How are you leveraging AI technology for customer finance offerings?
We are in the process of implementing AI in our organization and have recently taken a few steps to commence the journey. In the first stage, we are trying to master the usage of data that has been accumulated over the last 10-11 years of our existence. We are trying to develop hypothesis/algorithms on which we can do machine learning to solve specific problem statement based on historical data.
We have attempted small PoCs in the space of fraud management where we would like to use the available data and see the past trends of detected frauds to stop a repeat incidence. We have focused on understanding how we can leverage this information to predict the likelihood of fraud at the time of issuing a policy. The risk could be from geography, product line, customer/agent profile, the channel of sourcing, etc. At a macro level, we are also trying to define a broad framework/ecosystem/ methodology that can be leveraged in other use cases. And then, of course, there are a number of possibilities where AI could be leveraged to understand customer requirements/behaviour and have a more focused approach to fulfill their needs & requirements.
Which automation technology do you think has disrupted the insurance industry the most – customer-facing or backend processes automation?
Automation technologies have disrupted both customer-facing and back-end processes automation. There have been significant efficiency gains at the backend processing mostly due to workflow automation and more recently with the advent of RPA, which is likely to get even more pronounced, getting coupled with AI. Similarly, customer-facing processes have seen and continue to see a huge improvement/disruption to make it simplified, easy to understand, and navigate for the end customer. However, there’s still a huge potential that remains to be tapped on both customer-facing and back-end processes automation, where more and more customers would have access to self-service, instant gratification for most of the transactions, across a multitude of channels. Backend process simplification, modernization, along with better UI / UX for customer-facing applications and aided by technologies like ChatBots, RPA, AI, etc. can make this possible in the next 12-24 months.
Do you think that the use of chatbots and IVR can help customers make correct financial decisions?
I think this is a widely debated question because we believe, or want to believe, that chatbots can actually do a lot of things as efficiently and effectively as humans. Chatbots can be very efficient in collecting information, capable and methodical in terms of navigating the customer through a structured process of data gathering. But, I do not think they have evolved in today’s era to make or assist in creating a financial decision for a customer. This is because as a customer, even if all factors remain the same – age, gender, education, similar occupation, etc. the way they treat their financial decisions could be vastly different. And this kind of difference in decisions is not something that a chatbot would be able to distinguish easily. Chatbots can take responses on several parameters, and make it rather convenient for the customer to share informationthat can be made available for both humans and machines to process.
However, financial decision making, I think, is still a factor of many more things that are slightly subtle but are very deeply ingrained in the human mind and possibly our genetic build-up. So, I think chatbots still have some way to go before they could genuinely assist in making those financial decisions for the customer. They can help in making the information gathering process much more intuitive, structured, and comfortable, helping the customers in comprehending information in a much-simplified manner. They can take out the tediousness of the data collection process, gathering it accurately. But, to genuinely assist in financial decisions, chatbots have a long distance to cover. IVR can at best help in resolving some of the queries online or perhaps register a request etc., in my opinion, they are not going to have a play in financial decision making, in their current avatar.
Do you think the increasing occurrence of ‘fake news,’ affects social media marketing for the insurance industry?
Prevalence of “fake news” impacts social media marketing for most of the industries, including financial services & insurance industry. Generally, exposure to fake news might push us towards taking a decision that we would not have done under normal circumstances. I think the impact of ‘news’ or ‘fake news’ cuts across our day to day working, day to day living, and day to day decision making. Financial services perhaps are one of the largest industries to witness an impact because of the advent of fake news. For instance, the news of a bank going bankrupt might result in many FDs being encashed or money being withdrawn from the savings account and transferred somewhere else. Fake news of companies going bust affects shares, and they might be sold at throwaway prices. For insurance companies, one might witness the surrender of existing policies and may see an impact on the sourcing of new policies. So, businesses could get impacted drastically by fake news about an industry, organization, or in general. Insurance and financial sector possibly have the most significant effect as people buy promises that are long terms like 30 / 50 years or even 100 years. So, fake news is something which could adversely affect the trust levels and brand image of the company — having a significant impact on the existing and potential customer base. So with increased occurrence of ‘fake news,’ there’s a definite adverse impact on the overall social media marketing, where overall effectiveness of the campaign could go down, due to lower trust levels.
“Automation technologies have disrupted both customer-facing and back-end processes automation for financial and banking industry.”
Mayank Bhargava, CIO, DHFL Pramerica
