Monday, October 30, 2017

Financial Exploitation And Abuse Of Elderly Is The Same In Child Welfare

Image result for greedy money
Court Appointed Guardian Private Corporations
The Office of Justice Programs’ National Institute of Justice today published an article online that discusses new ways to identify financial exploitation and abuse of the elderly.

Great.

The Office of Justice Programs' National Institute of Justice decided to put skin in the game and come up with a new reason to utilize its human databases to scrap up all that 'financial exploitation' going on with elderly adults.

See, I am critical because the same goes on in child welfare, but, I digress.

The state courts assign representatives to older persons, in many instances, a private corporation.

The private corporation takes all their assests, just like they do in foster care.

The state will take all assets to "repay" for care, just like they do in foster care.

There is no civil rights assistance by the States attorney general because the States attorney general contemporaneously advocates and advises the state, which has made judicial determination for the appointment of a privately contracted representative, just like they do in foster care.

This means that the elderly individual, family members, or anyone of affinity, is forced to come out of pocket to hire an attorney for a civil action, which many, if not all, cannot afford.

Same thing happens in foster care.

The States become the beneficiaries.

So, instead of legal assistance program, or a direct phone or email to report fraud, these tech guys got a bunch of money to figure out how they can get into the financial fraud game using the human databases.

One of the variables is to detect real estate ownership of these elderly persons.

Besides, what do you think is going to happen once financial exploitation is identified among elderly adults?

The same thing that they do when fraud is identified in foster care.

Computers Learn To Detect Financial Abuse of the Elderly

Computer learning may provide a new avenue for creating tools to identify financial exploitation among elderly adults.


Extending on work by Drs. Shelly Jackson and Thomas Hafemister on the characteristics of elder financial exploitation,[1] NIJ funded researchers at the University of Texas Health Science Center at Houston to see if computers can “learn” how to: (1) distinguish between financial exploitation and other forms of elder abuse; and (2) differentiate between “pure” financial exploitation — when the victim of financial exploitation experiences no other forms of elder abuse and “hybrid” financial exploitation — when financial exploitation is accompanied by physical abuse or neglect.

This study demonstrated an innovative way to leverage administrative data to understand patterns of financial exploitation.

The researchers found that computer models were effective in identifying financial exploitation and its subtypes. This study may provide practitioners with ways to use existing data to identify financial exploitation among elderly adults.

Carmel Dyer, Jason Burnett, and their team used a Texas adult protective service administrative statewide dataset with 8,800 confirmed cases of elder abuse. The data were randomly split 80/20. The larger dataset was used to “train” the computer to detect patterns for financial exploitation and differentiate between pure financial exploitation and hybrid financial exploitation. The smaller dataset was used to test the computer models on accuracy in classifying the financial exploitation cases.

The computer algorithms were reliably able to predict clients who experienced financial exploitation compared with those who experienced other forms of elder abuse. Understandably, the main factors that distinguished the financial exploitation from other types of abuse were misuses of financial assets.

In distinguishing between pure financial exploitation and hybrid financial exploitation, the computer algorithms were able to make modest improvements in prediction accuracy compared to chance. The biggest factor that set the two apart was that hybrid financial exploitation cases were more likely to have an apparent injury (e.g., skin tears, bruises). Hybrid financial exploitation cases were also more likely to include clients who had overburdened caregivers, were facing a foreclosure, and were physically dependent than pure financial exploitation cases.

This study demonstrated an innovative way to leverage administrative data to understand patterns of financial exploitation.

The computer was able to learn how to distinguish financial exploitation from other types of elder abuse and further learn patterns of pure financial exploitation versus hybrid financial exploitation. The study only used the first confirmed abuse case, and there may be additional information to be learned from those who have repeat adult protective service reports. The researchers hope these data algorithms can be transformed into web-based applications so that practitioners can monitor financial exploitation in real time and quickly intervene.

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