Why Centana is Leading Gradient AI’s Series C
By Matt Alfieri | Co-Authors: Jay Lee, Chris Chen
The ability to understand risk is the lifeblood of insurance. As they say, “there’s no bad risk, just bad prices.” Whether or not this statement rings true, to maintain healthy loss ratios and grow a book of business profitably, an insurer must be effective at underwriting risk. This involves evaluating new (and existing) policyholders, assessing their risk factors, and pricing policies in such a way that they are compensated for the level of risk being assumed.
Similarly on the claims side, insurers must carefully monitor and manage risk effectively amidst the thousands of complex claims they process each year. Take, for instance, workplace injuries where an employee may require high-cost medical care. In these situations, knowing which claims to prioritize helps the policyholder recover and return to work faster. Furthermore, awareness of how to escalate the claim (for example, identifying new developments that indicate the need for surgery) enables insurers to make quicker, more effective decisions and better manage costs. As Centana’s Advisory Board member and long-time insurance expert, George Cochran, puts it – insurance claims age about as well as milk!
AI Benefits Both Underwriting and Claims Management
In the insurance market, the underwriting process has historically involved significant manual effort. For example, health insurance underwriters have relied on health questionnaires, actuarial consultants, and/or legacy providers – a painful process (for both the insurer and customer) often yielding suboptimal results. Gaps in claims and health history make it challenging to assess new policyholders, and a longer time-to-quote creates a negative customer experience. As a result, insurers often miss out on new business and the opportunity to drive greater profitability in their book.
Regulatory changes such as the Affordable Care Act have exacerbated these pain points. For example, in the small-group market (up to 50 or 100 employee groups), insurers are no longer allowed to underwrite individuals based on disclosed/requested health histories. However, new technology platforms have risen to address this changing landscape. Third-party data sources, providing information such as anonymized lab or prescription records, and predictive analytics can make a meaningful impact on the underwriting process. Artificial intelligence (AI) driven models can help insurers gauge leading health indicators and appropriately size the likelihood and magnitude of future claims.
Similarly, in claims management, insurers need to consider 30 or more different attributes to make judgments on the next action they should take with a claim, whether that is to settle, contest, or require more information. They face a myriad of questions and decisions when it comes to managing a claim around costs, claim reserves, potential legal representation, and much more. Determining how to handle serious claims involving a major injury requires more attention. Some of the most damaging cases are claims that start off seemingly innocuous but snowball with high expenses. In the worst-case scenarios, these claims morph almost unnoticed, until they emerge as catastrophic cost-drivers, where it is often too late for insurers to mitigate expenses.
AI enables claims professionals to leverage the history and nuances of every claim processed in their company, as well as those in other organizations like theirs. It also provides context and history to understand the factors that could drive a claim in one direction or another, and the ability to look ahead to how a current claim could evolve. This level of insight enables insurers to be more proactive, getting ahead of claims and taking action before they develop into costly outcomes.
And we’re in the early innings of this innovation – the global market for AI in insurance is projected to expand at a double-digit CAGR to reach $45Bn by 20311, with claims and underwriting considered among the largest use-cases for AI to transform the industry.2
Highly Predictive Models + Superior Data = Better Commercial Outcomes for Insurers
Gradient AI’s platform provides data and predictive analytics solutions across multiple insurance markets, including group health and property and casualty. The Company’s cutting-edge software combines AI and machine learning models with a vast pool of data assets to generate value-added insights into an insurers’ return on risk. As a result, insurers using Gradient’s solutions can effectively underwrite policies by offering more aggressive pricing for high-quality groups, avoiding or pricing high-risk deals appropriately, and gaining enhanced visibility into the performance of books of business at renewal. For example, Gradient’s AI-driven health underwriting product (SAIL) provides underwriters with a risk score for new employee groups and helps them better understand the risk of that population in an explainable and HIPAA-compliant way.
Through our conversations with dozens of market participants, the value of Gradient AI’s product was clear. The platform has aggregated a data set that is both broad and deep and is paired with best-in-class predictive models which are finely tuned to the Company’s respective markets. As a result, Gradient’s nearly 200 and rapidly expanding customer base, which spans insurance carriers, MGA/MGUs, PEOs, TPAs, and more, are able to gain a comprehensive understanding of risk, leading to improved loss ratios and enhanced profitability.
Centana’s Expertise in Insurance Technology
Centana has deep experience investing in enterprise solutions serving the insurance and financial services ecosystem, including a strong focus on underwriting software and AI infrastructure. Prior investments in the space include Zesty.ai (P&C underwriting), One Inc (insurance payments), and Striveworks (AI/ML operations software). Dedicated thematic work and long-time connectivity to relevant firms in the space, including insurance carriers, brokers, employer groups, and more, has highlighted the necessity of data-driven tools to help insurers grow profitably as competition continues to drive market adoption of new underwriting and claims management solutions.
What’s Ahead for Gradient AI
We’re thrilled to partner with Stan Smith (Founder & CEO), an experienced multi-time founder with a rare combination of product vision and commercial expertise. We’ve known Stan for over five years and have cheered from the sidelines as he and his team have consistently and methodically executed on their vision for Gradient AI over that time. Stan and his leadership team have decades of relevant experience in the insurance, healthcare, and software industries which has helped the Company scale to be a leading AI underwriting and claims management analytics player. We believe Gradient AI sits at an important inflection point and are excited to provide growth capital to allow the business to further invest in product expansion and go-to-market efforts to continue delighting its customers and extend its competitive advantage. We look forward to supporting Stan and the broader Gradient AI team as they embark on this next stage of growth.
[1] Accenture. (2022). Why ai in insurance claims and underwriting.
[2] Vinichuk, O., & Bekker, A. (2024). Artificial Intelligence (AI) for Insurance Underwriting in 2024.