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As much as 40% of an underwriter’s time is now spent on non-core administrative tasks.
Most underwriters can only address 20-40% of inbound opportunities.
Digital-first competitors are putting the squeeze on traditional insurance companies.
Get the data you need before making coverage and liability decisions while better controlling loss ratios with guidance on when you should quote. Now, you can respond more quickly to win more of the business you want.
It takes only about 200 documents to train a model on the key data to look for, which can then be fed to claims processing platforms, underwriting workbenches, or the like. The use of human-in-the-loop technology, included in some intelligent document processing platforms (including Indico Data’s), enable your associates to correct or verify the model’s decisions, increasing their accuracy over time.
A good part of the reason commercial insurance companies suffer from underwriting leakage is because examining each broker submission takes too much time. A solution lies in using artificial intelligence to help automate the insurance submission triage process, enabling the same staff to handle more submissions.
The traditional submission triage process is highly manual. An insurance submission request comes in from a broker in the form of an email with one or more attachments. Often, it’s a single attachment that contains numerous discreet documents, such as an ACORD form, statement of value, perhaps a free-form letter, and some custom forms.
With Indico’s AI and ML technologies, you can reduce your intake process costs with full confidence that processes will adhere to industry best practices, ensuring compliance while preventing underwriting leakage.
Automating your submissions intake process not only allows you to write more premiums but also handle a larger number of submissions in less time and with no upper limit to intake capacity.
How can you make good decisions about what risk to underwrite or which claims to approve if that data is trapped inside documents like emails, PDFs, loss runs, ACORD forms, and more?
To capitalize on investing in technology to improve operational efficiency and drive underwriting success, friction needs to be removed from the insurance purchase process. To do this, you need to focus on digitizing workflows, improving data resources, and applying automation to key parts of the claims and underwriting process.
Intelligent document processing can increase process capacity by 4x. That means underwriters can quote and bind far more submissions – dramatically increasing the top-line gross written premium figure. Claims handlers are likewise more productive, which reduces operational costs while keeping customers happy because they see claims processed faster.
Insurers can calculate the return on an intelligent document processing investment by looking at what increasing process capacity can mean in practice.
For underwriters, consider the submission quote to conversion rate for a global property and casualty insurer that receives a quarter of a million submissions annually. Given its capacity constraints, it quotes only 40% of submissions and binds 20%. Let’s say that results in $18.6 billion in premium value and $372 million in profit.
A good intelligent document processing solution can greatly increase the submission to quote conversion rate, from around 10 days to less than a single day. That means carriers can quote – and win – far more business.
At the heart of Indico Data’s solutions is DocumentDNA, our proprietary approach to modern AI and machine learning. DocumentDNA enables seamless multi-channel, multi-document intake for any format, using accurate, automated processes that keep your employees “in the loop” – giving you the power to make more informed decisions faster.
Powered by an AI-driven, multimodal fusion approach to document understanding, we gather both semantic and visual information to drive decisioning.
Our unique approach to transfer learning enables you to build custom ML models with as few as 200 sample documents – not thousands.
Enabled by a patented ML interface, non-technical users can create custom models with our “bionic-arm” approach to stay in the loop of the processes they are automating.
We’ve identified almost $100 million in hard value, hard dollar savings, that we can quite easily achieve over the next three to four years using unstructured data digitization and analytics tools. That just headlines how impactful this is.
