Throughout these years of working with insurance companies to leverage technologies such as like data streaming and orchestration, rules authoring and automation, as well as customer communications, MLx (Machine Learning executor), optimization, and others, I've noticed a trend. Insurers are looking for ways to proactively provide offers and secure solutions to insurance customers who want new forms of protection.
The world since COVID-19 — exacerbated by increasing uncertainties such as inflation, war, and climate change — is anything but secure. We are all, it seems, wrapped up in new anxieties about our families and loved ones. Many families are, for the first time, discussing the creation of emergency plans. This represents both an opportunity and a threat for insurers: How can we offer the best product at the best price and reach our intended customers exactly when the need arises?
Four Key Components of Insurance Systems Today
Insurers need to decide online, in real-time, and connect internal systems on the fly. More people than ever before are looking for life insurance. Products that can provide, for example, a back-up, in case of emergency, for college tuition or the unexpected disability are trending. Insurers that can identify these trends and quickly communicate offers through digital channels will be the ones to win new customers and solidify customer loyalty. Increasingly critical to success: online channels with 3rd-party data integration.
Many companies have invested in machine learning and AI, but not online and in real-time. These businesses can create models but it takes a long time to deploy them. Analytic models are the brains of all smart decision processes, and this brain must work fast. Historical offline modes are no longer acceptable. Even if the model can't learn in real time, the company can still succeed if the model can be deployed and provide responses in real-time.
Insurers should be able to classify clients and act instantly, providing a real-time response wherever and however a customer requires a response. Omnichannel responsiveness — like online, real-time decisions — is no longer a nice-to-have capability.
Lastly, for the most empowering customer interaction to occur, the insurer's systems should be able to generate a customer 360-degree view: a holistic picture of the customer’s historic engagements and insurance purchases. A customer 360-degree view can only be accomplished with the development of custom profiles. Every customer interaction should be captured as an event, and every event should update the profile in place. This profile is a set of characteristics easily accessed on the fly when a decision is needed.
To sum up, insurers need to harness:
- Decisions in real time
- Analytics in real time
- Interactive (two-way) communication in real time and omnichannel
- A complete view of the customer engagements in real time
With all those capabilities in place, insurers can offer new cutting-edge services like embedded insurance (insuring an Uber trip or an AirBNB rental, for instance). These new offerings, however, require integration of internal data along with third-party data, profiles, real-time or streaming data, and perhaps certifying a contract in a Blockchain for security and audit purposes.
One increasingly critical source of data is the IoT (the internet of things) data. The ability to know who, for example, is driving a car (is it the insured or is it a friend?) at any moment may appear irrelevant at first glance, but could have significant bearing on a policy offering going forward. In addition, it could prove very differentiated if, for example, the insurer could apply good driving discounts in real time, while also lowering inherent risks if the car is driven most of the time by a driver that maintains the limit speed, doesn't brake suddenly, and always uses a turn signal.
Fighting Insurance Fraud
One thing that also captures the imagination is leveraging these technologies to detect and treat fraud. For an insurance company, the ability to correlate additional third-party and often non-obvious data is essential.
For example, if the policyholder of a car claim has data that may connect him or his wife with the repair shop owner – who therefor charges more for the repair after a collision – can indicate a fraud. Sometimes the insurer can't know the repair cost in advance, and little extras can save a lot if we can issue a red flag saying that the repair shop owner is his brother-in-law. In health insurance, abuse is also a relevant topic when correlating such extra data, and the ability to identify such cases saves millions, and that's what I saw, for example, in an insurer who provided us with their past database, already analyzed by them. We found many cases they overlooked and saved millions for the company.
In health insurance, abuse is also prevalent but not obvious unless correlated with third-party data. The ability to correlate data to quickly identify fraud can save millions of dollars. Over the last few years I’ve worked directly with insurers who provided us with their customer database. This data, while already audited extensively by the customer, was not amended by additional and relevant policyholder data. Once this was done, we found many cases they overlooked which resulted in the Insurer saving millions in previously undetected fraud. One thing we know for certain, and which is borne out by our recent consumer surveys, is that insurance fraud is a real thing.
Of course, all business in Insurance begins with the underwriting process. If the insurer can capture the “right” clients (or the best clients), they can avoid most future problems. But great underwriting is an art, so the more Insurers we can help, both big and small, the more we improve our own processes and offerings, and subsequently make FICO Platform the best-in-class decision platform for all markets.
How FICO Can Help You Optimize and Automate for Greater Profitability
- Read the report Digital Insurance Special Report: Hastening the Speed of Change.
- Read the industry report FICO Enterprise Intelligence Network for Insurance.
- Accelerating The March Towards Digitization in the Insurance Industry: Part I.
- Accelerating The March Towards Digitization in the Insurance Industry: Part II.