? Learn to code I guess, what more is there to say?

#!/bin/bash

if [ $? -eq 0 ]
then
echo "The data has been successfully updated"
exit 0
else
echo "The appraiser is a moron and data rejected" >&2
exit 1


Artificial intelligence (AI), sometimes known as machine intelligence, refers to the ability of computers to perform human-like feats of cognition including learning, problem-solving, perception, decision-making, and speech and language. Early AI systems had the ability to defeat a world chess champion, map streets, and compose music. Thanks to more advanced algorithms, data volumes, and computer power and storage, AI evolved and expanded to include more sophisticated applications, such as self-driving cars, improved fraud detection, and “personal assistants” like Siri and Alexa. Today, medical researchers are using AI to develop technology that will detect a range of diseases, improve radiology imaging, fine-tune radiation treatments, simplify DNA sequencing, and advance precision medicine for more individualized health care.

Source: https://www.psychologytoday.com/us/basics/artificial-intelligence

Will Artificial Intelligence Soon Tell Us How To Live?

Source: https://www.forbes.com/sites/cognitiveworld/2019/01/27/will-artificial-intelligence-soon-tell-us-how-to-live/#4090339d2938

At the same time, the AI is evolving now in an unprecedented way, and the interim results of this transformation are expected to be truly impressive: according to the report, 79% of the banking sector representatives anticipate that in the next two years, technologies will advance to such an extent that artificial intelligence could work in financial organizations equally with living people as an employee and reliable advisor.

Source: https://www.fintechnews.org/artificial-intelligence-in-banking-industry-conversion-to-genuine-benefits/

Over the past couple of years, Artificial Intelligence (AI), including Machine Learning (ML), has gained traction by businesses that deal with large amounts of data to reduce human error and improve operational efficiency. With AI, computer systems are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, language translation, and decision-making. And with ML capabilities, they also have the ability to process large amounts of data (structured and unstructured) from various sources and recognize patterns in the data to identify opportunities or risks.

Major areas of AI/ML application to the mortgage industry may include identifying anomalies, assessing risk, exploring non-credit bureau data to enhance prediction of loan performance, and answering customer questions (e.g., search tools, improved guides, and chatbots).

Source: http://www.fanniemae.com/resources/file/research/mlss/pdf/mlss-artificial-intelligence-100418.pdf

Artificial Intelligence (AI) prediction models. This study attempts to analyze and summarize AI techniques, which gives insight to application of various techniques for prediction related to property valuation. Comparison of various techniques shows that Artificial Neural Network (ANN) and fuzzy logic are better suited if attributes and model parameters are appropriately selected.
Keywords: Real property, value forecasting, artificial intelligence, neural network, valuation.

Source: http://www.enggjournals.com/ijet/docs/IJET13-05-03-087.pdf

Pay attention to the fuzzy nature of logic cause like I said IT’S LEARNING, a bit or 1 or 0 reverse engineered into a database needs to know how to apply variance to the emotions and variances including all this inconsistent UAD stuff we are to aid by HARMONIZING this dam database even more going forward.

What you want to pay attention to is the movements of core logic for one as they will buy up key companies or startups with good A.I. and with access to data, historically this has proven to be true. All pay attention to NN and ANN these are neural networks to be combined with all this later. Remember the property is static and lets say 150 million homes in the US. Once they all get loaded up and they can link up the datapoint the variances are next, cycles, condition, market trend, cost of money, etc etc. From there just like the A.I. that lost the to worlds best Chess player originally that A.I. came back later and kicked his ass. So like I said we are feeding this machine that right now humans are empowering and just like the horse and carriage the car took over, just like the factor worker the robot took over and just like the appraiser the algorithm when it reaches it’s A.I. potential (ability to do what a human does) it too will take over.

P.S. for those not believing in this stuff, google how they are now using/considering DNA for storage of data. Yep that is how far advanced we are into this rabbit hole that the dam machine now wants our DNA to store data and the dumbass humans allowing this are insane.

https://www.technologynetworks.com/genomics/articles/dna-the-future-of-digital-data-storage-299234

Thanks
Alan

Seek the truth.

AMEN, good on you.  And also Protecting (our)  data is a waste, it is implying that the info is ours, not generated by others.

Most of us are in states where disclosure is the LAW. The sales prices are published as a matter of record, MLS prides itself on accuracy and disclosure.

WHO is the prideful appraiser that tries to capture, only interpretation is allowed.