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5 Insurance Front-Office Processes You Can Improve with AI

Nivin Simon
6 minutes, 5 seconds read

Amidst the growing footprint of Insurtech around the world, Insurance service models continue to evolve for both front and back-office processes. Currently, InsurTechs are using AI in three main areas: Customer Experience (58%), Product Innovation (43%), and Process Improvement (19%) — according to a McKinsey report. An organization’s ‘Front Office’ strategy will need to embody intelligent sales force automation, call-centre management, help-desk applications, product configuration and risk assessment tools. Insurance Carriers are restructuring these operations with an outward focus — aimed at improving interactions with their customers. 

While the Insurance back-office is focussed on streamlining in-house operations, the front office is responsible for driving customer experience, engagement and behaviour. However, most front-office operations deal with repetitive customer-facing jobs. Using Artificial Intelligence-based technologies such as RPA, tasks that require human mediation can now be handed over to automation technologies that imitate human interactions. Gartner estimates 20% of RPA will be cloud-based by 2022.

The real benefit of undergoing automation transformation is that both the front & back office can now be contextually linked in a smart manner — avoiding ‘working in isolation’ for extended periods. Customer-facing agents and reps can access information across the back-end more reliably and faster than before. Automating even routine tasks such as updating customer information, performing security checks, fetching product details or updating complaint forms — can reduce resolution times and the potential for manual errors.

This allows the front-office staff to focus on the most pressing matter — the relationship with the customer.

Customer servicing can now take place at incredible scale and complexity using chat, mobile and voice self-service tools. For example, speech recognition can capture what type of service to offer the customer (eg: update contact information, access policy details etc). These tools can also detect ‘anger’ or ‘frustration’ from the tone of voice and the information is passed to front-line reps who can quickly resolve an issue. As a result, remote diagnostics and self-service tools will see enhanced adoption over the coming years. The market for AI-enabled technologies in the claims process alone will be worth $72B by 2020.

5 key front-office operations that can be improved with AI

  1. Underwriting
    The most central function within the insurance value chain is to price risk. Using AI, the insurance underwriting process is now empowered with real-time insights derived from models analysis tons of customer-centric data.

Using historical data, machine learning models can be trained to understand ‘known risks’ based on experience. For ‘unknown risks’, IoT sensors play a crucial role — by delivering a real-time picture of an ongoing operation. This allows for a second model to infer risk based on current data and the entire historical record of that specific process.

Armed with in-depth knowledge about risk, insurers are moving from traditional risk pricing to a more proactive risk mitigation role. Through this new approach, carriers can set up real-time risk alerts, predict fraud and more accurately forecast ‘claims occurrence’ across the customer life cycle.

  1. Policy Administration
    A policy administration system is a backbone that manages all the policies within an insurance company. From the first point of interaction to fetching data from the back-office — most, if not all core operations run through this system. However, most insurance organizations still rely on legacy systems that require tremendous workaround using manual efforts.

    According to a study by Celent, nearly 45% of Insurance CIOs identified disconnected and duplicative legacy systems as a key inhibitor to digital transformation.

    Today’s challenging market dynamics and competitive pricing pressures are changing this approach. There are several areas worth investing in for carriers such as image & voice recognition to capture and authenticate customer information at the initial contact stage to intelligent entity extraction tools for understanding even handwritten text from a physical document.

    Automation enhancements help drive policyholder retention by improving connectivity to the back-end and delivering the most optimal outcomes for front-office workflows.
  1. Claims Management

Claims are the most widely scrutinized function within the insurance value chain. Most claims servicing is performed by human agents over the phone. With speech recognition, these conversations can be automatically transcribed/ translated in real-time. This frees up more agent time to handle greater issues while leaving automation enabled self-service to handle the most basic customer queries.


Claims assessment or loss estimation itself can be performed remotely using image recognition tools linked to algorithms that can calculate the payout for the policyholder.

Without the need for human intervention, straight-through processing can be dramatically improved by reducing processing time — allowing human agents to react faster to policyholders demands.

Also, read – How AI can settle claims in 5 minutes!

  1. Marketing & Sales Distribution
    According to Salesforce, only 36% of the average salespersons’ week is spent selling. Human sales reps typically spend a large portion of their time nurturing unqualified leads. With sales funnel maximizers, like LCA, reps can get quick access to leads that have been scored, prioritised and allocated for the right agent to optimize conversions.

    Distribution and sales chains are moving to a completely digital and affinity-based ecosystem. Chatbots and virtual agents can, therefore, play a critical role in increasing cross-sell and up-sell opportunities. These AI-enabled tools are fitted with Natural Language Processing (NLP) capabilities to contextually interpret the interaction with the customer.

    AI also leverages predictive analytics to produce behavioural insights when pitching the customer — allowing the agent to ask the right questions, address unmet needs and resolve anticipated near-term challenges.

  1. Product Personalization
    Using Machine Learning algorithms to precisely price risk, allows Carriers to understand the complexities involved in new product development — especially measuring the ‘unknown risks’ involved in creating new product lines.

    Data (both historical and IoT derived) coupled with predictive analytics can offer more personalised guidance to insurance buying. InsurTechs are poising themselves strategically in this area, ahead of the large carriers, to attract a new and younger customer base. Companies like MetroMile, Trov and Lemonade have been able to create unique offerings with AI-derived insights fine-tuned to the individual, while also charging much lower premiums than the market.

    New customers are able to buy convenient, sachet-type, even pay-as-you-use modelled insurance products for protecting their assets (mobile, laptop, home appliances, short travel, vacations etc). This has brought about an appetite for on-demand insurance where insurance can be bought, queries can be resolved and claims can be processed, all within a few minutes.

Other Customer-Facing Areas improved by AI

1. Proactive Front-Office Processes 
2. Precise Risk Mitigation/Active loss prevention
3. Chatbots and Robo-advisors 
4. Real-time Underwriting 
5. Accurate Claims Processing 
6. Direct Marketing & Cu0stomer Retention
 7. Bespoke Insurance Advice
 8. Understanding User’s Emotions 

Forrester predicts the impact of intelligent automation — through evidence in ‘the service desk’. They claim: automation will eliminate 20% of all service desk interactions, by the end of 2019. Enabling human workers with digital assistants in the insurance front-office has scope for very high disruption. Human agents are prone to making repeat errors that automation equipped with AI can fix easily — especially in routine and repetitive tasks.

Carriers, now have the opportunity to boost their market position by improving agent productivity, reducing operational inefficiencies like reprocessing, producing errorless transactions for customers and thereby creating an uninterrupted service chain.
Mantra Labs solves the most challenging front & back-office operations plaguing the Insurance value chain. To know more about our work in this space, reach out to us on hello@mantralabsglobal.com.

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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.

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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.

Gartner-Hype-Cycle

Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.

Emotion-Intelligence-Market



Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.
Gartner-Data-Analytics-Trends-Forecast-2019


Source: Gartner Data Analytics Trends for 2019


For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at hello@mantralabsglobal.com

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