Financial institutions are always looking to manage their risks better and reduce their exposure. From insurers looking for better risk pricing, traders managing their positions, to banks wanting to improve credit scores – they all are looking for better data and market intelligence to help make those decisions. Alternative data is one of the ways they do this
Many firms (over 53%) are now using some form of “alternative data”.
Alternative data has numerous definitions, but can be defined as non-traditional data, providing additional insights. Examples include – geolocation (foot traffic), social media, satellite data and web traffic. Alternative data has seen a massive increase in recent years, from $232 million spent in 2016 to over $1.7billion in 2020.
Why is alternative data used so much?
The reason for this expansion is three-fold:
Increased availability of alternative data
- There has been an exponential increase in the available data sources and a 450% increase in FTE in 5 years.
Increased ability to process and analyse the data
- Decreased costs via cloud computing fundamentals, and commoditization of machine learning.
Alternative data works
- The single biggest driver for the use of alternative data is that it works. It shows results and drives value for financial services.
The market for satellite data alone is one of the largest alternative data sources – and that is showing a steady 9%+ annual growth. By 2028 it is expected to have a market value of around $8 billion
Why satellite data?
Satellite data provides much more information than just photographs. Satellites are continually mapping and measuring the earth every day, providing data from weather predictions and high-resolution images to radar satellites that map the earth’s terrain with millimetre precision, and pollution detection.
These capabilities have a wide range of use – from predicting crops and monitoring oil extractions, to monitoring bridges for risk of collapse, and from detecting fires to predicting floods. All of these capabilities are incredibly valuable to traders and insurers – and the satellites have existed for some time. It’s only recently, with the advances in analytics, that this capability is being unlocked.
While analytics has increased the value of this data, another, more subtle reason is the ability to combine it with both traditional and other alternative data sources. The combination of different data sources is driving insights beyond any single data source.
Understanding the economic activities of countries and continents is critical for governments, global banks and institutional investors. However, knowing what the actual activity is before the end of the quarter has not been possible with traditional data.
Alternative data is providing more and more insights into economic activities – with transport data, foot traffic and geolocation data giving insights into how cities and countries are performing. Satellites are also providing insights into economic activity – from understanding the level of construction in China to monitoring the level of traffic (via emissions) across cities. Earth Observation data can see activity at mines, smelting plants, and oil wells.
Combing these alternative and traditional data sources can provide a detailed understanding of the economic activity, and global economic engines, well ahead of the standard quarterly reports.
Monitoring and predicting crops is crucial not just for farmers, but also for traders, banks and insurers. Wheat alone has an annual value of around $150 billion.
Several satellites have been built to monitor agriculture, to identify the size and health of crops, and to work well on the macro level. However, when dealing with small farms or looking at field-level data, the accuracy can drop.
Drones are now filling this gap as their costs are getting lower, and their capabilities are increasing. They are now equipped for hyperspectral imaging. While drones cannot monitor an entire country, they can now conduct hundreds of detailed surveys, collecting pinpoint data about crops health. This data, combined with smartphone apps and terrestrial sensors, enables highly accurate predictions on crops to be made at the field and national levels.
Managing risks for insurers has always been problematic, but climate change is making this even harder. The nature and number of extreme weather events like fires, floods, water scarcity, and crop growth are all changing and increasing – and the older models are struggling to keep up.
For this reason, insurers are increasingly using satellite data to better price their risks.
Natural disasters, past and present, can be monitored and understood – enabling insurers to understand the risks.
For example, NASA’s MODIS (Moderate Resolution Imagine Spectroradiometer) is built to monitor and track water and has a floodwater index. The European Space Agency (ESA) has Sentinel-1 which uses radar to map the earth’s surface daily, with millimetre accuracy whichcan detect changes in the height of the ground, rivers or thre sea, and help predict flood risks.
There are also systems built to monitor risks of fire and to detect pollution – all of which help insurers manage risks.
Satellites are not just being used by insurers to manage risks, but also to handle claims. When an event occurs, high-resolution imagery and radar data enable insurers to understand which assets were damaged, thereby allowing rapid support for the clients and preventing fraud.
Credit risk used to be calculated purely on traditional data sources. However, now a wide range of alternative data is available to calculate credit scores – from social media and geolocation to analysis of mobile phone use, and even text messages.
Even satellite data is now being used for credit scoring in the developing world to help manage the risks of loans to farmers. Satelite data alone is not useful for credit scoring, but when used in combination with traditional and alternative data, it can add real value.
Alternative data sources, from social media and web traffic, to satellite data and drones, are becoming increasingly important to financial services and are showing exponential growth – this is because it works. Alternative data provides new insights that traditional data cannot.