Network Capital Economics and Bureau van Dijk participated in a panel at the RegTech Accelerate Conference. The panel was chaired by the Commonwealth Bank, our focus was on applying technology and data to solve serious problems and create opportunity – financial stability, economic efficiency and improved governance.
Here are some themes from our work in this area:
Financial risk management
One of the big issues highlighted by the financial crisis was the connection between financial institutions. A combination of mathematics and computing power with appropriate data is starting to make these connections more transparent. Adequate data is key to unlocking this – regulatory initiatives are starting to make the data available to show linkages in financial market infrastructure. We can begin to see how markets and financial institutions are linked and what they look like under stress. We have the technology, and we are beginning to have the data, to understand what a failure like Lehman brothers looks like before it happens. We couldn’t do this previously.
Economic management
The other area we are excited about relates to the data becoming available from payment systems. If we think about the assumptions that underpin economic policy making, a lot of this is based on an assumption of economic efficiency – that markets incorporate close to perfect information. While we know this is not true, it has been an organising principle as the technology was not there to undertake economic management based on any other principle. Applying data science to payments and other new sources of rich economic data we can now begin to get a more realistic view of the economy.
This has a wide range of implications in the following areas:
Economic management – managing interest rates
Financial stability – connective tissue of the financial system
Payments – capital efficiency for banks
Prediction and causation
As far as AI and machine learning are concerned the question of data is very interesting for finance and economics. A very important question here regards correlation vs causation. Is what the data is telling us enough to change risk or policy decisions? Given the sometimes very immediate financial implications the answer to this is very important. We think this where data, human capital and technology all come together. You can have all the technology and data in the world however if the human capital is not right to understand the implications then it is of little value.
The big areas for exploration relate to:
Second and third order effects
Changes in correlation and
Warning indicators
Wicked problems
“A problem that is difficult to solve because of incomplete, contradictory and changing requirements that are often difficult to recognise”
“A problem whose social complexity means that it has no determinable stopping point”
Our view is that data gives us the opportunity to begin to solve some of these wicked problems. One of the issues with climate change is that the economic connections are not easily understood to allow us to work out what the cost could be. If we have the right data, for the insurance industry for instance, we can begin to assess this accurately. When is the insurance industry unable to cover certain types of risk? The flip side of this is what price would we have to charge today to make this insurable in a sustainable way?