TechTalk Blog - Role of the Management Accountant In Using Big Data and Predictive Analytics to Protect the Public Interest - Preventing Bias and Discrimination

By David Colgren posted 09-06-2018 12:45 PM

  


Great white paper from the US Federal Trade Commission on “Big Data - A Tool for Inclusion or Exclusion? Understanding the Issues”...

Big data analytics can provide numerous opportunities for improvements in our society and the capital markets worldwide. In addition to more effectively matching products and services to consumers, big data can create opportunities for low income and underserved communities through out America. Big data for example is helping target educational, credit, healthcare, and employment opportunities to low-income and underserved populations. It can also pin-point areas of crime and match social programs to create pathways out of marginalization in crime infested neighborhoods. 

Protecting Those in America Most at Risk - Vulnerable Children

Could data analytics and predictive analytics be used to protect those members of society most at risk - children? This article talks about how big data and predictive analytics can be used in our inner cities to protect vulnerable children.

Some 3 million children in the United States are the subject of maltreatment investigations each year, -- 700,000 of which are substantiated. There are about 2,500 child fatalities due to abuse or neglect by a parent or caregiver in the U.S. annually, and about half of those are cases child welfare agencies were aware of beforehand. Could we protect these “at risk” children we already know are at risk through better data analytics and predictive analytics?
 
“Million Dollar Blocks” In Urban Cities Across America

Data analytics and predictive analytics is being used to prevent crime and revitalize urban neighborhoods in the United States.

The New York-based Justice Mapping Center has been providing visuals of neighborhoods with high-degrees of crime for more than a decade using big data analytics. For example, by mapping the residential addresses of every inmate in various prison systems, the center has made vividly clear a concept it calls "million-dollar blocks" — areas where more than $1 million is being spent annually by government to incarcerate the residents of a single census block. Progressive cities are creating social programs in these targeted “million-dollar-blocks” to reduce crime through re-entry programs - including educational facilities to provide jobs and vocational skills to at-risk populations. There are hundreds of re-entry programs under way in cities across the country, and program designers are only just starting to use tools like big data, predictive data analytics and mapping (data visualization) to understand how incarceration and re-entry affects communities and government services. We know there are effective ways to better target government, company and community resources in neighborhoods to change economic demographics - which ultimately build stronger, safer cities and "connect" citizens to thriving communities. Big data can also be used to better determine the performance of government services to neighbors where these "million-dollar-blocks" are located. 

Role of Private Companies and a the Importance of a Vibrant Capital Markets

Private firms also hold a wealth of data that could enhance efforts to predict neighborhood change, including credit scores, health services, advertised rents, and retail purchases. These datasets are updated frequently, allowing for real-time reporting—an essential component of an effective early warning system. Other firms, for example, mobile phone providers and social media platforms, collect crowd-sourced user data that could also improve the timeliness of data and reveal how residents perceive and use neighborhood amenities.The private sector plays a major role in helping government utilize services more effective. 

From the Urban Institute -- “Understanding neighborhood trajectories would help cities get ahead of the curve to develop and implement place-based investments and policies to protect and promote economic inclusion. These strategies would most directly address families’ isolation from opportunity but could also improve economic security for vulnerable residents in changing neighborhoods. Residents would have greater security of tenure in neighborhoods facing upward market pressures and experience less distress and loss of wealth in neighborhoods at risk of decline.”

More and more data sectors (sources) will be coming over from the private sector to the government sector to support neighborhoods and local communities.  

Rise and Ethical Role of Management Accountant Data Services

Management accountants working inside companies and government organizations are playing a major role now in protecting the public interest through data analytics and predictive analytics. These services are -- and will be - further utilized to help communities more effective deploy government services to protect children, reduce crime and facilitate better health care and economic prosperity. Data analytics and predictive analytics is critical to effective allocation of critical capital to meet public and private needs in a vibrant capital markets. Good investment decisions is based on sound data analytics.  

Continuing to fight the battle:

On the flip side - unfortunately -- economic segregation is on the rise in cities across the United States -- preventing low-income families and vulnerable populations from accessing decent jobs, essential health care services, and safe and affordable housing. Multiple factors can contribute to segregation across neighborhoods and metropolitan areas, depending on local conditions and economic and demographic trends. In places with growing economies or rising demand for urban housing, affordability pressures and evictions can displace low-income families and small businesses, preventing them from benefitting from new opportunities in their neighborhoods. In weaker markets, disinvestment and crime can create downward spirals of distress, trapping low-income families in increasingly toxic and disconnected environments.

Potential inaccuracies and biases in data analytics might lead to detrimental effects for low-income and underserved populations and hurt or even kill those most at risk in our society. For example, there are concerns that companies could use big data to exclude low-income and underserved communities from credit and employment opportunities. Using data analytics to deny service through bias -- creates marginalization and does not serve the pubic interest and in some cases violates US law. 

Consequently, organizations – including government - need to consider whether their data sets are missing information from particular populations and, if they are, take appropriate steps to address this problem so as to not actively create EXCLUSION or DISCRIMINATION in the services they provide. Especially as certain services/analytics becomes mechanized without human analysis -- meaning -- is bias being built into programming that promotes exclusion or discrimination? Are accountants within management being asked to build into programming this bias and what ethic and business risk does this pose to the company, organization or government entity it serves? 

This US Federal Trade Commission white paper from 2016 suggests steps organizations can take related to big data analytics and predictive analytics to prevent bias/ marginalization and avoid legal and ethical risks companies can face under US law. Suggestions from the FTC include:

  1. Review your data sets and algorithms to ensure that hidden biases are not having an unintended impact on certain populations.
  2. Remember that just because big data found a correlation, it does not necessarily mean that the correlation is meaningful. As such, you should balance the risks of using those results, especially where your policies could negatively affect certain populations. It may be worthwhile to have human oversight of data and algorithms when big data tools are used to make important decisions, such as those implicating health, credit, and employment.
  3. Consider whether fairness and ethical considerations advise against using big data in certain circumstances.
  4. Consider further whether you can use big data in ways that advance opportunities for previously underrepresented populations.

 Companies can use big data in ways that provide benefits to themselves and society, while minimizing legal and ethical risks matching products and services to consumers. Every company in the United States serves the public interest by the license they hold that can be removed by the public at any time. What data elements held within the organization for example can be used to create opportunities and transform local communities or society as a whole -- critical to keeping a stable and democratic government?

In addition, companies should have an understanding of the various laws, including the Fair Credit Reporting Act, equal opportunity laws, and the Federal Trade Commission Act, that may apply to data governance practices used by companies.

Companies and organizations should also support diversity and inclusion efforts -- and part of this effort management accountants will play includes using data analytics and predictive analytics in a way that is not bias or discriminatory and consider how the services they provide and the data elements contained within their organization can be used to better serve the public interest. Accountants are perceived by society to be one of the most trusted advisors to both individuals and businesses owners – to maintain this continued confidence – as accounting evolves into more data analytics and predictive analytics – data governance and data stewardship will become even more critical in serving the public interest by the management accountant. Examples above begin to show the public interest data plays in saving and protecting lives.

Management accountants can anticipate both changes to their professional careers related to data analytics and predictive analytics and the new ethical/ data governance standards they will be asked to maintain. Diversity and inclusion ethical considerations will become increasingly important as data is shared with society to protect the public interest.

    

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