Exclusive Interview with Stan Smith, Founder, and CEO, Gradient AI

Artificial intelligence is making great strides in the insurance industry. AI is helping insurers assess risk, detect fraud, and reduce human errors in the application process. AI and ML systems are streamlining the insurance process to connect applicants with carriers more effectively and efficiently. Gradient AI is one of the most reputed artificial intelligent solution providers, helping enterprises by accurately identifying risks and improving their underwriting and claims management. To get deeper insights into how Gradient AI operates and serves the global industry, Analytics Insight has engaged in an exclusive interview with Stan Smith, the Founder, and CEO of Gradient AI.

Give a brief overview of the company background, its specialization, and its services.

Gradient AI provides proven artificial intelligence (AI) solutions for the insurance industry focused on improving underwriting and claims management outcomes. On the underwriting side, our solutions improve loss ratios and reduce quote turnaround time by predicting underwriting risks with greater speed and accuracy than traditional methods. On the claims management side, our solutions reduce claims expenses by identifying claims likely to generate high costs early in their lifecycle, reducing claim duration, and improving claims processing through intelligent automation. 

Gradient AI’s unique combination of three core elements offers a unique value proposition to the market. The first is that, unlike other providers that use limited claims and underwriting datasets, Gradient AI has a vast dataset of tens of millions of medical, claims, and policy data. Second, it incorporates numerous other features including economic, health, geographic, and demographic information. And third is Gradient AI’s team of data scientists with unparalleled experience in applying machine learning to insurance-specific applications. Taken together, we provide customers with the streamlined service and technology they need to maintain a competitive edge.

The company targets all types of insurers including 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.

Describe the disruptive innovation achieved by the company. 

AI has been widely implemented in just about every industry you can name, ranging from transportation to manufacturing, finance, and healthcare. However, the insurance industry hasn’t been as quick as other industries to embrace this technology disruptor. But now that’s changing. Insurance has been and remains a fiercely competitive market. Firms that are slow to leverage the value of their data with AI and machine learning will be at a grave disadvantage. They essentially will be competing against firms who will leapfrog competitors in the same way as Uber, Amazon, and Airbnb disrupted entire industries with digital transformation. I don’t believe the insurance industry has yet fully appreciated the power, scale, and scope of AI and the ways it will fundamentally change the competitive landscape and dynamics in the future.

Explain how your innovation disrupts the existing market.

AI is transforming the insurance industry from underwriting to claims management. Gradient AI’s solutions improve loss ratios and profitability by predicting underwriting and claim risks with greater speed and accuracy. It enables insurers to achieve competitive and operational gains in ways that, in the past, would simply not be achievable. Accelerating claims processing, speeding quote turnaround times, and reducing claim expenses are some of the significant benefits our customers are realizing by leveraging our solutions. Many processes that took days can now be performed in hours or minutes, and with greater accuracy. Here’s an example:

The CEO of a work comp insurance company turned to Gradient AI to solve the problem of creeping catastrophic claims or “creeping cats” as they are commonly called. These claims seem minor initially but end up turning into ongoing, serious issues with major expenses. Roughly 10% of claims will generate about 60% of the total losses.

The CEO was looking to contain the costs of these claims so that the company could identify and proactively manage these claims earlier in the lifecycle before they explode into catastrophic losses. By using our AI solutions on the company’s data, we identified more than 80% of the creeping cat claims by day 30. Compared to the original system, Gradient AI identified more than 5 times the number of claims in one-third of the time. The CEO said, “it’s a slam dunk, we’re doing this, it’s a no-brainer,” and we’re still working with them today.

Brief us about your proactive role in the company.

I first started the company as an independent, product-oriented practice within Milliman, an actuarial consulting firm. I subsequently acquired the business in 2018 and launched Gradient AI as an independent SaaS organization focused on using AI to help improve risk management, one of the insurance industry’s most challenging business problems today.

With nearly 30 years of experience growing AI and technology organizations, I’m focused on ensuring that Gradient AI is applying the latest AI and machine learning technologies to the insurance industry, enabling our customers to improve their claims and underwriting operations and increase profitability. Our growing customer list speaks volumes about what our team has been able to achieve.

Tell us how the company is contributing to the market and benefiting the clients.

Gradient AI is squarely focused on helping insurers achieve a better return on risk. In this data-rich environment, underwriting and claims management workers often don’t have immediate access to the information needed for informed internal and external decision-making. Quite often this is due to the ever-increasing volume and complexity of customer data scattered across siloed business units in various formats.

At a high level, AI replicates human learning, but an AI model can learn from far more policies and claims than any person could ever hope to. An experienced underwriter might see tens of thousands of applications in a career, while an AI model can consider tens of millions of expired policies and the closed claims made against those policies. The AI model can also retain every fact in every one of those policies and claims and can compare those facts to every fact in every other policy and claim it’s ever seen.

Gradient AI’s solutions use predictive analytics to foresee the likelihood of claims on each individual application. With this intelligence, we help insurers lower loss ratios, increase win rates, shorten the underwriting process, automate processes, expand into new geographies, and increase straight-through processing. On the claims side, our customers benefit from a decrease in the cost of claims, decreased spending on litigation, improved claim outcomes, and can allocate resources more effectively. 

What makes the company innovative? What are the key partnerships and involvements done to drive the innovation?

Gradient AI’s team of data scientists have deep insurance industry-specific experience. This has enabled them to innovate, develop, and engineer new data features and models that have powerful predictive capabilities that outperform traditional underwriting and claims assessment methods dramatically. 

Gradient AI has also developed unmatched industry intelligence through partnerships and engineering to create vast datasets comprised of tens of millions of policies and claims. It also incorporated numerous other features including economic, health, geographic, and demographic information. All of this data enables the company to train its models and deliver exceptional predictive capabilities, enabling insurers to more accurately and quickly assess risk and reduce claims expenses in entirely new ways.

Speaking of partnerships, Gradient AI has partnered and integrated its solution into insurance operating platforms including Spear Technologies, Socotra, and Guidewire, enabling insurers to benefit from Gradient AI’s solution within their operations while leveraging the best-of-breed solutions that our partners provide.

Brief us about the challenges and potential drawbacks of your disruptive innovation. 

Insurance is all about risk. Fundamentally, everything an insurance organization does has to do with risk. It’s also a well-entrenched industry, going back some 500 years. As you might expect, with that combination of risk focus and extensive history, insurance is a market that considers change very thoughtfully.

We’re at the early stages of AI in insurance. The innovators and early adopters are already seeing tremendous benefits, and that will only accelerate. We fully expect most, if not all, insurers will move to AI-based solutions. We’re already hearing from several of them about the dynamics of the market shifting.

We are excited about the value that our customers are achieving with AI, and we look forward to helping more insurance providers towards similar outcomes. 

How do you see the company/industry in the future?

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 will fundamentally change the way insurers operate, enabling them to make more decisions with greater speed, efficiency, and accuracy. 

We have seen record growth in the past two quarters at Gradient AI, both in numbers of new customers and revenue, and it’s only the beginning. We’re gratified by the feedback that we continue to receive from our customers about the value they see in our solutions. We also appreciate the validation from industry analysts and others about the sea change that’s underway. 

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.

This article appeared first on Analytics Insight.