4 ways Conversational AI Platforms can increase conversions for Banking and Insurance.
Products and services offered by banks and insurance companies can be pretty confusing and complex. However, they are some of the most crucial and important products we need today.
Banks offer a multitude of products and services such as individual and family accounts, salary accounts, PF accounts, wealth management schemes, various FD schemes, etc. and choosing the right one can seem confusing at times.
The Insurance sector takes the confusion to a whole new level.
With so many types of insurance products and offerings, one may find it difficult to fully understand the meaning of all the options presented and which insurance plan, term and offering would suit the person and their Insurance needs. Not to mention the many additional add-ons and covers such as ULIP linked insurance plans, zero depreciation cover, roadside assistance, various health insurance covers etc. only add to this chaos and confusion.
Today, we are seeing increased digital adoption in the banking and financial services industries across the globe. This change is driven primarily due to the increased use of smartphones and affordable data services and the comfort that users have with adopting digital mediums to transact. Additionally, the comfort of accessing online services in other areas has also paved the way for banks and insurance providers to offer digital-only propositions.
People no longer have to go to a physical bank branch or insurance provider’s offices to get their financial work done. However, due to the plethora of offerings available, there is confusion and lack of knowledge on the customer side regarding the best banking or insurance scheme.
Many banks and insurers face a challenge in converting users, providing them a positive user experience and retaining them online.
A Digital Insurance Survey conducted by PwC in 2019 showed that 47% of insurance purchasers in India depend on online information channels to make decisions. However, banks and insurance companies struggle to drive traffic on their digital platforms, retain their existing customers thereby missing out on opportunities for up-selling and cross sell relevant products to them. And even in cases where BFSI brands can drive users to their online platforms – conversion rates are extremely low.
Multiple banks and Insurance providers are using technology and innovation to connect better with their online users, build a connection and drive more conversions.
Conversational AI and Digital Sales Reps is one such method. Through the use of conversational AI – BFSI brands can increasingly convert traffic to customers, improve retention and improve customer lifetime value.
How? Let’s take a look!
1) Creating Human-like interactions and individualised solutions at scale – Using AI Digital Sales reps.
A second order effect of BFSI going digital is the lack of face-to-face interactions between customers and agents.
Users are looking for specific solutions that can help them and not a one size fits all approach.
There is a need for BFSI brands to create trust and maintain relationships with their digital customers.
However, the challenge is to provide insightful and customised guidance to customers that will help them make the right decisions – the same way as a trusted financial advisor would.
"Let’s face it – people do not like being sold to – they like being recommended to"
Today, people expect high-quality, frictionless digital interactions and offerings that have been tailored for them and their needs.
Banks and Insurance providers need to bring back the personal connection and interactions they have been running on for centuries, which has now become difficult to replicate online.
One way to do this is through the use of Conversational AI assistants that make the customer experience more individualised, human-like and human-friendly.
Banks such as Citibank, and JPMorgan have introduced digital, self-service banking options, via automated financial assistants, to perform tasks like tracking budgets, product discovery and making payments.
Additionally, these automated financial assistants have helped customers with curated suggestions and recommendations basis the bank’s offerings – creating a heightened customer experience and a deeper level of personalisation and engagement.
These AI Automated financial assistants can efficiently
Have a conversation and understand what the customer wants.
Understand the context of the customer’s needs.
Adapt the conversation in real time to suit the language and slang of the customer.
Recommend products and services based on the customers preferences and previous actions.
Automate lead scoring and enrich the CRM in real time – for picking up conversations later.
2) Acquisition, Up selling and Cross Selling through AI driven Conversations.
With the complexity of financial and insurance products, about 85% of customers want to learn more about the specifics of a product, understand its’ nuances and in most cases – prefer to speak to a representative to understand these.
What if the same degree of conversational ease could be translated digitally and at scale?
A smart AI digital sales representative will ask pertinent questions about the prospect’s age, family members, use other factors and data points to then suggest a suitable banking or insurance plan tailored to the user’s needs. .
By having personalised, context rich and tailored interactions with current policy owners, ORI’s Cognitive AI Sales tool – Convert, launched for a global Insurance brand increased customer engagement by 12% and up sell instances by 8% within a span of 3 months.
ORI’s AI Platform – Convert captured all previous customer conversation information, CRM data and behavioural insights using the same to preemptively guide prospects to closure, simultaneously enriching the CRM with new conversational analytics and insights.
Up Sell and Cross Sell using Conversational AI:
Conversational AI assistants have helped banks and insurance providers up sell or cross-sell products and services through a personalised and focused strategy.
Banks and Insurance providers can use conversational insights to build custom audience groups and behaviour based cohorts to contextually up sell and cross sell products with hyper personalisation.
These insights can be used to create highly targeted and personalised automated outbound conversational campaigns using Google RCS, Whatsapp Pixel and conversational ads.
Let’s understand more about cross sell instances through an example:
A male in his late thirties that is purchasing a car insurance would most likely have a family. Through conversations via the digital sales rep – data on number of family members, age of family members, locations etc can be captured.
This can be used to send personalised communication around a possible family health insurance, Term Insurance etc – thereby increasing the engagement with the user and the users Life Time Value with the brand.
Another example would be : If an existing customer having health insurance has put in a claim, he would most likely be looking to increase his Insured amount by opting for an Insurance Top-up or also purchasing a family health insurance plan.
3) Capturing Real time insights, intent and context through conversations.
KAI – is a conversational AI platform developed by Kasisto (NYC, USA). It has helped banks decrease the call centre volume as customers are given self-service options and solutions. These digital assistants on the platform also give the customers calculated recommendations to help them make everyday financial decisions.
Another example is the money-saving AI assistant: Trim.
The smart software connects to user accounts and keeps track of all spending activities. The assistant helps users eliminate unnecessary subscriptions, offers suggestions for services like insurance and even negotiates bills. According to a VentureBeat article in 2016, Trim could save $6.3 million for over 50,000 users.
Conversational AI platforms like KAI and Trim work the same way a human financial advisor would. However, these have a layer of machine learning and are able to manage these recommendations at scale, while at the same time sending data back into CRM and Marketing automation systems to create behaviour based cohorts and user segments at a granular level.
These insights help re-target and re-engage customers through marketing automation tools, conversational AI tools and digital sales reps.
These insights can also be extremely useful for sales agents, helping them strike a relationship with customers and tailor the most relevant recommendations for customers.
4) Real time feedback through conversations.
Knowing what customers and users are saying about your brand can draw deep insights on customer perceptions and help understand their pain points.
Banks and insurance providers, using Conversational AI platforms can truly understand what customers and users are actually saying about them and the questions they have about their offerings.
These insights can give deep understanding of user perceptions and pain points, helping improve customer experiences, product positioning and communication.
Understanding customer conversations can help create better value propositions that clarify issues immediately and provide a simple communication path that makes customers feel comfortable and connected.
Using conversational analytics can give some in-depth insights on consumer perceptions, behaviour and intent.