Digital crossroads: analytics and automation in the insurance sector
March 2019 | FEATURE | SECTOR ANALYSIS
Financier Worldwide Magazine
March 2019 Issue
The insurance sector is at a digital crossroads. Increasing competition, evolving customer expectations and a changing regulatory landscape are redefining the sector’s parameters and forcing insurers to adopt new technologies in order to remain relevant and competitive.
In the view of many insurance practitioners, the sector’s ills – which also include the need to drive down costs and boost efficiency – can be cured by utilising analytics and intelligent automation to a far greater extent than is currently the case.
Indeed, advanced technologies, particularly artificial intelligence (AI), cognitive robotics and machine learning (ML), can help the insurance sector to meet customer demands by delivering faster quotes, processing claims quicker, providing actionable insights, and achieving unparalleled performance and business growth, as well as managing risk and regulatory compliance.
“Analytics and automation is at the core of any insurance company,” says Øyvind Indrebø, head of ML and AI at Fremtind Insurance. “However, the extent to which each company has developed its capabilities varies. Those that seek to be at the forefront have started with lighthouse projects, such as better pricing of products or more personalised product offerings, in parallel with developing data platforms, talent and capabilities.”
In the view of Tjerrie Smit, head of advanced analytics at NN Group, a greater investment in analytics and automation can provide insurers with considerable benefits. “There are many reasons to invest in data science,” he suggests. “These include process optimisation, customer analytics or customer behaviour. Previously, this work was done manually, but through advanced data analysis we can calculate risk more accurately, and adjust products and services accordingly.”
That said, according to KPMG, 91 percent of insurance company chief executives admit they are unsure as to how to introduce analytics and automation into their business models – a critical determination given that, according to research by MarketsandMarkets, the global insurance analytics and automation market is expected to grow from $6.63bn in 2018 to $11.96bn by 2023.
What is certain is that if insurers can move swiftly and embrace a rapidly changing environment, then the sector will look very different in but a few short years.
The transformational opportunities analytics and automation offer the insurance sector are significant – especially in terms of the impact such technologies have on meeting customer demands and improving value.
“The opportunities afforded by analytics and automation are plentiful,” agrees Mr Smit. “New technologies and the use of data offer virtually unlimited technical possibilities. Customers expect a tailor-made interaction with the companies they engage with and instant and personalised processing. This is where analytics and automation comes in – helping to optimise business performance and increase customer satisfaction.”
Drilling down, analytics techniques such as ML offer a wide range of opportunities for insurance companies to create business value and enhance customer satisfaction, such as automating fraud detection. “Being more accurate in determining which claims are fraudulent allows insurers to reduce costs and enhance customer satisfaction by avoiding unnecessary investigations,” explains Mr Indrebø. In turn, he says, insurance companies can then offer more personalised products to customers, which could enhance customer satisfaction and boost growth.
“Multiple uses of analytics and automation offer attractive return on investment (ROI),” adds Alexandrina Scorbureanu, global head of projects and overarching activities at ERGO Group. “In Europe, many insurers are using the new regulatory challenges posed by the General Data Protection Regulation (GDPR), the Insurance Distribution Directive (IDD) and International Financial Reporting Standard 17 for insurance contracts (IFRS 17) as a door opener toward improving their data governance, analytical and automation capabilities.”
However, despite these overtures, Ms Scorbureanu feels that, as far as the insurance sector is concerned, the potential of analytics and automation remains mostly untapped.
While the extent to which the insurance sector utilises analytics and automation varies, the challenges facing those insurers that have or are looking to implement these technologies are not inconsiderable.
“It is not only about being the best on a technical level,” says Mr Smit. “The key success factor is having a true understanding of business challenges. Success in AI depends 10 percent on the type of algorithm used, 20 percent on the technical implementation and 70 percent on the business involvement. This makes it key for data and AI professionals to closely work with business stakeholders to understand the problems they need to solve. This is key to creating solutions that scale: invest once and use often. This is not easy, but very important in order to reach both top level customer satisfaction and profitability.”
In Ms Scorbureanu’s view, if insurance companies are able to master the challenges posed by new technologies, then they could position themselves as dedicated, proactive risk managers by better understanding and anticipating the needs of their customers, while also preserving their privacy. “A customised offering which closely corresponds to customer expectations implies better cost management and a lower administrative burden for insurance companies,” she suggests. “This allows for simpler processes, while also improving employee satisfaction. Most importantly, it offers greater scope to reduce or even prevent potential losses and establish prompt assistance services when customers most need it.”
In many cases, the opportunities new technologies offer the insurance sector are overshadowed by the implementation hurdles that companies have to overcome, especially the cumbersome IT legacy systems on which most of their core operations still run. “Some of the crucial challenges when applying these technologies or methods in insurance are still related to legacy core IT systems, as well as data granularity and quality, and data decentralisation,” says Ms Scorbureanu. “Additionally, a company’s skills and cultural mindset are fundamental ingredients to ensuring success or determining failure.”
Assuming the challenges involved in introducing new technologies are overcome, the implementation of said technologies – while recognising what this means for extant systems and processes, as well as employee commitment and acceptance – is the next major port of call for insurers.
“In order to implement analytics and automation solutions, insurance companies need to call on a range of different competencies within their business domains,” advises Mr Indrebø. “Implementing new technologies will challenge existing processes, infrastructure and notions of best practice. By focusing on completing the cycle from idea to service running in production, companies will be able to scale up and iterate or pivot faster.”
It should be noted, however, that the speed at which new technologies are implemented can vary substantially – by geography, customer and portfolio profile and sales channel – and is often subject to the flexibility, or otherwise, of a company’s culture and governance model.
“Scalability is therefore not always straightforward,” says Ms Scorbureanu. “For example, insurance companies’ analytics may focus on intelligent fraud prevention and corresponding mitigation plans. At the same time, applications to customer relationship management and customer feedback management have been successful in demonstrating how customer satisfaction improves if companies are able to more efficiently classify unstructured customer feedback and shorten back-office processes, so that they can offer immediate support when customers need it most.”
Moreover, selling the benefits of new technologies requires solid communication at all levels of a company’s organisational structure. “Specialists sometimes take for granted that everyone can immediately see the benefits,” continues Ms Scorbureanu. “We should not underestimate the fact that there is often a need for mindset and cultural change, which can be a lengthy process. So, companies should expect to see and manage delays. It happens often that the timeline for implementing such initiatives, and even cost estimates, are underestimated.”
As competition across the sector hots up, the uptake of analytics and automation is likely to accelerate in tandem, with insurers keen to identify opportunities that can solve business problems and deliver maximum ROI.
“At its core, the insurance business is based on data processing and predictions,” says Mr Indrebø. “AI models and technology make predictions faster, cheaper and better, and hence reduce the cost of predictions. A direct consequence is that higher quality and lower costs of predictions and data will lead to disruption of traditional insurance business models and operations. The exponential AI evolution gives insurance companies opportunities to increase the speed, accuracy, quality and efficiency of their business processes.”
According to Ms Scorbureanu, sensor-based data systems such as the Internet of Things (IoT), as well as mass digitalisation, will be the next big disruptors of traditional insurance operating models and value chains. “Currently, one million new IoT devices appear every hour of every day, worldwide,” she asserts. “This super-connectedness will enable profound new possibilities and capabilities which can be extremely beneficial for all – a world that can rapidly turn into a merger of digital and physical dimensions. Augmented reality, super-quantum computers and virtual assistants will definitely change our way of living and doing business in a shorter than expected time.”
In the end
Of course, in the end, the adoption of new technologies is all about optimising processes and increasing customer satisfaction – basic, as well as essential, commodities in a sector as customer-centric as insurance.
“The acceleration of analytics and automation will have a major impact on how companies work and on their labour forces,” suggests Mr Smit. “Not only will this impact blue-collar professions, but also white-collar professions such as financial services, doctors and lawyers. Some job roles will disappear but others will emerge. From a customer point of view, it enables insurers to provide more tailored products and individual premiums. New techniques enable us to be more prepared and to better and more accurately calculate risk. It also requires new capabilities and skills.”
As the insurance sector becomes increasingly competitive and forces practitioners to differentiate and personalise their products and services, the race to win new customers and maintain relationships intensifies. An answer but no panacea, technological tools such as analytics and automation nevertheless offer insurers a credible means of flourishing in the digital age.
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