Some members will get sick, some may have a predisposition to illness and some may live or work in places where illness is known to be more prevalent. But we don’t deny them healthcare or insurance.
"The burden for society is to ensure false precision doesn’t enter the [credit] system, increasing discrimination or exclusion.”
One of the challenges then, as society move towards more accurate understanding of an individual’s financial position is what we do with that understanding. There are tensions to be managed.
Take comprehensive credit reporting for example. The measure will provide a more complete picture of a would-be borrower’s financial affairs to would-be lenders. This has been many years coming to Australia and is already widespread globally.
It is now being mandated and rolled out; government is requiring banks to participate. The attractions are clear: providing both positive and negative data – that is, a full record of credit applied for and repaid as well as defaulted upon – has been shown to reduce bad loans and make finance cheaper for those with good credit records.
The downside however is would-be borrowers become far more dependent upon their credit history which, for a range of reasons – for example, illness – may be tainted by events beyond their control.
As Artificial Intelligence and machine learning come more into play in decision making, a vastly richer array of data will also be utilised to make credit decisions, even factors such as lifestyle, friends, spending patterns and more.
In aggregate, greater fidelity in credit decisions should help society as a whole. But safeguards are essential less an unexpected consequence is financial exclusion.
There is an analogy here with the familiar warning on wealth products: past performance is a poor guide to future outcomes. Lenders know some loans will go bad, they just don’t know precisely which ones. They also know some borrowers considered higher risk will go very well.
So making credit scoring more precise may actually deny credit to some who ultimately may prove to be good credits – despite their past performance or current circumstances.
My colleague Nigel Williams, ANZ’s head of risk, cites one scenario where sharing data via a comprehensive credit reporting regime could potentially harm a would-be borrower.
Banks encourage customers to come forward early with repayment problems, say due to a job loss or marriage breakdown.
Banks then endeavour to re-work repayments to give the customer some respite but still ultimately repay the loan. Both sides win if that works. The borrower’s credit record remains intact.
However, under the new regime the initial repayment trouble could be shared with other potential lenders (exactly how this plays out remains uncertain), so the borrower might automatically have a negative credit mark.
As Christopher Kent, the Reserve Bank of Australia’s Assistant Governor (Financial Markets), said in a recent speech, The Availability of Business Finance, comprehensive credit reporting will provide more information to lenders about the credit history of potential borrowers.
“When information about credit that has been repaid without problems also becomes available publicly, the cost of assessing credit risks will be reduced and lenders will be able to price risk more accurately; this may enhance competition as the current lender to any particular business will no longer have an informational advantage over other lenders,” he said.
“It may also reduce the need for lenders to seek additional collateral and personal guarantees for small business lending, particularly for established businesses. Indeed, the use of personal guarantees is more widespread in Australia than in countries that have well-established comprehensive credit reporting regimes, such as the United Kingdom and the United States.”
Further, making such data public – or even more available on a restricted basis - should also encourage new, non-traditional competitors who can use the data to launch new products and platforms.
In Australia, credit agencies – which manage all the borrowing and repayment data - have been collecting more information since the new credit reporting regime started in March 2014.
As well as information such as missed payments of more than 60 days, defaults and bankruptcies, they will now collect monthly payment histories on loans and credit cards and flag missed payments of more than 14 days.
Of course, one of the implications is there is now a much greater onus on individuals to make sure their credit reports are accurate – a non-trivial matter as anyone who has ever tried to correct theirs will know.
Consumer groups are also worried about the implications for access to finance and the price of finance.
For example, in its submission to the Royal Commission into misconduct in the banking, superannuation and financial services industry, the Consumer Action Law Centre argued the comprehensive credit reforms will increase the ability of lenders to “profile for profit”
“It has significantly added to the imbalance of market power between consumers on one hand, and banks and insurers on the other,” CALC said.
“Experience at home and internationally suggests these reforms will results in ‘riskier’ borrowers paying higher interest rates and premiums, potentially contributing to financial exclusion rather than reducing it.
“Price discrimination should be a cause for concern where it contributes to people on lower incomes paying higher prices than others, or where pricing discrimination negatively affects particularly marginalised groups. These are key issues of fairness and equity.”
At its most dystopian, this is the world of Gary Shteyngart’s Super Sad True Love Story, a novel set in the new future where a consumption-driven totalitarian regime has made the credit score a critical the measure of human worth.
A further consequence of greater fidelity in credit data is institutions will design, tailor and price products more specifically for their most profitable customers.
Again, this makes sense for one institution but, if ultimately it does drive financial exclusion’ it isn’t good for society as a whole. At the extreme, this would be akin to insurers only offering insurance to those most likely to not need it while leaving sectors of society with no safety net.
A further concern is how society – via regulation – chooses to delineate what information is private and what can be demanded.
To date the focus has been on the positive: the Australian treasurer described the new regime as a “game changer” which would allow new entrants and small lenders to better assess borrowing capacity and compete.
From an economy-wide perspective, this is evident. More, higher quality data does enhance the precision of credit scoring and pricing for risk. But the aggregate and the the individual are two different categories.
The burden for society is to ensure false precision doesn’t enter the system, increasing discrimination or exclusion. This is not simple, there is no algorithm, and as we have already seen with responsible lending requirements, it is not just a question of a change which is good in theory.
Andrew Cornell is managing editor at bluenotes