metadata
language:
- en
license: apache-2.0
tags:
- insurance
- fraud-detection
- xgboost
- isolation-forest
- uk-insurance
- tabular-classification
- bytical
library_name: xgboost
pipeline_tag: tabular-classification
datasets:
- piyushptiwari/insureos-training-data
model-index:
- name: InsureFraudNet
results:
- task:
type: tabular-classification
name: Insurance Fraud Detection
metrics:
- type: roc_auc
value: 1
name: AUC-ROC (Motor)
- type: roc_auc
value: 1
name: AUC-ROC (Property)
- type: roc_auc
value: 1
name: AUC-ROC (Liability)
InsureFraudNet — Insurance Fraud Detection
Created by Bytical AI — AI agents that run insurance operations.
Model Description
InsureFraudNet is a multi-line-of-business fraud detection system for UK insurance claims. It consists of paired XGBoost classifiers and Isolation Forest anomaly detectors for three lines of business: Motor, Property, and Liability.
Architecture
Each line of business has:
- XGBoost Classifier — Supervised gradient-boosted tree for fraud probability scoring
- Isolation Forest — Unsupervised anomaly detection for novel fraud patterns
Lines of Business
| LoB | Training Claims | Fraud Rate | Features | AUC-ROC | F1 |
|---|---|---|---|---|---|
| Motor | 25,000 | 8% | 23 | 1.000 | 1.000 |
| Property | 15,000 | 8% | 20 | 1.000 | 1.000 |
| Liability | 10,000 | 8% | 14 | 1.000 | 1.000 |
Top Fraud Indicators by LoB
Motor:
| Feature | Importance |
|---|---|
| claim_reserve_ratio | 48.9% |
| days_to_report | 43.7% |
| policy_age_days | 5.7% |
| previous_claims_3y | 1.4% |
Property:
| Feature | Importance |
|---|---|
| days_to_report | 40.9% |
| policy_age_days | 37.6% |
| claim_reserve_ratio | 20.0% |
| previous_claims_3y | 1.4% |
Liability:
| Feature | Importance |
|---|---|
| previous_claims_3y | 56.1% |
| days_to_report | 43.9% |
Files
| File | Description |
|---|---|
xgb_motor.json |
XGBoost model for motor fraud |
xgb_property.json |
XGBoost model for property fraud |
xgb_liability.json |
XGBoost model for liability fraud |
iforest_motor.pkl |
Isolation Forest for motor anomalies |
iforest_property.pkl |
Isolation Forest for property anomalies |
iforest_liability.pkl |
Isolation Forest for liability anomalies |
training_results.json |
Full training metrics and feature importance |
How to Use
import xgboost as xgb
import pickle
import numpy as np
# Load motor fraud model
model = xgb.XGBClassifier()
model.load_model("xgb_motor.json")
# Load isolation forest
with open("iforest_motor.pkl", "rb") as f:
iforest = pickle.load(f)
# Example claim features
claim = np.array([[
35, # driver_age
10, # years_driving
5, # years_ncd
2020, # vehicle_year
25000, # vehicle_value
12000, # annual_mileage
800, # premium
250, # voluntary_excess
100, # compulsory_excess
5000, # reserve_amount
4500, # claim_amount
0, # recovery_amount
0, # previous_claims_3y
3, # days_to_report
365, # policy_age_days
1, # witnesses
1, # dashcam
1, # police_report
0.9, # claim_reserve_ratio
5.625, # claim_premium_ratio
0, # new_policy
0, # late_report
4 # vehicle_age
]])
# Predict fraud probability
fraud_prob = model.predict_proba(claim)[0][1]
is_anomaly = iforest.predict(claim)[0] == -1
print(f"Fraud probability: {fraud_prob:.2%}")
print(f"Anomaly detected: {is_anomaly}")
Part of the INSUREOS Model Suite
This model is part of the INSUREOS — a complete AI/ML suite for insurance operations built by Bytical AI:
| Model | Task | Metric |
|---|---|---|
| InsureLLM-4B | Insurance domain LLM | ROUGE-1: 0.384 |
| InsureDocClassifier | 12-class document classification | F1: 1.0 |
| InsureNER | 13-entity Named Entity Recognition | F1: 1.0 |
| InsureFraudNet (this model) | Fraud detection (Motor/Property/Liability) | AUC-ROC: 1.0 |
| InsurePricing | Insurance pricing (GLM + EBM) | MAE: £11,132 |
Citation
@misc{bytical2026insurefraudnet,
title={InsureFraudNet: Multi-LoB Insurance Fraud Detection},
author={Bytical AI},
year={2026},
url={https://huggingface.co/piyushptiwari/InsureFraudNet}
}
About Bytical AI
Bytical builds AI agents that run insurance operations — claims automation, underwriting intelligence, digital sales, and core system modernization for insurers across the UK and Europe. Microsoft AI Partner | NVIDIA | Salesforce.