Have you noticed that Insurance has suffered a loss in trust more than any other in the financial services sector? Long call centre queues, damaging publicity around pricing and disappointed claimants have undermined customer confidence.
Have you also noticed that we are increasingly putting less trust in each other as a society? Once trust is gone, it is hard to get back.
As we try to put the pandemic behind us, there’s a burdening need for the industry to act and start building a better customer relationship. Overcoming inherent views will be difficult, and building trust will be vital to success.
All is not lost. We live in exciting times, and technology such as AI-driven analytics and new data from connected devices promise much and could help turn the ship around. So, how could the industry take hold of this tech uprising to move from a risk mitigation model to a justly trusted advisor?
If we were to give Insurance a revamp, starting with what we have today, what might it look like? Here we consider the essential constraints that are holding the industry back, the engagement challenges, and the importance of establishing customer trust. Finally, we can imagine a more predictive insurance model integrating automation, deep learning, and external data ecosystems, enabling more meaningful interactions with our customers building long-term loyalty.
CURRENT STATE OF INSURANCE
Insurance companies face numerous challenges as they try to offer the best services for their customers.
Let’s examine the three most prevalent issues.
Poor Reputation
We all need Insurance, and the very necessity often makes its purchase a distressed one where the price is the prominent determining factor. Lengthy policy wordings containing confusing language, complex pricing, and poor claims experience result in a lack of transparency, with the odds seemingly favouring the Insurer.
This picture of negativity is regularly exposed in the media by watchdogs, encouraging direct action by consumers at large. Added to this the spectre of personal data breaches and increased use of sophisticated algorithms which run the risk of customer marginalisation, it is no wonder that trust in Insurance is sketchy.
Research by the Chartered Insurance Institute shows that customers want to know that they can have confidence in reputable companies. The most trusted insurers strongly correlate customer trust and customer loyalty.
Hughes, Chief Executive at the Consumer Intelligence, said,
“Customer trust is a key element to standing out in an industry where customer perceptions are traditionally low. Brands that focus on building trusting long-term relationships with their customers thrive and grow. Customers do not want to do business with a brand they cannot trust.”
Internal Constraints
The industry has been battling to address the build-up of old systems and processes for decades. The impact of the pandemic has compounded matters, as Gartner research suggests that.
“60% of insurers reduced or stopped their IT spend in 2020.”
It can be hard to justify the commitment required to change these systems when looking through the investment lens. By analysing budgets, we can see the bulk of spending is often directed to keeping the operation running and maintaining the status quo.
The fundamental issue with these older systems is that their design is centred around traditional value chains and, by their virtue, are very transaction orientated. Agility and business cycle times were not a consideration, and as a result, a deep understanding of the underlying workings is needed to enable the required re-imagination. This knowledge is limited to a few long-serving individuals whose presence decreases every passing year.
Moreover, these older systems can cause a high degree of variability in team performance. We shall explore this phenomenon in more detail in a future post and how this needs to be addressed to unlock true enterprise agility in Insurance.
Lack of Capabilities
The challenge faced is not simply a technology issue.
We all lead by experience, and many of us don’t have the knowledge or capabilities to drive the scale of transformation needed. Such change must cut across many areas, including technology, process and culture.
Team silos make it hard to operationalise new ideas. Take the example of a Data scientist who has developed the latest algorithm. Working predominately in isolation, they struggle to articulate to the broader business the value of this work and how to get this into the operation to drive new insight.
Insurance is inherently complex. As a result, it seems to attract very strategic mindsets who demand to understand in complete detail how things work. This analytical approach is needed; however, too much detail orientated thinking can hinder efforts to transform at scale.
As Don Marquis put nicely,
“Procrastination is the art of keeping up with yesterday”.
What is needed are more individuals who can take a holistic view. These intrapreneurs see possibilities that have the potential to change the landscape of their world fundamentally. They imagine possibilities that others don’t see, and they engage people with genuine excitement and clarity of what is achievable.
We’ve considered the significant internal constraints; now, let’s contemplate how this impacts customer engagement.
THE ENGAGEMENT CHALLENGE
Insurance is very much out of sight, out of mind, with McKinsey reporting that, on average, we only have four interactions per year with our Insurer. Compare that to over 100 with our bank, and you can see why it is so tricky for Insurers to drive significant engagement.
Limited Interactions
These limited interactions make it hard to stand apart, engage and build relationships.
Typical insurance communications do not add meaningful value, such as renewal documents. The level of service will naturally influence customer opinion, with just one lousy experience heavily impacting their view.
Added to this, expectations around the quality of customer service have increased. Building a web portal or rolling out an app on its own is no longer sufficient. Instead, customer’s seek meaningful interactions which create awareness, knowledge, value and ultimately build loyalty and trust.
Given the importance insurance plays in our lives, there is a real opportunity for insurers to provide resources and information to help address customers financial, physical, and emotional wellbeing. This content should be intelligently personalised and driven by the needs of each customer.
6 Ways Insurers can build customer trust & loyalty
- Offer excellent customer service
- Publish customer reviews and testimonials
- Be transparent
- Ask for feedback
- Create a loyalty program
- Develop robust ESG strategy, demonstrating sustainable & ethical practices
Use of Customer Data
Granular customer data will need to be utilised to create engaging, personalised content.
Three types of personal data
- Self-reported data – such as email addresses
- System-generated data – such as geolocation information
- Profiling data – combining self-reported, system-generated, & other data
However, the utilisation of more data presents a new challenge. Namely, we all have strong feelings about when and how our personal information is used.
Insurers need to understand how customers value their data and provide clear information and controls for its use. This awareness and authority become even more critical when considering the impact on those individuals who may not have access to the necessary technology or are part of high risk or vulnerable groups.
As you might expect, the more trusted a brand is, the more willing customers are to share their data. It is paramount that Insurers take the lead in educating consumers about their data. As an example, look at Facebook’s privacy basics. These are easy to understand and clearly explain what data others can see and, more vitally, how an individual can control activities based on their personal preferences.
It is hard to trust a company if we do not understand how our data is used.
Artificial intelligence holds the key.
One of the key triggers in generating the necessary information is the explosion of connected devices (IoT) which have become commonplace in all aspects of our lives.
These devices collect large amounts of system data in real-time about the operation of an object – think of a telematics box in a car or a sensor monitoring water pressure in a house.
4 AI-related trends shaping Insurance
- IoT Data – enables a deeper understanding of customers
- Process Automation – improving efficiencies & shifting customer expectations
- Intelligent Interfaces (APIs) – seamless sharing of data across industries
- Cognitive Technologies – processing of image, voice, and unstructured data
Intelligent algorithms can rapidly process this information, automatically learning from patterns or features in the data. By better harnessing this data, Insurers can learn directly from life events and find ways in the causes of particular risks. By identifying the beginnings of these patterns in real-time, preventative interventions can be made before events play out.
This approach can be used throughout the lifecycle to enable customer engagement to grow over time.
Encouraging increased use of data
So how do Insurers encourage greater use of IoT?
A recent survey revealed that customers generally feel using personal data is a fair trade when the information improves a product or service.
Product managers should be looking to design new product offerings which exhibit gaming like characteristics. Insurance could, by de facto, become very engaging by appealing to what we all crave, namely instant gratification and having the illusion of control. For example, customers could directly reduce their premiums by moderating their driving behaviour by utilising telematics data.
THE INSURANCE PROPOSITION OF THE FUTURE
Lastly, let’s imagine how AI technologies and access to new data ecosystems could transform the future of Insurance.
Preparing for accelerating changes
The adoption of new AI technology advancements will continue at pace, as Insurers seek competitive advantage driven by the need to offer intelligent, personalised services.
C-level executive boards will sponsor ambitious digital transformation programmes to create holistic customer experiences. Having the right culture will be vital to attracting and retaining the best individuals who possess the necessary mindset and skills to work in a fast-paced, ever-changing environment.
Exciting new reskilling programmes will be developed to enable teams to continue to acquire new skills. They will gain a detailed understanding of AI-related technologies and trends, including integration of automation, deep learning and external data ecosystems.
All roles across the organisation will be supported by a mix of semiautomated and machine-supported tasks which continually evolve. This will maximise the operational efficiency and effectiveness of the organisation whilst delivering a first-class personalised service.
Data will, without doubt, be the most valuable asset for an Insurer. To maximise worth from this asset, internal capabilities will be augmented by a rapidly growing sector of Insurtech companies who offer hard to find data science competencies and proprietary data platforms, enabling rapid deployment of new insights.
These AI performs, built on modern cloud-based architecture, will be highly performant in processing extensive data from various sources. Insurers will seek to secure access to new information that enriches and complements existing internal data sets. This will be achieved cost-efficiently by using the latest API practices and technologies.
Distribution
Insurance policies will be issued immediately to a broader range of customers in the future.
As connected devices boom and pricing algorithms mature, these new products will tailor our behaviour. Product offerings will constantly adapt to usage and individuals’ behavioural patterns.
Distributed ledger blockchain technologies will enable smart contracts, supporting easy identification and verification of customers and allowing instantaneously authorised payments.
Underwriting & Pricing
Ultimately, products will become disaggregated into micro-coverage policies, ensuring an item or a particular scenario.
Think about insuring just your phone battery, electric car battery, or washing machine. Car insurance will all be paid according to the miles we drive.
This will all be made possible by sophisticated algorithms and deep learning models. Fuelled by internal data and a plethora of external data sources, pricing in real-time based on usage and dynamic risk assessment will be possible. In turn, these advancements will empower customers to decide how their actions influence coverage, insurability and pricing.
Fairness will be moderated by public policy, which will require transparency and traceability of algorithms whilst limiting access to specific sensitive and predictive data to avoid bias.
Claims Management
Advanced algorithms will control the assignment of claims, significantly increasing efficiency and accuracy compared to today’s operating models.
Claim processing times will be reduced to seconds as intelligent decision engines evaluate outcomes and determine the best following action for customers.
IoT devices will proactively monitor and detect issues. Customers will be altered instantaneously, avoiding potential loss, catapulting Insurance into the realms of sophisticated preventative service.
CONCLUSION
The impact of the sharing economy and technology enhancements is redefining the Insurance industry. Seamlessly leveraging data will be paramount, and Insurers ignore this shift at their peril.
The future of Insurance will demand that the customer is put at the centre of change and that the technology enables meaningful interactions. A new, bold approach is needed to break the cycle of creeping normality. Capacity must be freed up to undertake this enterprise-scale transformation.
Significant business opportunities await the brave.
- Improved customer experience.
- More precise risk identification.
- Broaden coverage.
- New types of Usage-based Insurance coverage.
The winners will be those Insurers that maximise the use of new technologies to create innovative products, harness cognitive learning insights from new data sources, streamline processes and lower costs.
These will need to exceed customer expectations by creating meaningful engagement and establishing Insurers as justly trusted advisors.
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Exciting times!