Fraudulent Claim Detection
This bot will allow you to detect fraudulent claims using DataRobot’s automated machine learning along with Automation Anywhere's RPA capabilities.
Top Benefits
- In case of Fraud claim, the bot would send an email to supervisor. Otherwise, the bot would redirect the user to claim approval system.
Detect whether a claim is Fraud or Not Fraud using Data Robot APIs.
IQ Bot 6.0 is required
Key Use Case: Fraudsters are not discriminating. They target any insurance company, large or small, that doesn't have a predictive system to catch fake claims. Without a predictive model to identify fraud, insurers have two options: 1. Review no claims and pay out on fraud OR 2. Review every claim and lose good customers at renewal time due to poor treatment and slow claims processing. With the Fraudulent Claim Detection Bot we can detect whether a claim is Fraud or Not Fraud using Data Robot APIs. In case of Fraud claim, the bot would send an email to supervisor. Otherwise, the bot would redirect the user to claim approval system.
Get Bot
Free
- Applications
-
- Business Process
- Information Technology
- Category
- Cognitive Automation
- Security
- Passed third-party anti-virus scan conducted by Automation Anywhere.
- Downloads
- 158
- Vendor
-
- Automation Type
- Bot
- Last Updated
- December 6, 2019
- First Published
- December 7, 2018
- Enterprise Version
- 11.x
- Community Version
- -1
- Support
-
- Predikly
- +14082428232
- prediklybots@predikly.com
- Bot Store FAQs
See the Bot in Action
Setup Process
Install
Download the Bot and follow the instructions to install it in your AAE Control Room.
Configure
Open the Bot to configure your username and other settings the Bot will need (see the Installation Guide or ReadMe for details.)
Run
That's it - now the Bot is ready to get going!
Requirements and Inputs
- AAE v11.1 , IQ Bot 6.0
Inputs:- DataRobot Credentials
- Username
- API Key
- DataRobot Key
- Project ID
- Model ID 5 Variables required for training/testing/prediction model
- RULE MATCHES
- CLAIM_TYPE_MOTOR_THEFT
- DISTINCT_TYPES_ON_CLAIM
- POLICY_CLAIM_DAY_DIFF
- REGION
- Data Source - csv file