Gone are the days when insurance and nbfc sector was relying completely on manual processes. Today with the emergence of AI and data-driven business decision making coupled with the application of IoT technologies there is a radical transformation of business processes in insurance and other financial services, like straight through processing becoming mainstream.
Let us look at different use cases:
1. Insurance Models:
Consider the recent proliferation of usage-based insurance models. These models are a product of a comprehensive AI applied on data collected by telematics and IOT devices. The transformation from legacy fixed premium models to these modern pays as you go models is via leveraging AI and driving data to more accurately profile driver and trip specifics to offer accurate micro insurance amounts. So the best possible use case of AI is usage-based insurance.
2. Customer Profiling
Via the extensive application of AI to customer profile related data and transaction data it is possible to get to know your customer much thoroughly and accordingly use it in multiple scenarios: premium pricing, detecting potential defaulters, etc.
3. Risk Management
AI has radically transformed the way in which data is used to streamline risk computation across financial services including insurance. An AI-based risk computation allows for factoring in more dynamic and accurate analysis of a case. AI-based risk manager, for example, will reward a safer driver by analyzing driving behavior.
4. Personalization
By extensive usage of AI-based analysis of customer profiles, it is possible to achieve N=1 offerings, a hyper-personalized offering to the level of unique offering for every individual. So it is possible for customers to get personalized products to be it from insurance providers or finance providers.
5. Claim Settlement
Today by the usage of vision and rich AI technologies we can look at gathering real-time information related to accidents etc and use the same to be made available to insurance companies to enable assessors to do a real-time gathering of information. This helps in the faster settlement of claims.
6. Fraud Detection
Usage of AI empowers finance services providers to be aware of fraudulent transactions in real time as compared to earlier. Depending upon the anomaly detection techniques in use fraud detection is getting more real-time or early warning across several finance use cases ranging from insurance to nbfcs.
7. End to End Automation
Several front end and back end processes in finance sector ranging from KYC, to claim to process, all are now leveraging the power of automation tools like RPA and other complex AI-powered automation technologies. Example for certain categories of new insurance applications it is possible to issue policy straight through.
8. Disruptive AI Enables Processes
Using face authentication and AI processes like that several processes can be disrupted like for example detecting fraudsters in real time etc.
9. Underwriting
There is a sense that via penetration of AI there will be a time when manual underwriting will be eliminated. All this due to AI based deep learning algorithms taking over the underwriting process, a process already begun.
10. Customer Service & Interactive Services
Much like other industries financial services including insurance are going to deploy chatbots for customer service tasks.
11. Financial Advisory
Via AI it will now be possible to generate specialized advice for a customer in terms of financial plans. So personalized financial robot advisors will be the norm in the future.
12. Smart Contracts
Via AI In conjunction with smart blockchain interfaces, insurance, and nbfc s will be able to provide decentralized automated processes which involve multiple parties like trade finance.
