May 2019

The Rise of Intelligent Automation in Personal Lines Insurance Part 1 & 2

In part one of our blog, we discussed intelligent automation and its practical applications in the insurance lifecycle.

In part two we explored the key challenges insurers face when trying to introduce new technology into their business, expected ROI and business outcomes.

Overview

www.the-insurance-network.co.uk

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Personal lines insurance is benefiting from the development of AI methodologies to overcome practical business challenges. Changing customer expectations and the emergence of insurtechs providing cost-effective solutions have been the driver for investment in emerging technologies.

However, getting the balance right between introducing technologies which enhance the customer experience and streamline business practices against reducing expenses and getting the right ROI can be problematic.

The rise of intelligent automation in personal lines insurance

However, getting the balance right between introducing technologies which enhance the customer experience and streamline business practices against reducing expenses and getting the right ROI can be problematic.

The technology

Here we have listed 5 technologies that can drive value for an insurance business, either from extra revenue or cost savings, including:

1. The cloud

Insurance is data intensive and thanks to cloud-based storage, vast volumes of data can be stored and managed at an affordable cost. By accessing the cloud through the internet, insurers can avoid the costs and burden of setting up and maintaining their own IT infrastructure. Instead, they ‘pay as you go’ for the amount of storage they use.

They can also rent other services such as applications and processing power.

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2. Robotic Process Automation (RPA)

RPA is the automation of mundane, repetitive and labour-intensive tasks carried out by employees. It increases productivity and frees up staff to deal with more complex and challenging issues which require the application of emotional intelligence and strategic thinking.

3. AI and machine learning

Machine learning is a branch of AI where systems learn and improve from previous experience rather than being directly programmed. Machines learn patterns in sets of data and use it to predict patterns in new sets of data. This makes analytical models in areas such as risk and fraud detection more accurate and helps insurers make better business decisions.

4. Neural networks

Modelled on the human brain, neural networks, also known as deep learning, are a set of algorithms designed to recognise patterns which help analyse and classify data. The analysis is then used to improve insurance services and enhance the customer experience.

5. Chatbots

Chatbots are virtual assistants who simulate conversations with people, responding to or resolving their queries. If someone needs further help, the chatbot can direct the person to resources or humans who can help them. Examples of how you can interact with them are on websites, via message apps and by phone. They improve support for customers and time for insurance customer service agents who don’t have to deal with simple repetitive queries.

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The application of intelligent automation in personal lines

Intelligent automation can be used throughout the insurance lifecycle. It delivers business intelligence through high-speed evaluation and analysis of data, a crucial task in a data focussed industry.

1. Automation of business processes

RPA is helping with process optimisation. For example, rather than manual data entry, documents are digitally scanned and information stored for access at a later date. It also provides an electronic audit trail for tasks performed, which helps with regulatory compliance and identifying areas to make further improvements.

2. Product design

AI and machine learning are being used to create products for different customer segments. Using behavioural data analysis, insurers can explore the relationships between customer segments and policy types, then design products tailored to their needs.

3. New Business

AI is also being used to optimise new business agents’ performance and online transactions. By tracking the sales cycle and analysing interactions, AI can provide recommendations to improve sales opportunities.

• the optimal point to interact with a customer, • when to tell them about the benefits of a

particular policy and • what products to cross-sell.

For example:

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4. Customer experience

Customer experience is an area where leveraging digital advancement can have a significant impact on a business. A seamless journey encourages loyalty in an industry where customers are actively encouraged to consider alternative providers. Self-service portals, omnichannel communication and automated service assistants providing 24/7 contact options are all helping to meet customers’ growing expectations.

5. Claims

82% of respondents surveyed for our Digital Claims Conference 2019 said they thought AI and machine learning would transform the claims experience.

AI and machine learning tools are already enabling insurers to identify and flag abnormal patterns which may be fraudulent claims, saving money on claim payouts and keeping premiums lower.

Moreover, online claim notification and the electronic submission of evidence and claims related documentation is reducing claims processing times significantly and improving customer satisfaction.

6. Underwriting

RPA is helping insurers gather detailed information about prospects and customers to make accurate risk predictions. It can speed up data collection and processing, update systems and make premium recommendations based on customer behaviours (behavioural premium pricing).

Devices such as telematics in car insurance or a fitness tracker in health insurance collect data and feed it back to the insurer.

The information helps insurers to build a picture of customer behaviour and shows their risk level.

In the next section, we’ll consider the key challenges to implementing new technology, ROI and business outcomes.

Intelligent automation is playing a crucial role in disrupting the insurance industry, simplifying business processes, rewriting the rules of data analytics and enhancing the customer experience. However, some insurers are struggling to deal with the challenges the introduction of new technologies brings. External factors such as ensuring the technology complies with already burdensome regulations add to the internal pressure of transforming traditional business models to remain competitive in a crowded market.

Insurance is notoriously process driven, so making changes in one area can often impact several others.

So, what are the key challenges when implementing intelligent automation?

Intelligent automation offers a swathe of benefits, but it can be difficult to identify the right technology for a business. Start by carrying out an IT audit to confirm current technological capabilities. Then put together a business case which defines what it needs. Customer expectations should be taken into account as much as cost optimisation.

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Ultimately, a business will need to make a judgement on how much of an edge the technology will give it over its competitors.

Key challenges when implementing intelligent automation

Deciding which technology will bring the most benefits

Unpicking current technology and processes

Mapping out current processes and technologies will help identify where intelligent automation can benefit a business.

An all or nothing approach isn’t required, often adapting and adding to existing systems will improve the customer journey and reduce inefficiencies just as well as replacing them.

Competitors may be investing in technology that enables them to heighten customer satisfaction. Be it a more competitive pricing strategy, 24/7 customer assistance or an expedited claims process. If an organisation doesn’t provide a comparative service, it may find the missed opportunities outweigh the savings on the balance sheet.

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The cost of investment

Rather than asking whether an organisation can afford to invest in new technologies, a more pertinent question may be whether it can afford not to.

There are many variables to take into account when calculating the return on investment in technology. Increases in revenue, for example, from increased sales or a more accurate pricing structure. Cost reductions from streamlined business processes and cost avoidance if a cost can be eliminated entirely, by, for example, lowering the number of customer service queries. A reduction in capital expenses from needing less data storage or servers. And capital avoidance if the technology helped get rid of a capital expense.

It’s also important to consider non-quantifiable benefits such as customer satisfaction and an improved customer journey as well as measurable gains. Any value added that could be attributed to new technology will help justify the investment.

ROI

Old school resistance

Some insurers may take an ‘if it ain’t broke why fix it’ approach and resist introducing technology they are not familiar with. Alternatively, previous attempts at introducing technology may not have been successful, or ROI wasn’t as much as a vendor initially suggested. Resisting change in the current climate of increasing customer demands and an innovative digital landscape will harm an organisation’s growth opportunities.

“What if we don’t change at all ... and something magical just happens?”

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Business outcomes

Broader business outcomes for introducing intelligent automation into a business revolve around cost reductions or increasing revenue. For insurance companies, this is evidenced by:

• Improved customer acquisition and retention rates from customer segmentation and targeted sales campaigns• Increased customer loyalty because of improved processes, personalisation and behavioural premium pricing• Enhanced customer satisfaction because of faster claims settlements • Cost savings from a reduction in fraudulent claims

With smart strategic planning, insurers can capitalise on the advantages intelligent automation brings. Investment in technology that reduces costs improves productivity and provides an exemplary journey for customers will keep insurers competitive and revolutionise the way they do business.

TINtech 2019 is the leading technology strategy and innovation event for the market taking place on 25th June 2019 in London.

The Insurance Network (TIN) is the forum for business leaders from brokers and insurers to meet their peers, discuss the latest strategic issues and share best practice in both formal and informal environments.

Focussing on leveraging innovation for a successful digital transformation, book your place now and learn how to respond effectively to technology-driven change, drive operational efficiency and enhance your customer experience.