Resources

How In-Network Providers Shape Group Benefits Strategy

Not long ago, a plan member could walk into an in-network hospital, receive care from an out-of-network provider, and walk out with a five-figure bill. The plan paid some. The provider charged what they liked. The rest landed on the patient. Those days are fading, but not because care has gotten simpler. It is because […]

How Insurers Are Innovating Solutions for Group Benefits

You can sense the transformation rippling across the group benefits industry. Employee demographics now span five generations, mental health challenges are on the rise, and personal finances have grown more precarious than ever. Meanwhile, 40% of employers are boosting their investment in benefits innovation to stay competitive (SHRM, 2023). At the same time, tech-savvy startups […]

Mitigating Risks in Group Benefits Underwriting: Best Practices for Insurers

Underwriting is the ground zero of group benefits. The place where cost, risk, and regulation collide to shape coverage for millions of employees.  Done right, it keeps plans both affordable and solvent. Done wrong, it amplifies the system’s worst pressures. In the U.S. alone, more than 155 million people rely on employer-sponsored health insurance. The […]

How Insurers Can Streamline Group Benefits Administration and Improve Outcomes

The storm rolling over the insurance industry has been long in the making.  Underwriting margins once cushioned by predictable payrolls now face a choppy sea of unpredictable market shifts. Brokers, desperate for swift answers, wrestle with outdated tech that chugs along like an old locomotive on a modern bullet-train line.  Employers, anxious to secure the […]

Why Manual RFP Processes Are Costing Insurers More Than They Think

Is it still possible to stay afloat when every new email threatens to submerge you in data? For underwriters at group benefits insurance companies, that question hangs in the air each time a fresh Request for Proposal (RFP) makes its way to their inbox. Modern RFPs rarely arrive in tidy packages. They are a mishmash […]

The Rise of Domain-Specific Knowledge Agents: A Deep-Dive

TL;DR Agents have caught enterprise fancy with clear economics and by all predictions, demand for AI agent led IT and Business transformation is likely to be a multi-year journey. Output quality, accuracy, safety, and privacy are key differentiators and crucial for driving up the consumption. Agentization depends on availability of high quality domain-specific knowledge Curating, […]

The Future of Employee Benefits: Top Trends to Watch Out for in 2025

Imagine telling an insurance executive in the 1970s that, in the not-so-distant future, they would be crafting group benefit plans that include coverage for mindfulness app subscriptions, pet insurance, or even student loan repayment assistance. They might have chuckled at the absurdity—or marveled at the complexity. Yet here we are in 2024, navigating a landscape […]

Top Insurtech Trends for 2025 and Beyond

The insurance industry stands at a crossroads. The global protection gap, a measure of uninsured risk, looms large. By 2025, it will reach $1.86 trillion. This is not just a number. It represents real people and businesses exposed to financial ruin. The old models of insurance are failing to keep pace with a rapidly changing […]

A Guide to Managing Illiquid Assets in Pension Risk Transfers

As the sun rose on a crisp autumn morning in 2022, pension fund managers worldwide awoke to a startling new reality. The gilts crisis that had rocked UK financial markets had not only sent shockwaves through the economy but also dramatically reshaped the landscape of defined benefit pension schemes. For many, the path to buyout—once […]

Finding Conversion Anomalies at a Large E-Commerce Firm

Learn how a leading multi-billion dollar e-commerce company used Enrich to identify anomalies in their conversion rates and to find out their causal factors.

Streamlined data insights and agile data preparation for Terrapay

Learn how Terrapay, a leading cross-border payment infrastructure solution provider built the Terrapay Intelligence Platform (TIP) with Enrich to achieve operational efficiency through use cases such as Forecasting, Partner Performance Analytics, Customer Journey Analytics, and more.

How Mars Took Steps to Evaluate the Potential Impact of the “Great Resignation”

Learn how Mars, a Fortune 100 CPG company collaborated with Scribble Data to assign a “probability of attrition” through data, and ML modeling.

Accelerated ML Engineering for a Leading E-Commerce Brand

Learn how a leading e-commerce brand selling children’s apparel built their data intelligence platform on Scribble Data that supported the rapid development and deployment of use cases such as Product Listing Optimization and Re-ordering.

Understanding Shopping Paths at a National Mall Chain

Learn how a nationwide mall chain used Scribble Data’s Enrich platform to identify patterns of shopper footfalls, determine the timing and location of ads, and achieve a significant M-o-M increase in revenue.

A National Level Retail Store Chain

A national level retail chain in India leverages Scribble Data Enrich for developing an accurate understanding of their buyer personas, their distribution, demand and context at a fine granularity to address multiple operational use cases.

MLOps Conference: Fast Development of ML Applications

Malavika Lakireddy (VP, Product Development, Zeotap), Saransh Verma (Director-Analytics, TerraPay), and Dr. Venkata Pingali (Co-Founder and CEO of Scribble Data) talk about the challenges in developing ML applications.

Orchestrating AI Assistants at the Enterprise

Dr. Venkata Pingali, CEO of Scribble Data, talks about the complexities of orchestrating multiple AI systems to work seamlessly together.

Lifecycle of a Data Product with Dr. Venkata Pingali

Watch this session where Dr. Venkata Pingali, Founder & CEO of Scribble data shares his perspective on Data Products, the types of Data Products, and the lifecycle of Data Products with the Data Heroes community.

Customer Testimonial: Cloudphysician

Dileep Raman, Cloudphysician’s Co-founder and Chief of Healthcare, talks about how Scribble Data enabled them to rapidly build pipelines to transform their data and get daily updated feature sets as well as trustworthy models – all in less than 4 weeks!

Customer Testimonial: Mars, Inc.

Dr. Vidyotham Reddi of Mars, Incorporated–a leading US-based multinational CPG manufacturer of confectionery, pet food, and other food products and a provider of animal care services, talks about his experience of working with Scribble Data. Learn how his team at Mars was able to assign a “probability of attrition” to employees, calculated based on which […]

What’s the deal with sentient AI? – Achint Thomas

Sentience in AI has always been the holy grail for computer science. What qualifies as AI sentience, and what is just another case of a model mimicking the data it’s trained on?

Anatomy of a production ML feature engineering platform – Venkata Pingali

This talk draws upon the Scribble’s experience in building and evolving a production feature engineering platform, and the many conversations we have had with user data scientists. The talk will focus on the learnings, and not on the Scribble product itself, and expand on the talk from Fifth Elephant Mumbai in Jan 2019 on reducing […]

Accelerating ML using Production Feature Engineering Platform by Venkata Pingali

Anecdotally, only 2% of the models developed are productionized, i.e., used day to day to improve business outcomes. Part of the reason is the high cost and complexity of productionization of models. It is estimated to be anywhere from 40 to 80% of the overall work.

Global Feature Store Meetup #13 – Scribble Data

Feature stores have been traditionally designed for complex ML applications (Big-ML) that normally assume clear and high value propositions, long lead times, skilled staff, and advanced methods. Sub-ML is a space of mid-complexity ML applications where there is higher uncertainty in terms of value, methods used, available staffing, and speed is critical. Sub-ML is interesting […]

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