Verikai

Understanding food security’s impact on diabetes risk has transformed our assessment approach. Geographic food environment data tells a powerful story: • Fresh food access patterns • Fast food density impact • Grocery purchase behaviors • Nutritional resource availability Your thoughts on food security in risk assessment? #insurance #insurtech #underwriting

Our AI just identified a combination of factors that predicts MSK surgical outcomes with 85% accuracy. Traditional models are missing this crucial signal… By analyzing millions of surgical outcomes, we’ve uncovered surprising predictors that outperform traditional risk factors. Our machine learning revealed: • Social factors predict outcomes better than medical history • Recovery patterns follow unexpected trajectories • Support network size impacts complications • Lifestyle factors determine success rates These insights help underwriters: • Predict surgical success probability • Adjust risk models for surgical cases • Price coverage more accurately • Target pre-surgical interventions This is revolutionizing surgical risk assessment. How do you currently evaluate surgical risk? #insurance #insurtech #underwriting

By leveraging non-standard data sources beyond claims information, creative solutions can be made. We’ve transformed our risk assessment approach by looking beyond traditional data sources. Here’s why it matters: • Deeper insights • Better predictions • Earlier interventions What non-standard data sources are you exploring?

“The treatment adherence predictor hiding in your data” Our AI has uncovered a startling correlation between seemingly unrelated data points and MSK treatment success. Here’s what it means for your risk models… By analyzing an extensive array of behavioral and social factors, we've identified powerful predictors of treatment outcomes. Key insights: • Social factors predict adherence better than demographics • Digital engagement correlates with treatment success • Transportation access impacts completion rates • Support network size affects outcomes Our machine learning helps underwriters: • Predict treatment success likelihood • Identify adherence risk factors • Adjust risk models accordingly • Target support resources effectively This transforms how we assess treatment risk. How do you currently predict treatment adherence?

Claims data alone isn't enough. Our analysis shows that behavioral patterns significantly influence diabetes outcomes. The game-changer? An extensive array of unique behavioral indicators. We're revolutionizing risk assessment by analyzing: • Economic vulnerability • Food security • Healthcare access • Environmental factors • Lifestyle patterns The impact is clear: better prediction models for a condition affecting 529 million people globally. What non-traditional data sources are you using in your risk assessments? #insurance #insurtech #underwriting

Here’s a powerful insight: 96% of diabetes cases are Type 2 – and largely preventable through lifestyle interventions. This changes everything about risk assessment. Our machine learning models now analyze an extensive array of lifestyle indicators to predict and help prevent Type 2 diabetes development. Key focus areas: Prevention Opportunities: • Weight management indicators • Physical activity patterns • Dietary habit analysis • Stress level monitoring • Sleep quality tracking But the real breakthrough? Our predictive analytics can now identify high-risk individuals up to 18 months before traditional diagnosis methods. By integrating lifestyle data with clinical indicators, we’re transforming: • Risk prediction accuracy • Intervention timing • Prevention strategies • Cost management approaches The future of diabetes risk assessment isn’t just about managing existing cases – it’s about preventing new ones. Share your thoughts: How are you incorporating prevention into your risk models? #insurance #insurtech #underwriting

🌟 We're live at the SIIA Spring Forum in Tampa! Stop by Booth 9 at the Tampa Marriott Water Street to learn how our AI-powered risk assessment tools are revolutionizing healthcare decisions. Our team is ready to demonstrate how we analyze an extensive array of unique behavioral patterns to enhance risk prediction accuracy. Currently at the booth: • Paul Stock • Mike Gold • Justin Nestico • Brooke Cleary Drop by today or tomorrow - we'd love to connect!

“Why your age-based risk adjustments are off by 40%” Our machine learning models just exposed a flaw in traditional age-based MSK risk assessment. Here’s what the data really shows… After analyzing millions of claims across all age groups, we’ve discovered that standard age adjustments can miss crucial risk factors. Our AI revealed: • Activity levels matter more than age • Recovery patterns don’t follow expected curves • Lifestyle factors override age indicators • Prevention effectiveness varies unexpectedly These insights help underwriters: • Adjust age-based risk models • Identify true predictive factors • Price coverage more accurately • Target interventions effectively The future of age-based risk assessment requires AI-driven precision. How are you currently factoring age into your risk assessment? #insurance #insurtech #underwriting

After analyzing millions of health records, we’ve identified economic vulnerability as a crucial predictor of diabetes outcomes. Breaking down the barriers between financial and health data. Our research shows that understanding economic factors – from income stability to healthcare access – transforms risk assessment accuracy. Here’s what we’ve learned: • Low income impacts treatment access • Unemployment affects medication adherence • High out-of-pocket expenses influence outcomes • Financial stress correlates with poor self-care By incorporating these factors into our predictive models, we’re seeing a significant improvement in risk assessment accuracy. What economic factors do you consider in your risk models? #insurance #insurtech #underwriting

We're excited to announce our upcoming presence at the SIIA Spring Forum in Tampa! Join us at Booth 9 to discover how our predictive analytics are transforming healthcare risk assessment. Visit our booth to meet our team: • Paul Stock • Mike Gold • Justen Nestico • Brooke Cleary Where: Tampa Marriott Water Street When: March 17-18 Booth: 9 Stop by and let's explore how we can transform healthcare risk together!