AI Insurance

The system that is smart enough to take care each of the insurance thing to the coustomer and can also help in the operating part to the insurance company.

Background

The advent of the 𝐂𝐨𝐯𝐢𝐝-𝟏𝟗 has turned all of our lives upsides down. At present, the traditional way of interactng with the customer and insurance agent have been breaking since, INSURANCE companies are facing catastrophic challenges in providing proper facility and hasel free claim processing to its customers. Some traditional way of handling the customer and to file a claim or policy with help of agent is risky in this situation, visiting homes of various coustomer increases exposed contamination since it's time-consuming and often requires creating extensive schedule changes in one's daily routine. Moreover, Insurance-Company don’t have the capacity for handling large amount of customer just through the agents. Additionally, some agents may be often inadequate and lack personalization to handle the customer in a Smart way.

WHY AI/ML for Insurance-Companies?

Insurance is an old and highly regulated industry. Perhaps because of this, insurance companies have been slower to embrace technological change compared to other industries. Insurance is still steeped in manual, paper-based processes that are slow and require human intervention. Even today, customers are faced with time-consuming paperwork and bureaucracy when getting a claim reimbursed or signing up for a new insurance policy. Customers may also end up paying more for insurance because policies are not tailored for their unique needs. In an age when most of our daily activities are online, digitized and convenient, insurance is not always a happy customer experience.

That said, we are starting to see a global push by insurance companies to augment their technological capabilities so that they can do business faster, cheaper and more securely. In the past few years, there have been some prominent examples of insurers investing heavily in Artificial Intelligence solutions.

McKinsey estimates a potential annual value of up to $1.1 trillion if AI tech is fully applied to the Insurance industry. Of this, the business areas that can benefit the most are:

Sales and marketing: machine learning can be used to price insurance policies more competitively and relevantly and recommend useful products to customers. Insurers can price products based on individual needs and lifestyle so that customers only pay for the coverage they need. This increases the appeal of insurance to a wider range of customers, some of whom may then purchase insurance for the first time.

Risk: Neural networks can be used to recognize fraud patterns and reduce fraudulent claims. According to the FBI, non-health insurance fraud in the US is estimated at over $40 billion per year, which can cost families between $400–700 per year in extra premiums. Machine learning can also be used to improve insurance companies’ risks and actuarial models, which can potentially lead to more profitable products.

Operations: Chatbots using neural networks can be developed to understand and answer the bulk of customer queries over email, chat and phone calls. This can free up significant time and resources for insurers, which they can deploy towards more profitable activities.

There is a need for a technology platform to Revolutionize the operation of Insurance Sector and that's how our project Smart AI Insurance jumps in!

What is Smart AI Insurance?

Smart AI Insurance is the concatenation of Insurance Company and Customers which together stands as the Gateway of Insurance-Sector. Our software is a web application that utilizes cutting-edge modern technologies to Revolutionize the existing Insurance-Claiming and handling system! Smart AI Insurance is a complete AI-based Insurance handling for everyone, including Customers, Agents & is directly connected with the Perticular Insurance company. It has also a dataset of list of mechanics and are arranged according to the ratings and views for a perticular need of our choice. Please follow through to explore!

A further explanation of how each of these works can be found in the Engineering section below.

Features

AI-Insurance currently supports all of the following features!

To interact with the customer with an AI based Virtual Assistance.

It gives the coustomer all the possible details about the insurance policy they wants to know.

It can also file a claim for us in case we come out with an accident.

The insurance moderator can check the claims or policy request accordingly.

Manually applying for a new policy of insurance.

Manually applying for a claim to the company.

It can assign us or recommend us mechanics around us with some good ratings and views depending upon our car-damage.

It can also help us to check with the claim status.

Most importantly this project has a hastle free password-less login page with SAWO AUTH API.

It can detect the car damage type for the insurance company to assist the moderator to take action accordingly.

Distinguishable dashboard pages for all of the above.

Delve deep to explore more!

Engineering

System Architecture

Technology Stack:

1) IBM-Watson Knowledge Studio 2) Natural Language processing 3) IBM-Watson Assistance 4) IBM-Discovery 5) IBM-Virtual Recognition 6) React-Js 7) HTML 8) Java-Script 9) SAWO-AUTH API

So, how everything works?

Insurance policy documents are uploaded to Watson Discovery, and then annotated using Watson's Smart Document Understanding tool.

Mechanic review documents are uploaded to Watson Knowledge Studio, and then annotated to create custom entities and relationships.

User chats via web-application UI to talk to Watson Assistant.

Watson Assistant answers policy questions using Watson Discovery's querying capabilities.

The chatbot recommends a mechanic based on the type of damage that is done to the vehicle, and on the sentiment of the customer reviews.

The User can also apply for a new policy manualy through it which is backed by a insurance moderator.

Takeaways

What we learned

A lot of things, both summed up in technical & non-technical sides. Also not to mention, I had enhanced my googling and Stackoverflow searching skill during the hackathon and beside that I had learned a lot about the IBM-Cloud :)

Accomplishments

I had explored so many things within 24 hours. It was a tad difficult for me to collaborate with every stack including the frontend backend and the IBM cloud but I am proud of finishing the project on time which seemed like a tough task initially but happily implemented every thing what I had thought of. Lastly, I think the impact of my project could have a significant accomplishment. Especially, trailing the current scenario of COVID19, this could really be a product that both the people and the insurance-company can find useful!

What's next for Smart AI Insurance

As previously mentioned, Smart AI Insurance is one of the most technically sound projects I have made till now, and I would love to expand the wings of my project beyond the hackathon. Apart from fine-tuning the project, I am also planning to give the project with some more features in the operational side which can increase its usability more and can be more effective.

Some of them are:-

To implement a ML model which can help the company with the damage detection capabilities.

Facial recogniton, to find the database of the particular customer.

Number plate detection of the car, So the company can match the database with it.

we're also planning to integrate new user-intuitive features such as refined User access, easy checkout option, adding more such IoT-based inter-device support for maximizing our audience interaction.Though the project basically focuses on the AUTO-INSURANCE we can also give some of the features more to use in different Insurance-Sectors. Apart from these, a lot of code needs to be refactored which does include CSS improvements for desktop preview as I couldn't hit so much under 24 hrs. Overall, I hope that one day this project can be widely used among the Insurance community to redefine the existing & remove the backlogs.