Financial institutions are demanding real-time analytics at their point of customer interactions. Why? Sophisticated analytics applied in real time and at the point of customer contact can deliver better customer experience as well as increase the financial results of the institution. For example:
- An insurance company can match different combinations of coverages and add-ons that can fit within a customer’s given constraints on price.
- A banker receiving a phone call can see on screen the updated Life Time Value (LTV) of the customer and hold the discussion accordingly.
For years, we have been advising our clients to connect their front-end, customer- facing systems with real-time pricing analytical capabilities, or at least lay the foundations to enable this capability in the near future.
According to a September 2016 report from the research firm Gartner, “Between 2016 and 2019, spending on real-time analytics will grow three times faster than spending on non-real-time analytics.” Getting the right real-time analytics at the right time can deliver great value. Yet, from my company’s standpoint, most of the questions we get about real-time pricing engines are from vendors of front-end systems and other stakeholders. They are approaching us to enable the integration of their systems with their client’s back-end pricing structures. These are providers of insurance rating engines and underwriting solutions, as well as providers of core systems, revenue management and onboarding systems.
It seems that the driver for this vendor interest is explicit demand from the banks and insurance companies themselves. These institutions are increasingly investing in off-line pricing analytics to improve performance, software that can be used to optimize pricing and decision making.
Why Is This Happening Now?
The rush to utilize real-time analytics in customer-facing processes and decisions is not unique to pricing nor to the financial services industries. It has been growing for several years as part of the broader big data and advanced analytics trends.
Banks and insurers are now raising real-time pricing analytics as a requirement from suppliers of pricing systems, and have been defining such capabilities, or connectivity to such systems, as must have “add-ons” in requests for proposals for core and front-end systems. For example, banks and insurers are demanding real-time analytics for systems that offer customer relationship management, underwriting, onboarding, rating and pricing. Of course, the level of demand for such pre-integration differs between countries and sub-industries, and it is highly influenced by regulatory requirements, however, in most segments we have noticed the pull in this direction.
Moving From Off-Line Analytics to Real-Time Analytics
Today, it is even easier for financial organizations to get their budgets to include expenses of adopting real-time analytics. Replacement of core systems is accelerating as more resources are available to buy and implement these systems. This is enabling companies to re-evaluate all related processes, including pricing. Coupled with the surge in analytical know-how and advances in analytics technologies, including real-time capabilities and faster optimization, real-time analytics is becoming more widely feasible.
But the underlying benefits of real-time analytics is what is really driving the demand. Financial institutions realize that connecting their offline analytics to the customer facing process brings uplift not only in numbers but in the customer experience itself. According to a December 2016 report from the research firm Gartner, real-time analytics at firms is facilitating faster, more accurate decisions, especially for complex digital business initiatives such as online and mobile banking. Below are some of the benefits we have seen customers enjoying after migrating to real-time analytics:
- The ability to react quickly to aggressive competition, especially given the rise of direct channels and players.
- Improvement in the efficiency of price execution processes as well as a reduction in time-to-market of new pricing strategies.
- Improvement in customer-facing decisions. Once a company has a system in place to analyze real-time data, their ability to understand the customer significantly increases, translating into improvement in key performance indicators such as annual increases in pricing, as well as being able to anticipate and meet customer expectations.
Is Real-Time Analytics on Your Roadmap for 2018 or Beyond?
Regardless of what the reasons might be, we have been receiving more and stronger indications that real-time analytics is catching on in the insurance and banking markets in which we operate. Offline advanced analytics are already mainstream investments in financial organizations, and the focus seems to be progressing very practically to the next logical extension of real-time application of these analytics. Implementing real- time analytics that is connected to customer-facing systems requires forethought and planning. Even if this is something you are considering doing three years from now, the planning should start today.
To discuss how these topics impact your business, feel free to contact us at firstname.lastname@example.org.