AI and Data Innovation
OIP Insurtech combines in-depth insurance expertise with advanced AI and data engineering to deliver tangible outcomes: faster quoting, sharper decisions, and more efficient operations.
The future of insurance runs on AI and clean data. But first, your systems need to speak the same language. We help you get there by combining:
Automation that mimics your underwriter's workflow
Custom AI models built for your lines of business
Data platforms that make insights easy to access and act on
What we build
What we build
- AI Agents and Intelligent Document Processing (BoundAI)
- Custom ML and Gen AI Models
- Data Engineering and Advanced Analytics
Built for insurance. Trained by underwriters.
Most AI tools fail because they're built in a vacuum. We embedded insurance logic directly into BoundAI so it doesn't just scan PDFs, it understands what matters and what's missing.
Impact
- Cleared 69% of new submissions with zero human touch
- Cut average submission processing time from 3.5 hours to 4 minutes
- Saved ~1,200+ underwriter hours per month
What if your team didn’t have to handle the busywork?
LLMs are easy to drop into a workflow. Real results aren't.
We design, train, and deploy insurance-specific ML and GenAI models around your actual workflows, data, and risk appetite.
Use GenAI to summarize large packets (e.g., SOVs, policies, loss runs) and validate binder vs quote
Train on submission metadata + past placements to improve quote routing accuracy
Extract, classify, and route FNOL documents using GenAI
Assist underwriters/claims analysts with context-aware agents trained on their own docs
Specialty MGA
Underwriters were manually classifying business lines, which slowed quote speed and created inconsistencies.
We built a custom LOB classification model trained on historical submissions.
Impact
- 96% model accuracy
- 52% reduction in misclassified submissions
- 3x faster quote generation and less rework
AI shouldn't be a black box
Insurance runs on data, but only if you can trust it, structure it, and surface it in time.
From ingestion to insight, we design, maintain, and evolve your data pipelines for performance, scalability, and insurance-grade reliability.
Centralize structured and unstructured data
Clean, transform, and load data across systems
Build trust with rule-based validation
Ensure your dashboards are always up to date, driven by continuous data flows and short refresh periods.
Understand where your data comes from and where it goes
Executive dashboards
Track bind rates, loss ratios, and producer performance
Underwriting insights
Analyze hit ratios, submissions, and premium or TIV trends
Claims intelligence
Identify frequency/severity trends, reserve adequacy, and closure rates
Operations monitoring
Surface cycle time blockers and productivity gaps
Client
Mid-sized MGA
Problem
Submission and quote data was spread across carrier portals, internal Excel sheets, and AMS exports, making reporting a difficult, long, and manual process.
Solution
We built a centralized data platform with an automated ingestion workflow.
Impact
Consolidated multiple data sources into a single source of truth
Automated dashboards for underwriting and sales that lead to a significant improvement in the turnaround time
Make data your competitive edge
Proof in Practice
Custom ML and GenAI Models
A mid-size MGA writing specialty business was overwhelmed with broker submissions, forcing underwriters to review too many risks that rarely bound. Nearly 55% were out-of-appetite, and static PDF guidelines made consistency impossible. By unifying three years of submission, quote, and bind data, our team built custom ML models that scored each submission against actual binding patterns. The scores, embedded directly into the underwriting workbench, gave underwriters real-time triage guidance and leadership new distribution intelligence.
The results? In-appetite rates jumped to 69%, average review time per submission was cut in half, and hit ratios climbed from 18% to 32%. Brokers even began improving submission quality thanks to new efficiency rankings.
“We went from chasing everything to focusing on what actually fits. The model saves time and gives us confidence we’re spending it where it matters.” – Head of Underwriting, Specialty MGA
Data Engineering and Advanced Analytics
A specialty market intermediary modernized its data foundation by migrating from a legacy Oracle database to SQL Server. OIP Insurtech designed custom ETL pipelines, optimized schemas for analytics, and ensured seamless continuity across APIs and utilities. The cutover was completed with zero downtime, reducing ETL runtimes by 35% and eliminating long-standing data inconsistencies.
“Now our data environment is faster, cleaner, and analytics-ready. We can run advanced queries and integrate BI tools directly without the bottlenecks we used to face.” – Head of Operations, Specialty Intermediary
Real clients, real results
83% faster submission-to-quote cycle by pre-clearing ACORDs, loss runs and SOVs before a human sees them
2.3 fewer FTEs per 10K submissions - without reducing service levels or speed
Zero-touch approvals for up to 69% of standard submissions, with embedded business logic checks
Why it works: Insurance-first AI
That’s why our document agents know what to look for and why our models outperform off-the-shelf options.
