I recently saw a tweet from Mat Velloso - “If it is written in Python, it’s probably machine learning. If it is written in PowerPoint, it’s probably AI.” This quote is probably the most accurate summarization of what has happened in AI over the past couple of years. A few months back, The Economist shared the chart below that shows the number of CEOs who mentioned AI in their Earnings calls. Towards the end of 2017, even Vladimir Putin said: “The nation that leads in AI ‘will be the ruler of the world.” Beyond all this hype, there is a lot of real technology that is being built. So how is 2019 going to look for all of us in the insurance world?
The field of artificial intelligence has always envisioned machines being able to mimic the functioning and abilities of the human mind. Language is considered as one of the most significant achievements of humans that has accelerated the progress of humanity. So, it is not a surprise that there is plenty of work being done to integrate language into the field of artificial intelligence in the form of Natural Language Processing (NLP). Today we see the work being manifested in likes of Alexa and Siri.
One of the challenges insurers face when implementing any new cloud-based application into their workflow is the integration of both internal and external data. Gaining access and permission to use internal data can be the first hurdle. Adding the requirement to format the data in a specific format can be a show-stopper.
Insurers have been using data to improve the customer experience of their policyholders for quite a while now. This data is typically explicit data that is gathered by asking policyholder specific questions. By gathering implicit data, insurers can now understand the sentiment of their customers at any given point of time during their customer journey, without even asking them.
Insurers have a near-constant stream of unstructured data at their disposal that can be used to drive growth by improving policyholder retention and identifying cross-sell and upsell opportunities. One of the challenges for insurers is sorting through this mountain of unstructured data quickly to gain an accurate understanding of the sentiment of their customers in real time.
Enterprise applications belong to a vibrant ecosystem and consequently the data they generate is large and varied. Enterprises both benefit and suffer from this nature of application and data.Whenever a new application is to be deployed in an enterprise that integrates with the applications in the ecosystem, the precondition is an 'expansive data definition with referential value' on day 1 to start integration. Traditionally, this approach to data integration involves identifying a target data structure, and force fitting data from all sources into it. This is done to ensure a 'seamless' integration - never mind the loss of data considered irrelevant.
According to the Coalition Against Insurance Fraud, at least $80 billion in fraudulent claims are made annually in the U.S across all lines of insurance. This translates more than $400-$700 per year in increased premiums for each American family.
Bajaj Allianz Life Insurance Company recently hosted a unique insurance summit focused on putting customer experience first. The event titled Future Perfect-Customer First Insurance Industry Summit 2018 was a full-day event that was attended by 21 of the 24 insurance companies that operate in India. While the focus was life insurance, the summit also saw participation from a few general insurance carriers.
Customer Experience (CX) has seen a paradigm shift from just a good-to-have-function to one of the key differentiators and now a core strategy function for many organizations. CX is no longer limited to knowing what your customers feel about you, instead it includes taking essential actions to enhance a customer’s overall experience (by converting an unhappy customer to a happy one). Companies are offering best-in-class customer experiences over their competitors to grow faster and to be more profitable.
2017 has been a year when ML/AI technologies have become mainstream, and businesses are conversant with their application and possible use cases. 2018 will, however, be the year when trends from 2015-17 will finally come into maturity and we will be able to see results. Commercial application of blockchain (beyond Bitcoin), wider acceptance of enterprise SaaS solutions, and optimization of investments in data lakes – are just some of the examples we can think of. Customers too, are now beginning to understand more about data privacy and security, and want to be more in control of their own data. It seems that finally in 2018, technology and business will move ahead together.