Donald Trump’s healthcare bill is already in a death spiral – FT

Via the FT. Let’s all take to calling it Trumpcare as often as possible….


A disproportionate share of those losing their insurance would be older, white Americans who voted Trump.

via Donald Trump’s healthcare bill is already in a death spiral

The Big Problem With Big Data

Cathy O’Neil (aka MathBabe) has posted another good piece on the drawbacks of using big data-driven algos to make important choices. Via Bloomberg View:

One issue is that the algorithms tend to use linear models, so they assume that more is always better, and way more is way better. This can be fine when dealing with attributes such as education or experience. Something like Facebook activity, by contrast, could have a golden mean — a reasonable amount might suggest engagement in a community, while an abundance could indicate addiction.

More important, such algorithms will tend to discriminate against attributes that, though beyond people’s control, have historically been correlated with a lack of success. A marker of poverty or race, for example, can translate into a demerit, even if the person is eminently qualified — thus reinforcing the historical pattern that the algorithm finds in the data.

This follows on an earlier post (Insurance and Big Data Are Incompatible) regarding the drawbacks of allowing health insurers to use big data-fed algos to make coverage and premium-setting decisions.

These algos are touted as impartial arbiters, free from human bias and prejudice. They’re not. They draw conclusions from properties exhibited by large groups of people – their Facebook likes, zip codes, career choices – and apply them to individuals. In the aggregate, this might work, but for the individual person seeking insurance, applicant seeking a job, inmate seeking parole or homebuyer seeking a mortgage, the outcome can be manifestly unfair and riddled with the types of biases that the systems were meant to eliminate in the first place.

via Bigger Data Isn’t Always Better Data – Bloomberg View

Watchdog’s MetLife Blunder Boosts Systemic Risk

If MetLife’s escape from too-big-to-fail scrutiny leads to a rush for the exits by more obvious financial time bombs, regulators only have themselves to blame.

The country’s largest insurer just convinced a Federal court that the Financial Stability Oversight Council’s designation of it as a “systemically important financial institution” under the post-Crisis Dodd-Frank rules was arbitrary and capricious.

The details of the ruling, handed down on March 30, are sealed until April 6, but other non-bank SIFIs are already straining at the leash.

GE filed an application with the FSOC today to have its SIFI status removed. It and MetLife are two of four non-bank SIFIs – the other two are Prudential and AIG. Prudential has kept mum on its plans; AIG – the near-death experience of which was one of the most painful pain points of the Crisis – hasn’t a prayer. Its $180 billion government bailout and de facto nationalization saw to that.

In 2013 and 2014 the FSOC, a panel of financial regulators set up under Dodd-Frank in large part to oversee potential basket cases, lumped these four in with more straightforward financial time bombs – investment banks and commercial banks like Goldman, JP Morgan, Citi and others. From the FSOC’s statement at the time:

Under Section 113 of the Dodd-Frank Act, the Council is authorized to determine that a nonbank financial company’s material financial distress—or the nature, scope, size, scale, concentration, interconnectedness, or mix of its activities—could pose a threat to U.S. financial stability. Such companies will be subject to consolidated supervision by the Federal Reserve and enhanced prudential standards.

GE boss Jeff Immelt never claimed that GE Capital – once the biggest commercial paper issuer and the entity that generated over half the financial-industrial behemoth’s sales at its height – wasn’t systematically important. He has spent the last couple of years slashing GE Capital assets by some $160 billion, reducing its contributions to revenues from half to just under 10 percent.

The MetLife court case is the real problem for FSOC. It seems from MetLife’s complaint, and the bits and pieces reporters have gleaned from the court ruling, that FSOC failed to make a convincing argument that the insurance business model was subject to capital pressure due to customers’ “running for the exits” – akin to a run on a bank – and that this vulnerability threatened the financial system due to the firm’s size and interconnectedness. Bloomberg View’s Matt Levine has a run-down on the argument here. MetLife also claims the FSOC never did a vulnerability analysis. If so, that’s at best sloppy and at worst terribly arrogant regulatory behavior.

Step back for a second. MetLife says its business model is not subject to runs because it issues long-term liabilities (insurance policies) that customers cannot cash in at will. But FSOC, if anyone’s awake there, knows the trouble isn’t with the firm’s liabilities, it’s with its assets.

This is an industry wide problem. Insurance margins have been crushed by low rates; the need to shimmy further and further down the credit spectrum in search of yield has been tempting. Like banks making mortgages, insurers are in the maturity transformation business – borrow short, lend (or insure) long, and hope to the gods things add up in the end.

That’s where the risk in an institution like MetLife lurks. But it’s not a contagious risk. If assets fall short of liabilities, shareholders get screwed first, then, perhaps, policyholders, although that would be almost unthinkable with a firm of MetLife’s size.

So by designating MetLife a non-bank SIFI, regulators did two things. First, they stretched the rationale for such a designation to the point where the firm was able to blow it up in court (against expectations – MetLife was so sure of losing it had begun to execute plans to spin off many of its business lines). And as a result, they gave the anti-regulation camp a shot in the arm – and that could lead to more systemic risk, not less.