Cognitive Business
Analytics Platform
Planck’s platform delivers more than just static data points to make assessments—it generates actionable underwriting answers to power the commercial insurance strategies of the future.
Commercial underwriting doesn't need more data... it requires answers
Planck’s Cognitive Business Analytics Platform uses proprietary algorithms to map a business’s digital footprint and create powerful underwriting insights in seconds. Confidently bind, assign, or reject submissions based on a complete, real-time risk assessment.
Consistent Underwriting Assessments
Beyond automating submissions or robotic process automation, Planck deploys world-class AI capabilities to automate all phases of underwriting and remove decisioning noise. By layering specific AI functions across the information flow, the AI matches and standardizes the thought process of a team of seasoned underwriters.
An Army of your Best Underwriters
Future-proof your organization. With a complete and business-specific risk assessment based on strategic focus and best-practices, Planck’s AI can automate sections or the entire underwriting process from submission to bind—freeing underwriters to focus on more nuanced tasks and strategic growth.
Real-Time Data Collection
Leveraging Planck’s exclusive open web data-mining capability to pull from thousands of available sources, your underwriters will gather all available data about a business entity and its operations in real time.
Planck uses advanced machine learning to ensure the risk data results provided are relevant to the business in question. Entity matching, or entity resolution, is a vital verification step for accurately pulling together data from unrelated sources.
Planck scans thousands of sources, including industry-specific sites, social networks, consumer reviews, business websites and profiles, public records, governmental databases and more. More data points contribute to a more accurate risk profile, which leads to more informed underwriting decisions.
Data Processing: Knowledge
Using proprietary artificial intelligence capabilities built and trained specifically for commercial insurance (including computer vision, natural language processing, unstructured data analysis, and others), Planck interprets millions of collected data points about a business to assess intermediate insights.
Many data points incorporate additional layers hidden below the surface. Images can include metadata that reveal when the image was taken, the device it was taken on, where it was taken and more. Planck’s algorithms can also interpret images and video to detect specific risk-related elements within specific frames.
Unlike traditional data platforms that rely on static data sources, Planck finds all available evidence for a specific business in real time, and then analyzes the collected data to uncover every last relevant data point.
Creating Insights: Wisdom
After all data points are collected and processed, deep-learning algorithms crunch the data to reveal the complete truth about the business. Then, all collected and created insights are returned to the carrier via an API.
The deep-learning algorithms are continuously trained on “gold data,” verified information about a business, to create connections and reveal valuable insights that can’t be found in traditional searches.
Each piece of information tells its own story. Some data points might even contradict one another. And often the most valuable insights aren’t available as raw collectable data. That’s why Planck focuses on context to provide answers.
Creating The Truth: Decisions
Planck’s AI operates with the experience of multiple veteran underwriters. It draws actionable conclusions that are infinitely scalable for consistent assessments throughout the underwriting process. Imagine an army of your best underwriters operating at full speed, all the time.
Training in best practices
Some of the underwriter’s decisions can be easily automated using a basic rule-based system. But a lot of decisions can’t. Just like training a new recruit, the AI will learn from the decisions and best practices of veteran underwriters. But the AI can learn from multiple experienced underwriters simultaneously and be brought completely up to speed in just a few months to tackle more and more complex submissions.
