Everyone is exposed to machine learning every single day. Do you use an Amazon Echo? iPhone’s Siri? Netflix? Google? If you said no to Google, we know you’re lying, says Interaction.
Being a go-to technology today, banking and insurance sector is one of the early adopters of machine learning. This rudimentary technology has several applications in this sector; some of which are chat bots for delivering 24*7 customer service, AI robots for self-service, etc.
The objective is to provide a personalized experience to every individual. There has been significant improvement in back-end operations and also fraud & cybercrimes has been reduced to a great extent. Taking about insurance, the technology helps in assiting people for taking up policies based on predictions.
Approximately 93% of Indian bankers go for automated decision-making by using humungous data.”
ML In The Banking Sector
The banking system in the country is reaping significant benefits such as better customer experience and transparency in work with the adoption of ML. Now, chatbots can make customer interactions easier.
India’s City Union Bank is the first bank to incorporate chatbots to answer customer’s query. ML is used to gauge the investment decisions across various companies and is also used for portfolio management in capital markets. ML has the potential to detect frauds in the banking sector, saving the customers trust in the Indian Banking system.
As per the 2018 report’s of Accenture Banking Technology Vision, “Its is believed by 83% of the bankers that by 2020 Humans and AI will work parallely which is 79% of the global average.”
In the backend part, ML has brought whopping differences. Banks can strategically use big data and analytics to upgrade the quality of their services. In short, ML is undoubtedly a boon to the Indian Banking system.
ML in the insurance sector
Insurance sector is that one sector where customers are sitting on the emperor’s throne. Insurance companies have to constantly dig out ways to upgrade their services and provide customer satisfaction. So, adoption of ML is imperative for getting astounding results.
As per Salesforce, “By 2020, 57% of business buyers will depend on companies to know what they need before they ask for anything. This means having solid prediction capabilities with your AI will be the key to keeping your customers. “
It can benefit insurance companies in the following ways-
- Personalised product offering– According to Accenture, more than 80% of insurance customers are looking for more personalized experiences. With AI and ML algorithms, insurance companies can enjoy the luxury of recommending personalised policies and products to the customers.
- Claim management– ML can wipe out the unnecessary steps and streamline the process of claim management. This, in turn, would create a good customer relationship.
- Fraud detection– Insurance companies are prone to frauds and attacks. ML can curtail the situation by automating the claim assessment and detecting potential frauds patterns.
“AI software will grow from $1.4 billion in 2016 to $59.8 billion by 2025”, says Tractica.
In short, AI and ML are angels that can bring good luck to Banking and Finance verticals. It holds a felicitating future, and if implemented correctly, can be a great fortune to any business. These verticals can proliferate their operations with the help of AI and ML.