How does one go about preventing credit frauds, ensuring the reliability of someone that one proposes to give a loan to, or, more generally, taking safer decisions when it comes to something as tricky as financial risk management?
This isn’t a new question, of course – it’s been around as long as people have borrowed and bartered, and over the ages the finance industry has come up with several methods of trying to address this concern. The latest has been to take the approach of statistical modelling, and one has to admit, this has helped matters tremendously. Banks are able to paint a more detailed picture of what their overall risk profile is, and avoid seriously risky situations.
As of 2015 however, over a dozen European banks have moved away from statistical modelling to determine financial risk. Why would they give up such a proven, effective method of managing risk? What’s wrong with them?
Not much, apparently – some of these banks have increased sales by 10% (with a lower risk profile), while others have seen a 20% reduction in churn and capital expenditure. Their magic trick?
Machine learning. Identified by Gartner and McKinsey, among several others, as one of the top ten technology trends for this year, this new approach to financial risk management has already helped several financial institutions across the world reduce their losses and take better business decisions.
With hurdles such as access to massive computing power now a thing of the future, organisations like IDfy have been able to develop algorithms and technology that can sift through tremendous volumes of historical data to deliver predictions about the likely outcome in a situation at hand. Not only that, these algorithms and technology continue to learn as they work, refining themselves and fine-tuning the accuracy of their predictions with every piece of data that’s thrown at them.
Combined with our proven expertise in background verification and processes optimised to ensure the most efficient and accurate people information processes, our machine learning-based technologies can be used in several different ways to minimise financial risk: micro-targeting can help identify the risk of credit default, so one can take a decision on whether or not to extend a loan or an insurance policy to someone; more broad-based analyses can help determine what geographical area one should invest in so as to obtain best yields; and what’s more, one can even predict the probability of fraud in a particular transaction!
Better informed is better prepared – and better preparation leads to better decisions. With IDfy’s combination of the latest computational technology and super-sharp processes, you have all the information, preparation, and insight you need to take decisions that slash financial risk to a minimum!
We’re excited about these new developments, and we’re willing to bet you are too! With each advancement in these new technologies, we progress on our path of making people decisions safer, simpler, and easier, and of providing even better, more accurate decisioning tools for our customers!