Dais

Who They Serve

Dais offers quote/rate/bind, policy management, rating as a service, effortless connectivity, automation, broker + customer portals, and self-service product management—all in a configurable, no code, event-based system—for MGAs, MGUs, and agencies.

Dais also offers competitive pricing without, in our opinion, sacrificing quality or features. We've seen several teams put Dais in their shortlist for this reason: a rich feature set with a price that doesn't make them spit out their coffee.

A lot of the gems of Dais's functionality and design are found in the little things—same as with most systems, really—so we encourage you to read on.

What They Do

Quote/Rate/Bind

We've known teams to use Dais purely for its quote/rate/bind functionality. You can set up an insurance product from scratch inside a week or two, upload your logo, set a few colors, and with very little difficulty you have a web-based application flow to share with customers. (Dais calls these application flows Storefronts.) You might say it's similar to Typeform for insurance, if Typeform had a rating engine, generated forms and docs, and integrated with the back end of your choice.

To be clear, you don't have to use Dais D2C, and you don't have to use straight-through processing (fully automated underwriting). We've worked with MGAs that sell every policy through brokers and trust every submission to the discretion of an experienced underwriter. And we've had clients whose underwriting and rating is far more turn-key. Both have been at home with Dais's quote/rate/bind flows.

Policy Administration and Customer Portal

The vast majority of Dais customers use the platform not just for quote/rate/bind, but for the whole range of policy administration, including endorsements, billing, cancellation, and renewal, along with all the rules and rates, forms and document generation, carrier reporting, and billing for each one. In other words, Dais is a full-featured policy administration solution.

This is all available in Dais's authenticated portal for agents, brokers, and customer service reps—branded their Copilot experience. You can also send customers magic links to customized question flows to handle their policy admin needs. Or Dais offers a D2C policyholder portal behind a login, where insureds can see applications, quotes, and policies, apply for new policies, request certificates of insurance, submit a claim (FNOL), or kick off an endorsement flow. At time of writing, in September 2023, the policyholder portal was still relatively new. But it shows promise for insureds who want a unified digital experience.

Self-Service Product Management

Product Configuration

Like many of the policy software platforms we review, Dais is also designed to empower you, the insurtech team, to create, maintain, and manage your own insurance products.

A no-code product builder offers an intuitive interface for laying out the question set associated with each product. You write the wording of each question and give it a unique “question ID.” You determine the question type (true/false, multiple choice, numerical, free response, etc), set any dynamic logic for when it should and shouldn't be displayed, and add help-text if you like. The product builder supports question groups, complex schedules, and more, all in the same straightforward user experience.

The platform aims to use familiar tools whenever possible. You can plug in your own Excel rater for your product, for example, and plug in your own forms and document templates from PDFs or Word docs. We all know Word and Excel are still the lingua franca of the insurance world, and even those of us who use Google Drive extensively are able to import and export those files, minus macros and pivot tables of course.

ISO and Carrier Integrations

Of course many of us use variations on standard ISO products, for applicable lines of business. For this, Dais offers full ISO integration. You can use an ISO product as is, and it will have all the rules, rates, forms, and documents ready to go. More commonly, you can create your own variation on an ISO product. Dais allows you to store only your variations as a separate layer, so when there are changes to the underlying product they flow through naturally. All of this is a familiar pattern; see our write-up on bureau integrations for more. But the process is quite fast for Dais; you can clone a standard ISO product and have it ready to go in literally under a minute.

Instead of using an ISO rater, or building your own Excel rater from scratch, your business model might be such that you request rates from one or more carriers. Dais also supports this path, in at least two ways:

• You can set up a direct, automated integration with the carrier, if the carrier supports it. When it comes time for rating, Dais will call that carrier and return pricing information to the user.
• Some carriers are not set up for that kind of integration, for any number of reasons. In this case Dais can set up PDF templates, filled automatically from the insured's application details. This can be emailed automatically to the carrier, or you can have a more personal touch, and have your broker send it to them with a note.

Carrier Reporting and Portfolio Analysis

Whatever your product and whatever your business model, you will also need reporting: carrier reporting, such as bordereaux, and operational reporting, such as new business, renewals, retention, and book of business mix. In many cases it's helpful if your business folks can do this without requiring dedicated data and analytics professionals. Dais has this handled as well, in the form of Excel reports you can configure and schedule yourself. You build a report in a no-code configuration screen by mapping product fields and measurements (counts, sums, etc.) to Excel columns. Reports can be triggered by specific events or run on a fixed schedule. For the Linux nerds among us, you can even specify your schedule using cron expressions!

Finally, there's a hidden gem we'd like to point out when it comes to product management with Dais. At some point we all have to raise rates, and when we do it can wreak havoc on our existing book of business. No one likes an arbitrary price increase—not for Netflix, and certainly not for insurance—and come renewal time they will shop. What can help is a good disruption analysis. A disruption analysis answers, “If I applied my proposed new rates to my existing book of business today, who would be hit the hardest and by how much?” This allows you to be proactive about retaining your customers, and can result in as much as an X% decrease in attrition. Disruption analyzes aren't the only standard portfolio analysis that helps a product manager do their job. But they are an important one.

Dais comes with a variety of portfolio analysis tools—including disruption analyses—out of the box. This is a relative rarity, a time-saver, and a relief for whoever does product management on your team. To be clear, this kind of analysis is possible with other policy software platforms, as long as they have solid and well-managed rating APIs, you know how to use those APIs, and you have the product know-how. But having them ready to go when you need them is a strong plus.

With other providers, if a policy software solution has good rating APIs, if you know how to use them, and if you have the insurance product know-how, you can build this kind of tool yourself. But with Dais it's available out of the box!

No-Code Configurability

Products, Portals, Events, Actions, and API Integrations

Everything we've discussed so far can be configured by your team, with or without assistance from Dais, notably:

• Basic product configuration
• Underwriting rules, rates, forms, and document generation
• Application and quote flows (“storefronts”)

To simplify and extend the picture, we say that Dais is an event-based system, and that all events in it are configurable.

In an event-based architecture, everything that happens in the system is an event. Dais has a lot of types of events, specific to insurance: rating, endorsement, cancellation, renewal, non-payment of premium, and the like.

Every event in Dais can trigger an action. These actions can be any number of tasks for the system to perform—also targeted to the needs of an insurtech team. To name a few:

• Rate a product
• Call an external rater or other API
• Stream the event data to your data lake
• Run an automated report
• Send an email
• Initiate cancellation

Any number of actions can be strung together in a chain, each one informed by the results of the actions before it. In this way you can create entire “conversational” API workflows: calling an API with a snapshot of the policy and the details of this event, getting the results back, using those results in a related API call, and so on.

Data Prefill

This same kind of daisy-chaining comes into play in a simpler form elsewhere in the Dais system: data enrichment, or prefill. Insurtech teams love data prefill because it helps price more accurately, enhances customer experience, raises conversion, and saves time for brokers and underwriters. Dais has more than a dozen prefill providers available out of the box, and configuration is simple and intuitive.

Intentionality of Design

Example: Data Prefill

The way Dais handles data prefill is thoughtful, and is a good example of the attention to detail we've seen in their design.

• Relativity6 is one of Dais's available prefill providers. They provide NAICS codes based on business name and address. That's 3 inputs (client.name, client.address1, and client.state) and one output (client.industry.naics).
• Those inputs and outputs are called question IDs, or QIDs. As long as you use those same QIDs in your product, Relativity6 will look up NAICS codes for you based on business name and address, and fill it in. All you have to do is click a toggle at configuration to turn the prefill on.
• If you've done data work, you know how easy it is to instead call your customer something like insured.name… and then the integration wouldn't work. So before you're even looking at Relativity6, when you're setting up your product in the first place, Dais offers field name auto-completion. You start typing "Name," for example, and Dais proactively recommends "client.name: used in Relativity6 and X other places." This forethought anticipates a major headache (your team creating 7 different fields with slightly different names) and significantly simplifies data prefill. Dais gets the mapping out of the way, up front.

Example: Multi-Product Flows

This particular strategy of matching QIDs helps deftly tackle another challenge as well: multi-product application and quote flows.

Say your insured is applying for both a Commercial Property and a Work Comp policy. You might want to do this one of two ways: create a single application flow for both products, or serialize them to chunk up the work for the applicant. But either way you do not want the insured to have to enter the same data twice.

Dais handles this the same way it does data prefill. Say you have the client fill out the applications in order: Commercial Property, then Work Comp. Both products will need the client name. As long as you call it the same thing in both places (client.name), it will prefill from one to the other, exactly like the Relativity6 example.

If you have the client fill out both at once, and both products include client.name, the application flow will automatically only show that question once. Of course, any third-party data prefill you set up for one will automatically flow to the other. And when you first set up your Work Comp product, again Dais's autocomplete will remind you that you called it client.name in Commercial Property… so you might want to use that name here as well.

Continuity of Design Elements

We find Dais to be designed in such a way that if you learn to configure one part of the system, it will help you to learn other parts of the system.

• The way you map Excel workbooks to fields for rating is the same way you map them for reporting.
• The way you map API integrations for rating is the same way you use them to connect to premium finance providers (see below).
• The application has a similar look and feel throughout, and similar navigation elements. If you find your way around one place, you will find your way around the whole more easily.

Automatic, Product-Specific APIs

Every product configured in Dais has a corresponding API. Any time you build a new product, Dais automatically creates that API, and when you change that product it updates the API.

You'll need this kind of API functionality if you are building a front end or integrating with a distribution partner, and that front end or partner has to interact with your policy platform. Any event that can be triggered in Dais can be triggered via API, from rate/quote/bind to endorsement, renewal, and cancellation.

Anyone who's built an integration in or out of a PAS knows that you need to be able to test and troubleshoot that integration. To this end, in their configuration screens, Dais has a prominent section for "API Tools," including usage logs, automation logs, API access keys, and dev docs. The section is a top-line menu item, alongside Customers, Submissions, Products, Portals, Accounting, and Reports. This is a small but meaningful indicator of the priority Dais places on developer experience.

Modern Connectivity

A common theme in our observations of Dais is connectivity. Dais is designed intentionally to make connectivity easy.

To recap some connectivity we've mentioned:

1. Bureau integrations. You can connect to ISO for your rating, underwriting, forms, and product definition.
2. Multi-product. When you use the same questions IDs between 2 insurance products, data seamlessly flows from one to the other.
3. Data prefill. When you use the same question IDs as a data prefill provider, data flows seamlessly in from that provider. All you need to do is toggle the integration on.
4. API calls. You can configure any number of API calls out, strung together in a "conversation," after any event to connect to a provider of your choice.
5. API endpoints. You can also make API calls into Dais. Every product you build has its own full set of API endpoints for this. If you want to, you can create your own whole front end on top of Dais in this way.
6. Reporting. Configurable reporting lets you connect to regulators (via bordereaux), actuaries (via disruption analyses), and your daily operations.

To add more instances of Dais connectivity:

• Distribution. Dais connects out to providers like Talage and Semsee, where brokers can access your products alongside other insurers they're integrated with. Data mappings here are handled as deftly as for data prefill: When you first build out the fields for your product, Dais's auto-complete recommends question IDs that will match these distribution providers for you. Generally speaking, QIDs tend to match cleanly across all use cases: ISO integration, data prefill providers, and distribution.
• Webhooks. Just as every product you build in Dais has its own set of API endpoints, it also comes with its own set of webhooks. For any event that occurs with that product, you can subscribe to be notified at a URL of your choosing via an automatic webhook.
• IoT Integrations. Whether you're partnering with an IoT provider or deploying your own devices, you understand the significance of triggered events—sales, movements, temperature changes, and more. Dais matches these with corresponding moments in your policy's lifecycle. Dais can help you weave a connected product between the two worlds, with IoT events triggering policy events, and insurance events triggering calls to your provider’s API.
• Payment. Naturally Dais includes turn-key integration with Stripe for payment. Stripe is a pretty common payment integration for a policy software platform. Beyond this, though, Dais includes an entire module for premium finance. See the next section!

Premium Finance: Pavo

If you're not familiar with premium finance… well then you probably don't need this feature. But in some sectors of insurance, premiums for an annual policy can be very high, ranging from tens of thousands to hundreds of thousands of dollars, or more. This is particularly common in excess and surplus markets, for example.

Premium finance exists to fill this gap: It's a loan the insured takes out to fund their premium. Most importantly, it allows them to spread their payments into installments throughout the year. As a bonus, if they purchase multiple policies at once, it allows them to bundle those into one loan with one payment plan. If you're a carrier, it means you don't have to manage the complexities of an installment plan. If you're a broker, it helps you close the deal.

Pavo Insurance Solutions is a premium finance marketplace. Pavo integrates with multiple premium finance companies, so that at the moment of checkout you or your broker can offer the insured more choices and have a greater shot at closing the deal. Dais integrates seamlessly with Pavo to make this available on any of your products.

Dais technically offers this functionality outside of Pavo as well. But premium finance as an industry is even more antiquated than insurance. You're going to have a hard time finding a loan provider with JSON/REST APIs. Pavo takes care of all these integrations so you don't have to. And they do it at no cost to you; in fact they share revenue with you from the premium finance companies in the Pavo marketplace.

Insurance-Specific, Baked-In AI

Large language models (LLMs) like GPT are revolutionizing every industry. Smart technologists are building on this foundation to power a new generation of products for domain-specific use cases. Dais is an early adopter to seize on this trend for insurance. They've developed an application called UnderwriteGPT, which is available both through a UI for immediate use and via an API for integration across the Dais platform.

Unsurprisingly given its name, UnderwriteGPT's clearest use cases are to assist underwriters. Here are a handful of the specific experiences they've preconfigured for your team, trained with domain-specific knowledge:

• Exposures. Given this insured's application and all I can pull from the internet, what are the company's top risk exposures? How would I score them?
• Question checklists. For this account and this line of business, what further questions are worth asking to underwrite more precisely?
• Chat. This is essentially ChatGPT, but fine-tuned on underwriting data in addition to all the input the model's already pre-trained on. It extends your underwriters' capabilities the same way that thousands of developers consult LLMs to write code today.
• Class codes. Misclassification of risks can cost you 2–10 points of loss ratio. UnderwriteGPT suggests likely class codes for the insured.
• Sales letters. UnderwriteGPT can draft a letter to your insured simulating what a covered loss might look like and mean to them, and how your policy would make them whole. If you have a highly specialized product, you can even paste in sales collateral about it, and UnderwriteGPT will fold that into its letter.
• Risk management. UnderwriteGPT will help you draft customized risk mitigation checklists for your clients, to help you proactively protect your clients from loss (and safeguard your loss ratios).
• Dynamic large-loss reviews. UnderwriteGPT will help you extract lessons learned from large-loss reports and make recommendations to the underwriting ruleset to improve. Your team can run this manually as needed, or you can automate it at scale with API calls.
• Custom instructions. If you’ve experimented with ChatGPT+'s custom instructions, you’ll appreciate this feature. Custom instructions allow you to tailor how the AI understands and responds to queries by answering prompts like “What do you want the bot to know?” or “How should the bot react?” Dais's version of the feature is intentionally targeted to insurance underwriting use cases. And while prompt engineering can get technical, Dais simplifies it with a user-friendly, no-code interface. This lets anyone fine-tune UnderwriteGPT to meet their unique business needs without delving into complex code.

In many of these cases your underwriters can then accept or reject the suggested content to further train your instance of UnderwriteGPT.

And UnderwriteGPT's functionality extends beyond manual input; you can also configure it to operate automatically, responding to any event that calls for underwriting intelligence. This means that insights from UnderwriteGPT can be integrated directly into your daily workflow, scaling with your needs and extending your team's capacity throughout Dais’s event-based system.

You'll find the Dais team quite excited to demo these features. From what we've seen, their enthusiasm is not unfounded. Applying trained underwriting intelligence across the moments of a policy lifecycle—especially when done at scale in an event-based system like Dais—creates a very real possibility of substantial combined ratio improvements.

Here's how this could break down for carriers and MGAs:

• Classification enhancements (1–2 points)
• Additional underwriting questions and insights (1–2 points)
• Scaled risk management (1–2 points)
• Real-time and scaled large-loss reviews with underwriting rule updates (1–3 points)
• Expense automation (1–2 points)

As you can tell from these use cases, Dais's offering in the space represents quite a bit of thought-work. Integrating AI with underwriting isn't just a futuristic concept; it's a practical approach already taking shape, setting the stage for notable shifts in efficiency and financial outcomes. We suspect LLMs will only become more prevalent in insurtech, and it's encouraging to see the first such products hit the market.

How to Work With Them

Dais Customer Segments

How you work with Dais depends somewhat on how you use them. We've seen teams use Dais in 3 ways, broadly:

1. Brokers use Dais to handle most of the functionality of an agency management system, including a storefront, a customer portal, and the back end to go with them.
2. MGAs and carriers use Dais as their primary policy software platform: front end, back end, and orchestration layer.
3. MGAs and carriers use Dais as their back end and system of record, connecting to it via API and building their own front end.

Option 2 is the most common we've seen, but all 3 are valid. As with any policy software platform, start by letting them know what it is you're doing, what you know of your constraints and specific needs, and what your timing is. Get a demo on the books and start from there. If they make your shortlist, sketch out for them your roll-out plan of states and lines of business, so they can draft up a contract.

Who to Bring

You'll want to bring to the table an underwriter or insurance product specialist so they can make sure your rater calculates premium definitively and your forms and documents nail your specific product language. That is, of course, unless you're using an ISO product without variation (in which case ISO is your product specialist), or unless you won't be using Dais for rating and document generation.

You might also benefit from having someone with the skillset of a business analyst on your team. And it can be helpful to bring your own project manager to the table. This is true of most rollouts of this sort, to be honest.

You will not need your own developers, unless you're building your own front end on top of Dais, as in customer segment 3 above.

Onboarding

At time of writing, lately some teams have found Dais onboarding somewhat rocky, but for the best of reasons: Dais has experienced unprecedented growth and is racing to keep pace. Having an active engaged project manager as we mentioned above should mitigate any bumps. Furthermore, the recent acquisition of Dais by Origami Risk offers a promising avenue for scaling their team to meet increasing demand.

As always, Finsure stands ready to help you think through all your needs, guide your project, and even manage your product launch: whatever gets you to the next step in your journey.

Products

We usually ask providers what specific insurance products their clients are actively selling or placing. In this case, Dais supports a wide range of insurance products, and they encourage potential clients to contact them directly for more detailed information.

Locations

We asked Dais where their customers are currently actively selling or placing insurance. If you don't see your region on the list, we recommend reaching out to ask! This is not meant to be an exhaustive list of where Dais will do business.

Customers Actively Selling or Placing Insurance

• United States

No Current Customers

• Canada
• Latin America
• Europe & UK
• Australia/Asia/Pacific
• Africa

Featured Customers