This is a sponsored post by Tim FitzGerald, EMEA Financial Services Sales Manager, InterSystems
The use of analytics within the financial services sector has evolved over the years, with some suggesting that it could be about to evolve even further, moving from a landscape where decisions are “data-dictated”, rather than “data-informed.”
There is a distinct difference between the two concepts and the role, or lack of, that humans play in each scenario. In the case of data-informed, humans remain in the loop to make decisions and take the appropriate actions based on data and analytics, whereas data-dictated refers to applications executing programmatic actions automatically in response to some stimulus or event.
So, are financial services organisations really at a point today where human insight is no longer a vital requirement of the decision-making process and are there really just two types of data-related decision-making at play? In short, no. But it’s not completely black and white, as discussed in a recent Economist Intelligence webinar. Instead of just two options, today’s financial services firms typically implement four different categories of analytics: panoramic, predictive, prescriptive, and programmatic. Depending on the use case and the organisation, each of these types of analytics provide businesses with immense value.
Panoramic, predictive, prescriptive, and programmatic
Firstly, panoramic is about providing the business with a real time, accurate, expansive view of what’s happening inside and even outside the organization. For financial services, that might be the real-time liquidity across an entire firm.
Predictive, on the other hand, calculates the probability that events are likely to occur. For example, what’s the probability the Bank of England will cut interest rates if inflation pressures ease, as has been mooted, and how will this impact the firm’s positions?
Prescriptive analytics analyzes data to suggest the most appropriate actions to take, based on what is likely to occur, or what is already happening. This type of analytics would allow an investment bank for example to continuously predict the probability that their total market exposure will breach their risk utilization limits. With the right data and analytics platform in place, firms can also obtain prescriptive guidance that presents various options they can take to prevent or eliminate a breach, with the expected outcomes and trade-offs associated with each option.
These insights allow risk managers, who tend to have extensive experience in handling these kinds of situations, to make decisions based on their experiences, and guided by data-driven prescriptive analytics. For instance, it can help them to determine whether to initiate a hedge or unwind some positions. Prescriptive analytics therefore ensures experienced experts remain in the loop and at the heart of decision-making, rather than actions happening programmatically.
The final of the four Ps is about executing real time programmatic actions based on predictive and prescriptive analytics. Often, programmatic analytics are employed when there’s no time for human intervention, for cases like fraud prevention, pre-trade analytics, trading, and customer next-best action. Programmatic actions are also deployed in use cases when there’s simply no need for a human to be in the loop, which allows the organization to streamline operations and improve productivity.
Pragmatic application of the four Ps
Consequently, rather than moving away from a data-informed (human in the loop) to data-dictated (no human in the loop) state, the financial services sector is instead opting for the pragmatic application of any or all of these four Ps of analytics.
This use of analytics is providing firms with the capabilities needed to gain a 360-degree view of enterprise data, delivering a wide range of benefits to the business including better compliance, increased revenue generation, and improved decision support. When financial business leaders are empowered by real-time data and analytics, they are able to make decisions based on accurate and current data, not data that is weeks old, thereby eliminating errors and missed business opportunities.
Additionally, by incorporating advanced analytics into real-time processes flows, dashboards, and reporting, businesses can obtain better insights to guide decision-making, helping to understand what happened, why it happened, and what is likely to happen.
Armed with a current, trusted, and comprehensive view of what’s happening in the moment ensures financial services firms are prepared for events and disruptions that are likely to occur, can manage events and disruptions faster as they arise, and are in the best position to take advantage of new opportunities as they present themselves.
Photo by David Pisnoy on Unsplash