Personal Accidental Claims & Investigation Audit Automation Case Study for SBI General Insurance by Artivatic
Use Case & Objective
The solution needed to help in enabling claims team to faster asses the intimation data, documents reading & processing, data match among multiple documents, building investigation audit for conducting investigation and providing final claims assessment with adding multiple processes and rules already available with SBI General Insurance. The idea was to digitally enhance the PA process for reducing time, assessing better, building more AI Based risk /fraud triggers and reducing processing cost.
About SBI General Insurance
SBI General Insurance is a joint venture general insurance company between State Bank of India (SBI), the largest state-owned banking and financial services company in India and Insurance Australia Group, a Sydney based multinational insurance company. SBI owns 70 per cent of the total capital and IAG 26 per cent of the capital. Other investors are Axis Bank Asset Management Co. Ltd and Premji Invest, holding 4% of the total capital.
The company offers a wide range of insurance products and services, in the retail and commercial space.Its offerings include personal accident, home, health, travel and motor insurance in the retail space and aviation, marine, fire, liability insurance, engineering and construction in the commercial space.
Key Challenges & Issues for Personal Accidental Claims
>95% Manual Process
>20-90 Days Turnaround time
<10% Data Driven Insights
Error-prone insights
No Scoring, no risks, no profiling
Legacy process and too many systems
Manual video or image based inspection
100% Surveyor dependent claims process
Bad customer experience
Increase in fraud cases
Investigation documents reading and analysis manual
Artivatic's Approach
Solutions provided by Artivatic to meet SBI GIC Personal Accidental Claims requirements:
Historical Learning based in-depth trigger analysis for risk & fraud activities
Document digitization for quick claims processing
Document data match with internal and external environment
Using 3rd party or external data like news, FIR, google map, trends, risks, social, historical, triggers, matching etc. provide audit for claims intimation assessment for investigation need
Document extraction & Matching for possible key triggers and authenticity check
QC process, Audit process in bulk claims check
Provided system for probability of claims investigation need based on multiple data attributes
Reasons based on Machine Learning approaches was provided for each claim’s investigation need
Interested in knowing more ? Write to contact@artivatic.ai
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