The insurance industry isn’t known for taking risks, in fact, they are the exact opposite.
When it comes to “innovation” spending, some insurance companies are a little sheepish to invest money into projects that don’t have a predictable outcome.
Hence, we are going to present a case for a fairly novel idea: Enterprise insurance innovation projects should be funded with money saved by the implementation of automation within the organization.
More companies are seeing predictable savings from automation methods like Robotic Process Automation (RPA), Machine Learning and direct integration between platforms.
Cognitive Intelligence gives insurers the tools to automate non-routine tasks that require soft skills such as creativity, problem solving and intuition. Insurers are looking to heavily invest in this type of automation.
Long story short, automation is working well. Almost too well.
We’ve worked with many Insurance companies who saved millions of dollars by implementing automation.
In the rest of this article, I’m going to lay out how insurance companies should be approaching innovation,
and it all starts with, of course, automation.
Here are our thoughts on insurance automation.
Section 1 – Business case: Innovation projects should be self-funding.
Section 2 – The 4 stages of effective insurance automation.
Section 3 – A framework for investing in innovation.
Digital has changed the Insurance industry forever. That’s hardly news. The changing digital landscape has provided a major disruption for the insurance industry. If you don’t invest in digital innovation, you may find yourself at a slower growth rate than the rest of the industry.
This presents a conundrum for many insurance companies who are structured to invest in predictable costs. Investing in innovation isn’t necessarily predictable, so locating the funds to invest in an unknown outcome can be very difficult. As we alluded to in the introduction, we think there is a good middle-ground to this problem. Investing in automation has a predictable cost savings structure. Automation not only makes insurance companies more efficient, but allows them to take more risks with innovation projects.
Here’s a pretty significant statistic about the impact of automation:
According to PwC, more Americans than any other country will have their jobs up for grabs by the increasing demands of innovation as more Robotic Process Automation tools become commonplace. Take the statistic for what it’s worth, but it’s a good sign that more companies are realizing automation is allowing them to do more with less, and recognizing the real savings made by implementing core business functions. Automation isn’t just a one-time cost savings. It’s recognized year after year, and the technology gets smarter all the time. Most importantly, each automation project can predict the savings for each successful implementation.
Keep in mind that RPA tools can be implemented to not only expedite previously manual processes, but also take the industry in new directions that weren’t possible until recently. Back to the business case: The risk-free way to innovate in insurance companies: Let the savings from your automation projects fund your innovation projects. So why choose to automate a process that already heavily relies on algorithms and formulaic procedures? The money saved will be used to fund new projects, which in turn, will lead to even more innovation. On the level of pure business model, it’s an ingenious strategy.
Mainly because it’s self-funding.
Dollars that used to be spent on paying for outdated processes and inefficient resources, can now be used to make the entire model even more efficient. The money saved will be reinvested into other aspects of the business, which will allow for more research and push new boundaries in exploring just how far automated processing can take the industry.
Now, insurance companies can continue to do what they’ve always done best, even more effectively: hedge risk.
So, in conclusion, if you’re a risk-averse company, then consider investing heavily in automation and using those savings to fund innovation projects.
Automation occurring in the insurance industry operates on four primary levels, think of these as being rolled out in iterative stages. The first two stages are processes that can be rolled out almost immediately. The latter two will take some time for adaptation to catch on, based on predictions of how the industry is starting to shift.
1. The first stage is what’s assumed to be obvious – standard processes that make sense for companies to
implement right away.
2. In the second stage we begin to see where the role of customer automation comes into play. This is a huge move in the right direction for companies looking to have an easier, streamlined approach to dealing with customers and having them police themselves.
3. Later on, the tertiary stage brings to light fundamental changes in how insurance will be purchased, namely in conjunction with other ancillary products – such as buying travel insurance while simultaneously booking accommodations.
4. Finally, the fourth stage is representative of the “wild west” of where Artificial Intelligence and automation can take the insurance industry and the yet-to-be discovered offshoots of where these new approaches can lead the industry as a whole.
This automation stage can save the most $$$.
One of the first things that comes to mind when thinking about automating insurance is the simple fact that a lot of the current procedures lend themselves to being automated already. In fact, there are many areas in a firm where manual effort is still prevalent, but could soon become an easy task for RPA tools to take over. Chief among these easy initial delegations are simple financial processes like invoice automation, which doesn’t require much human oversight and can easily be delegated. Deloitte has a great report on the impact of robotic automation. A few graphs stood out to me, including which functions can be highly automated with little to no manual intervention:
These functions, once automated, will provide you with better results, and more efficient organization. Next, RPA tools could move on to tackle more complex business operations such as KYC processes and managing claims procedures, which would make for a better use of resources.
A lot of the fascination with insurance becoming more agile is the fact that this will intrinsically lead to more innovation. More innovation means that Machine Learning can replace the current temporary fix that RPA tools are able to provide, but more on that in Stages 3 and 4.
The even bigger sales pitch for automation in insurance lies in its ability to help on the customer side of the
Grocery stores & McDonald’s aren’t the only businesses that can implement self-service systems. Handling customer inquiries / issues currently accounts for a large majority of employee interactions, especially when it comes to call center interactions.
This will be accomplished by automating the experience for customers by integrating their customer information through online platforms, rather than through a call center employee who would have to interact with the customer directly and pull information from a file. This type of revamped service offering falls into the category of Customer Self-Service, which eliminates the need for an intermediary call service employee. Additionally, improved automation could also handle other crossover components of Customer Self-Service such as: Policy Administration, Premium Payments, Renewals, Claims Initiation, and several more as the technology becomes available.
Even more important in the quest to add value in a newly revitalized industry is providing an easier experience for the purchase of insurance. Insurance sales are changing, primarily in the way that people are able to buy insurance. Rather than buying insurance independently, the future will hold a space for a synergistic transaction between people buying insurance and the items they are purchasing that insurance for, at the same time in a single location. Instead of buying travel insurance and then buying plane tickets in two separate transactions, for example, adding an API to insurers will allow quick on-the-spot convenience. We believe this will become the norm and insurers have to adapt to this. There will also be first-mover advantages in this space and insurers who can create their own APIs for their business will see tremendous gain in building ecosystems that create a nexus of opportunity and innovation for continued success.
Today, using the advances in Optical Character Recognition and Machine Learning, most data-heavy processes like underwriting, fraud detection, and claims processing can be automated to a large extent. The ultimate aim of this type of automated decision making is to get to straight-through processing of 99% for underwriting and claims processing. One of the most interesting debates that has come out of this conversation is about the usage of rule engines. Rule engines are widely prevalent in the industry, but can be seen to be at odds with machine learning.
However, at RapidValue we don’t believe in a strictly either-or approach. Instead, we’ve found that it’s a combination of these two processes that will give the best results in the foreseeable future. Whereas in the long term the hope is that our approach will move towards a fully cognitive system. As a first step though, all the processes that were automated using RPA in stage 1 will have to be disrupted again once the use of Machine Learning comes into play. Machine Learning will connect the dots for a lot of these processes and eliminate some RPA related processes.
The fourth and final stage ushers in a new frontier. This is the domain of true AI where new products and business lines will be developed by AI-enabled algorithms.
How will this be possible?
AI will begin mining patterns in data, which is currently being done by human-assisted analysts today. Furthermore, AI will go on to not only interpret the patterns mined in these mountains of data, but will be able to write its own APIs that will be able to assess risk all on their own. This will create several new changes in the insurance industry, and is one of the primary reasons why automation is going to be so pivotal over the next few years.
As technology advances, specifically machine learning and artificial intelligence, there will be a few future business cases that can make an impact. Now, these are still fairly far out and won’t provide immediate return, but it’s good to think of what will be impactful in the future.
However, the most exciting changes will be the ability for true AI to introduce new products online with very limited human intervention. As data is being interpreted and the AI-created APIs are able to assess risk, AI will be able to once again find patterns in this information and introduce various new products that will help to adapt to the trends found in the data. This is something completely revolutionary and will be groundbreaking. However, at RapidValue our prediction is that this will only go as far as regulations will allow, as technology will not be the bottleneck. However, keep in mind that the technology available to do this is still a decade or so away and insurers should start to adapt more forward-thinking strategies now in order to stay ahead of the curve.
You invested in automation and have realized the savings. Great!
Now, the real question is what should you do with that money, and more pointedly, where are the wisest places to reinvest it? The first thing to realize is that automation is causing the employment structure of companies to change dramatically.
Take a look at this future state graphic from Deloitte.
Digital is the name of the game in 2018 and beyond, and is the best use of your reinvestments. If you aren’t putting your resources towards a digital strategy, then you aren’t focusing on the right areas, and you won’t survive the next wave of digital innovation.
Specifically, as it relates to insurance, digital-led emerging markets are going to be the most profitable as evidenced by the graph above which indicates that nearly 3 billion mobile users are either searching or paying for their insurance plans on their smartphones.
Here are two steps to include when creating a digital-first strategy.
This includes business and IT processes across the organization. Even if you don’t believe the process can be automated, an extensive inventory is recommended. As mentioned previously, cognitive intelligence paired with RPA has the ability to automate non-routine tasks that require more critical analysis and deep thinking.
The most routine and labor-intensive activities should be placed at the top of the list because these processes offer the most cost savings.
Once you identify and prioritize the list of automations, our recommendation is to build the tools that will automate each identified activity. We recommend grouping the execution per business / IT area, which will simplify the execution and signify a cohesive approach from Business & IT.
Speed to market is the limiting factor for so many companies (incumbents and newer companies alike). Being able to ship and then relaunch successive iterations based on real customer feedback is the key to building longevity within the industry. Rather than focus on getting it perfect out of the gate, get it off the ground first and make several iterations based on real feedback in order to test the needs of rapidly changing markets.
Automation is changing the way business is done in every sector of the economy. Intelligent automation systems are able to detect and produce vast amounts of information. They can automate entire processes or workflows and at the same time learn and adapt as they go. Insurance automation and innovation is already helping organizations to transcend conventional performance so that they can achieve unprecedented levels of efficiency and quality.
Every insurance company, big or small, can now fund innovation through savings made by automation projects.