Avoiding Discrimination in Unstructured Data

An article published by the Wall Street Journal on Jan. 30, 2019  got me thinking about the challenges of using unstructured data in modeling. The article discusses how New York’s Department of Financial Services is allowing life insurers to use social media, as well as other nontraditional sources, to set premium rates. The crux: the data cannot unfairly discriminate.  

I finished the article with three questions on my mind. The first: How does a company convert unstructured data into something useful? The article mentions that insurers are leveraging public information – like motor vehicle records and bankruptcy documents – in addition to social media. Surely, though, this information is not in a structured format to facilitate querying and model builds.

Second: How does a company ensure the data is good quality? Quality here doesn’t only mean the data is clean and useful, it also means the data is complete and unbiased. A lot of effort will be required to take this information and make it model ready. Otherwise, the models will at best provide spurious output and at worst provide biased output.

The third: With all this data available what “new” modeling techniques can be leveraged? I suspect many people read that last sentence and thought AI. That is one option. However, the key is to make sure the model does not unfairly discriminate. Using a powerful machine learning algorithm right from the start might not be the best option. Just ask Amazon about its AI recruiting tool.[1]

The answers to these questions are not simple, and they do require a blend of technological aptitude and machine learning sophistication. Stay tuned for future blog posts as we provide answers to these questions.


[1] Amazon scraps secret AI recruiting tool that showed bias against women


Jonathan Leonardelli, FRM, Director of the Business Analytics for the Financial Risk Group, leads the group responsible for model development, data science, documentation, testing, and training. He has over 15 years’ experience in the area of financial risk.

Does the Liquidity Risk Premium Still Exist in Private Equity?

FRG has recently been investigating the dynamics of the private capital markets.  Our work has led us to a ground-breaking product designed to help allocators evaluate potential cash flows, risks, and plan future commitments to private capital.  You can learn more here and read about our modeling efforts in our white paper, “Macroeconomic Effects On The Modeling of Private Capital Cash Flows.”

As mentioned in a previous post, we are investigating the effects of available liquidity in the private capital market.  This leads to an obvious question: Does the Liquidity Risk Premium Still Exist in Private Equity?

It is assumed by most in the space that the answer is “Yes.”  Excess returns provided by private funds are attributable to reduced liquidity.  Lock up periods of 10+ years allow managers to find investments that would not be possible otherwise.  This premium is HIGHLY attractive in a world of low rates and cyclically high public equity valuations.  Where else can a pension or endowment find the rates of return required?

If the answer is, “No,” then Houston, we have a problem.  Money continues to flow into PE at a high rate.  A recent article in the FT (quoting data from FRG partner Preqin) show there is nearly $1.5 trillion in dry powder.  Factoring in leverage, there could be, in excess of, $5 trillion in capital waiting to be deployed.  In the case of a “No” answer, return chasing could have gone too far, too fast.

As mentioned, leverage in private capital funds is large and maybe growing larger.  If the liquidity risk premium has been bid away, what investors are left with may very well be just leveraged market risk.  What is assumed to be high alpha/low beta, might, in fact, be low alpha/high beta.  This has massive implications for asset allocation.

We are attempting to get our heads around this problem in order to help our clients understand the risk associated with their portfolios.


Dominic Pazzula is a Director with the Financial Risk Group specializing in asset allocation and risk management.  He has more than 15 years of experience evaluating risk at a portfolio level and managing asset allocation funds.  He is responsible for product design of FRG’s asset allocation software offerings and consults with clients helping to apply the latest technologies to solve their risk, reporting, and allocation challenges.






Private Equity and Debt Liquidity, the “Secondary” Market

A significant consideration in several aspects of Private Equity and Private Debt has been attributed to the liquidity (or lack thereof) of these investments.  The liquidity factor has been cited as a basic investment decision, influencing complex pricing, return of investment and financial risk management.  But as the environment has changed and matured, is liquidity being considered as it should be?

FRG’s ongoing research suggests that some of the changes this asset class are experiencing may be attributable to changes in the liquidity profile of these investments, which in turn may affect asset management decisions.  As modeling techniques continue to evolve in the asset management space, illustrated in our recent paper Macroeconomic Effects On The Modeling of Private Capital Cash Flows, their use as both an asset management tool and a risk management tool become more valuable.

The extreme importance placed on liquidity risk for all types of financial investments, and the financial community in general, to this point in time have been primarily associated with public investments.  However, a burgeoning “secondary” market in Private Equity and Private Debt will change the liquidity consideration of this asset class, a better understanding of which is necessary for investment managers active in this space.  Achieving this understanding will in turn provide private equity and private debt investment managers with another perspective with which to assess management decision aligning a bit more with that traditionally available for public investments. FRG is refining research into the liquidity of Private Capital investments through an appreciation of the dynamics of the environment to provide a better understanding of the behavior of these investments. Watch for more from us on this intriguing subject.

Read more about FRG’s work in Private Capital Forecasting via the VOR platform.

Dr. Jimmie Lenz is a Principal with the Financial Risk Group and teaches Finance at the University of South Carolina.  He has 30 years of experience in financial services, including roles as Chief Risk Officer, Chief Credit Officer, and Head of Predictive Analytics at one of the largest brokerage firms and Wealth Management groups in the U.S.

Macroeconomic Effects on the Modeling of Private Capital Cash Flows

The demand of private capital investing has investors clamoring for more information about prospective cash flows. Historically, that data has been hard to estimate. Because the investments aren’t traded on a public venue, there are few figures generated beyond the data received by existing investors.

So what’s an investor to do? FRG has developed a Private Capital Model solution that provides more insight and understanding of the probable cashflows, one that includes the macroeconomic variables that have been found to influence cash flows and significantly improve the forecasting probabilities. We have found those variables create a more complete picture than the Takahashi and Alexander model, commonly used within the industry to provide guidance around cash flows.

Three of FRG’s modeling and investment experts – Dr. Jimmie Lenz, Dominic Pazzula and Jonathan Leonardelli – have written a new white paper detailing the methodology used to create the Private Capital Model, and the results the model provides. Download the paper, “Macroeconomic Effects on the Modeling of Private Capital Cash Flows” from the Resources section of the FRG website. Interested in a perspective on an investor’s need and utilization of cash flow information? Download FRG’s first Private Capital Fund Cash Flows paper.

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