December 14, 2022
My background is in growing AI and technology organizations, which I have been doing for the past 30 years. Several years ago, as a predictive analytics practice leader at an actuarial consulting firm, I witnessed first-hand the inefficiencies and mistakes occurring within the insurance industry because of compounding data issues. Insurers were spending an awful lot of time collecting data scattered across siloed business units on paper or in other unstructured digital formats. Underwriting and claims management professionals didn’t have access to the information they needed to make decisions, and they were assessing risk using traditional approaches that have largely been in place for decades, if not centuries.
Determined to address these business challenges, I launched Gradient AI as a software-as-a-service (SaaS) organization focused on applying artificial intelligence (AI) and machine learning technologies to help the insurance industry operate more efficiently and effectively.
We enable insurers to achieve competitive and operational gains in ways that were simply not possible in the past.
Gradient AI provides artificial intelligence-driven SaaS solutions exclusively for the insurance industry, with a focus on both underwriting and claims.
Underwriting
Gradient AI’s solutions help insurers with underwriting by helping them to more accurately identify the risks inherent in new and renewal policies. This allows insurers to:
Claims
Gradient AI’s claims solutions help insurers improve their operations by providing an “early warning radar” to identify the most expensive claims earlier in their life cycle. This enables them to proactively focus on those claims that can have the greatest business impact to reduce costs. As a result, insurers can:
We serve mid-market and large insurers in the workers’ compensation, group health, and property & casualty markets. Our customers include primary carriers, third-party administrators, self-insured entities, brokers, captives, excess and surplus carriers, managing general agents and underwriters, professional employers’ organizations, reinsurers, and risk pools. We are particularly well-suited to organizations looking to take advantage of the speed, accuracy, and scalability that AI can offer to better assess risk and increase profitability.
In addition to its extensive AI and insurance expertise, Gradient’s AI-powered solutions achieve a greater level of accuracy by leveraging its vast federated dataset containing tens of millions of policies, claims, and health records. We also incorporate numerous features including economic, health, medical, geographic, and demographic information.
We’re a leader in the market and we’re building on this leadership position in several ways. I’ll give you one example in medical underwriting: Gradient AI recently acquired the healthcare analytics business unit from Prognos Health. Now, in addition to retrieving medical and prescription claims data, customers also have access to lab data, which has been a missing factor for many insurers when predicting group risk.
According to the Centers for Disease Control and Prevention (CDC), 70% of today’s medical decisions depend on laboratory test results because they are among the best indicators of disease severity and progression. With the acquisition, Gradient AI became the only company in the group medical insurance market to provide a medical, prescription, and lab data from a single source. It’s a game-changer. Our combined solution provides a holistic picture of group health risks that have never before been possible. Working with Gradient AI, insurers can now improve their abilities to project group health assessments and costs with much greater confidence.
We are seeing AI pass a tipping point in insurance by transforming the claims and underwriting processes. This is being driven by three key factors:
The insurance industry is 500 years old and understandably the people who work in it are risk-averse. That said, insurers that don’t leverage AI for their businesses will be at a major disadvantage. Other firms will leapfrog over them in the same way as Uber, Amazon, and Airbnb disrupted entire industries with digital transformation.
I would advise insurers to not procrastinate, as a similar disruption is underway in the insurance industry. They should start by developing a clear vision of the strategic levers they want to move, whether that is to reduce costs, improve the customer experience or offer a new and differentiated service. The objective should be to invest in AI in ways that benefit your business model, to achieve a positive, significant, and sustainable impact on your business.
The coming years will bring about a dramatic transformation in the insurance industry. AI has been called the next industrial revolution and I believe it is transforming the way insurers operate, enabling them to make more decisions with greater speed, efficiency, and accuracy.
As testimony to AI’s adoption, we have experienced record growth over the past year, both in numbers of new customers and revenue which have more than doubled. We are grateful to our customers who have chosen us, which to my mind, is the most credible validation a company can achieve.
We plan to continue our growth trajectory by investing in three areas: (1) our data assets, (2) an advanced AI platform and (3) tighter integration with our insurance technology partners. I see AI in insurance continuing to be further integrated into all phases of a company’s operations including underwriting, claims management, and customer service operations. I also believe the industry will continue to leverage machine learning to gain value from both their structured and unstructured data assets to power better decisions and offer customers a better and differentiated experience.
We will also see more novel uses of image recognition, video analytics, and speech recognition, as the industry finds new and innovative ways to leverage AI strategically. That means resolving claims more quickly, providing immediate quote responses, more competitive quotes, and better customer service.
As a serial entrepreneur, I’ve been involved in a fair number of growth markets and successful companies. Even then, I’ve never been more excited to be a part of a company than I am at Gradient AI, as we help insurers achieve a better return on risk.
I hinted at this earlier – my strongest advice would be to consider AI not as a technology decision, but as a business one. You really need to have your business strategy clearly mapped out before making a major investment in AI (or any other technology for that matter). This should be a strategically driven business decision first and foremost. I would suggest that companies develop a roadmap for what areas of the business they are looking to impact, and the metrics they will use to measure that impact.
For example, let’s assume that a company is really interested in offering a differentiated customer experience. That may involve leveraging AI as a way to power straight-through processing to reduce the quote turnaround time, and some level of automatic claims settlement to provide a better customer experience.
The other important piece of advice is that while taking a wait-and-see stance may seem like a path of less risk, it is in fact the opposite. Those insurers who sit on the sidelines are very likely to find themselves at a significant competitive disadvantage as the industry’s adoption of AI has crossed a tipping point.
Stan founded Gradient AI, first as a unique practice within Milliman to focus on the risk management and insurance industry’s most challenging business problems. He subsequently acquired the business from Milliman in 2018, founding Gradient as a rapid growth independent SaaS organization. With nearly 30 years of experience growing AI and technology organizations, Stan’s leadership ensures that Gradient is applying the latest Artificial Intelligence and Machine Learning technologies to the insurance industry, resulting in proven financial performance for its stellar list of customers and better treatment and outcomes for individuals.
Stan has held founding or executive-level roles for multiple startup companies, including Vice President at MatrixOne, Executive Vice President and General Manager at Agile Software, and CEO and Founder OpenRatings.
Stan also led the development of patented technologies including technology that predicts bankruptcies for small, privately held suppliers; a global database to improve supplier performance for more than 80 million companies; and, technology that combines assessments with performance data to identify opportunities for reducing inefficiencies through lean initiatives.
This article first appeared on AI TechPark.
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