Tag Archives: build or buy

Conundrum Facing Commercial Insurance

Artificial intelligence (AI) seemingly has been discussed everywhere over the last few years, and now it’s made its way into the commercial insurance industry. Organizations are using AI and machine learning for everything from streamlining operations to offering more personalized care and better customer service. There is an increasing sense of urgency about getting started on the AI journey. The question is how. Do they develop a custom solution in-house or purchase a third-party solution already on the market?

At first blush, the temptation to build can be strong — after all, you can design exactly what you want for your specific environment. In reality, it’s hard to accurately weigh the perceived benefits of a highly customized internal platform against the time and cost requirements compared with purchasing a tested, third-party solution. To help figure out the best course of action for your organization, I’d like to share some criteria that may guide you.

Staffing

Developing a quality AI-based platform that effectively addresses specific needs requires a dedicated team. To build this team in-house, your organization will need to hire more than just data scientists. Full deployment of a new solution requires product managers, software engineers, data engineers, data scientists, operational experts to develop process and operational workflows, staff to integrate data models into operations, people to manage onboarding and training of the employees who will ultimately use the solution and staff who can quantify value. It’s also important to have all these members operate as one unified team instead of spanning various organizational groups that are not 100% aligned.

For some organizations, this may not be a big deal. For others, the process of recruiting, hiring, training, managing and scaling down staff is one of the worst, and often most prohibitive, parts of embarking on the AI journey. If it’s too daunting to put together a team with the necessary skills, opting for a third-party solution that already has this figured out could be the way to go.

See also: How to Use AI in Commercial Lines  

Data

What types and how much data does your organization currently pull? If you can glean industry-leading insights and possess a treasure trove of information internally, you may want to keep it under lock and key, developing new ways to access and analyze it in-house. But this is usually the exception rather than the rule due to the complexities involved in the insurance industry. Even very large organizations with a high number of claims may lack a preponderance of data on a particular feature, injury or litigation scenario. An external vendor, however, could have data aggregated more broadly to cover all situations. External AI vendors draw on a wealth of anonymized and aggregated data from both public and private sources. This means data models can be trained more quickly and accurately.

Customization

This is an area where in-house development wins. Your organization can build something from the ground up completely specific to your needs at every turn. If you opt for a third-party solution, there are some constraints that you have to adhere to. However, it’s important to think of customization not just at a point in time but also across the entire life of the AI solution. While you might be able to build exactly what you want right now, if you don’t have continued focus, the solution will become obsolete rapidly. This brings us to the next point.

Continued Focus

Just because an AI-based solution is created and implemented doesn’t mean the work is done. It is, in fact, just the start of a journey that requires a dedicated team focused obsessively on the problem. These solutions need to evolve fast, or they will rapidly get irrelevant. Models need to refresh. And platforms and software need to be updated, maintained and optimized. When planning for this in-house, factor in both the staff and time involved to refresh models, fix bugs or add fields or features. If you go the third-party route, maintenance and improvements are typically included in the cost or subscription. If you feel uncomfortable dedicating an internal team to the project on a continuing basis, it might be better to go to a third party.

Security

When it comes to security, in-house platforms have an edge because data is not shared outside of the organization. While you still have to ensure that your networks, systems and endpoints are carefully managed, you are in control. While evaluating third-party vendors, it’s important to check their security credentials and processes to handle data. They need to be as good as your internal processes (if not better) with clear evidence of tight controls through certifications like SOC 2 Type II, HIPAA and HITRUST.

Time to Capture Value

There is a race going on to bring down cost structures dramatically. This is driven by the premium pressures in the market. The primary way to improve combined ratios is by pushing on operational efficiencies. Time matters. It’ll help to think hard about how you could capture value quickly. Ask yourself how much time it will take to:

  • Assemble the team
  • Receive data and set up a data pipeline
  • Design the solution
  • Build the solution and create a testing infrastructure
  • Operationalize the solution
  • Design and implement a way to track value
  • Continuously iterate on the solution

Cost

Your ultimate decision may come down to some basic math. Once you’ve narrowed the list of potential outside vendors and receive their quotes — which typically include a continuing fee that covers hosting, support, performance and additional improvements — you can compare them with what you estimate for the total of building a solution internally. In calculating this estimate, factor in staffing, training, infrastructure and hosting costs as well as maintenance and continuing improvements, as previously discussed.

See also: Leveraging AI in Commercial Insurance  

I hope these guidelines assist you in making the decision on how to best bring AI into your organization. There are pros and cons to both building and buying. The trick is to prioritize your needs and what is actually feasible and realistic for your company to ensure that the result more than justifies the means to get there.

To Build, or Not to Build…?

“To be, or not to be, that is the question:
Whether ’tis nobler in the mind to suffer
The slings and arrows of outrageous fortune,
Or to take arms against a sea of troubles
And by opposing end them. To die—to sleep,
No more; and by a sleep to say we end
The heartache and the thousand natural shocks
That flesh is heir to: ’tis a consummation
Devoutly to be wish’d. To die, to sleep….” ~Hamlet

I’m not going to paste the entire Hamlet speech here, but you can see that he was going through a very tough decision-making process about a form of death he wanted to pursue.

Technology decisions being made in organizations should also be deemed as do-or-die if you want to continue to exist. I know: very drastic. But let’s face it, competition is fierce, startups are popping up ready to grab your market share and the organizations that survive look at expenditures from a strategic viewpoint.

From an application development lens, questions include: Should we build, whether in-house or outsource, or should we buy and integrate?

See also: How Insurtech Helps Build Trust  

The ugly truth: Developers LOVE to build. The maker inside of us wants to create. Integration projects aren’t deemed as fun. I worked with an organization where the IT department predominantly built software solutions. Need a scheduling tool? “I can build this.” Need a workflow solution? “I got this.” Developers would make any excuse known to mankind to devalue other products in the marketplace.

Another ugly truth. Build projects are EXPENSIVE and take forever even if you outsource them. Why would you build a scheduling tool? There are thousands of such tools. The same is true with workflow.

You may be thinking: Such problems could never happen! Why would someone sign off on the project if such problems were ahead?

If you don’t have the right leadership — your technology reports to a non-technologist or you don’t have the right project oversight — your organization might very well make this kind of mistake.

Technology dollars are precious, so why spend your time, resources and capital on projects that don’t propel your organization forward. Why spend the money building a scheduling tool or workflow solution? Why not take the opportunity to integrate with someone who has already built the solution?

Here is the challenge I would offer you if you sit in project prioritization or new initiatives sessions, regardless of your department and role: Has due diligence occurred to look at software solutions that may solve the need?

If the answer is no, figure out a way to start the process, or you will be in the do-or-die situation.

If the answer is yes, vet various solutions. This can’t be left to IT only. The vetting must be done by a mixture of IT and the business, with equal decision-making power. Vet the various solution providers and find out how you can integrate while building the other pieces.

Ask yourself: As an organization, what is your mission? Are you in the business of developing software or using software to serve the mission? Why would a life insurance company want to develop its own workflow tool, its own policy admin systems or its own claims systems? There are vendors whose sole purpose is to make your organization run better.

See also: When It’s Better to Build In-House  

Use your brightest IT talent in innovation, not in building solutions that exist in the marketplace. Figure out how to transform your organization using best-in-class technology. Integrate with solution providers and startups. Build what others cannot do, and innovate on solutions to beat the competition.

“To be, or not to be, that is the question….”

When It’s Better to Build In-House

Exploring the initial steps of any development includes the question: “Stay in or go out?” which translates to, do we build in-house or can we use off-the-shelf applications? Advantages of using applications already developed are self-evident: They save time and resources spent on recreating common code that similar platforms need. The frustrating downside, though, is the need to often modify the off-the-shelf technology so extensively for passable integration that time and resources are ultimately not saved and the results are sub-par.

Incumbent carriers are struggling to deal with legacy-based policy management systems that have been in place since the 1980s. One of the difficulties with off-the-shelf solutions is that carriers can’t migrate all the data from their legacy platforms into a cloud-based platform. Even if they come up with a potentially relevant solution, there is still a significant risk of disrupting their customer portfolio.

This was the dilemma facing us at Hippo Insurance as we discussed what a system that effortlessly supports home insurance agents and consumers would look like. The highly regulated, slow-moving and traditional home insurance industry seemed poised to benefit from widely applicable innovations and rapidly changing technology, motivating me and our team at Hippo to see about making such a system a reality.

When our director of software architecture, Adrian Olariu, joined Hippo to help build out the company’s home insurance tech platform, we analyzed what was currently available and looked for an off-the-shelf service we could mold into something we would use for years to come. After trying to work within the legacy systems of the industry, we discovered outdated functionality and limited capabilities that not only made it difficult for insurance carriers to maintain cost-effective and compliant policies, but also made it difficult for us to provide a positive user experience for carriers and customers alike.

So, we decided to build a policy management system in-house at Hippo, starting from the beginning. This undertaking, while risky, seemed to be the best option to create a streamlined offering we knew the system – and those using it – needed. Our goal was to launch an initial working version in three months and a fully functioning system in six months.

See also: Trends in Policy Admin System Replacement  

The complexity of the system we were building continued to reveal itself yet further reinforced our decision to build in-house. We successfully developed patent-pending technology that balances regulatory compliance with a user-friendly experience that saves time and money for agents, underwriters and support staff, ultimately passing along those savings to the customer. Our focus included:

  • Single-system functionality. We created a single system that provides a seamless experience for the customer, agent and developer. It is one of Hippo’s most important features and means that all processes are handled within the one platform through the use of microservices. We included everything from document generation and storage to quotes and underwriting, billing and servicing to reporting and agent commissions. We designed it to streamline the management process, provide expansion capabilities and significantly reduce costs. Traditional policy management systems are built in fragments and pieced together. Because they operate independently from one another, they lack connection, causing additional cost, time, continued maintenance and potential for error.
  • Automated. Within the single-system functionality, we also built functionality to automate potential change-in-policy notices, such as cancellations, non-renewals, non-payments and reinstatements. Communications are automatically triggered to send to the customer via e-mail as soon as they are processed (or mailed, when required by law). This allows customers more time to respond to any required actions and developers more time to focus on other projects. Legacy systems only generate hard copies of notices, meaning additional lag time that causes a delay in alerting customers to any actions necessary. Simultaneously, automation benefits agents who no longer need to pay attention to or manage repetitive and manual processes, freeing their time to attend to customers. This has already showcased strong value in our organization, helping us drive average NPS scores upwards of 78, and 85% five-star reviews.
  • Cloud-based. The Hippo team also made the decision to make this a cloud-based system. We recognized that a cloud-based system allows for the kind of scalability we want through unlimited expansion and storage, enhanced data encryption (which protects consumer data), multiple redundancy backups and accessibility from any internet-connected device. Compare these benefits with the traditional server-based systems, which are prone to lost data, lack efficient expansion capabilities and limit remote user access.

We also built and implemented key pieces of technology such as:

  • Out-of-sequence endorsement processing, which means the system allows endorsements to be automatically updated regardless of when they’re processed (no longer needing manual processing by dedicated engineers)
  • Real-time document generation once a transaction is completed
  • Automated future-update processing (versus agents and underwriters remembering to manually process the required change at a future date)
  • Pre-programmed renewal periods to match the timeline set by the Department of Insurance, helping reduce compliance violations and regulatory fines.

See also: Innovation: ‘Where Do We Start?’ 

Hippo has been able to expand into eight states in eight months with multiple products, including homeowners and condominium insurance. Building our system in-house has also allowed us to partner with large insurance carriers that lack the capabilities this system provides, allowing them to benefit from one of the most advanced policy management systems in the industry.