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HOW IS GEN Z SHAPING THE FUTURE OF CAR INSURANCE?

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By Evan Davies, CTO, Solera

 

Generation Z is reaching its mid-20s in 2021. This generation has grown up in an age when companies like Amazon, Uber, and Airbnb use AI to simplify purchasing, communicate directly with customers, and apply analytics to their business. Gen Z probably doesn’t remember services or products without voice activations, personalized buying suggestions, and chat bots offering instant interaction. As they become more influential as consumers, their expectations for services and interactions will include many AI-based offerings. This, combined with the purchasing power of Millennials will require all businesses to evolve if they want to meet these collective expectations for technology and rise to the new standard of on-demand interaction.

To come to terms with this, the insurance industry is quickly adapting and integrating AI into business operations and claims infrastructure. In a recent report, McKinsey projected that there is a potential annual value of up to $1.1 trillion in additional business revenue if AI is fully embraced in the insurance industry alone. The sector itself has been slow to mobilize digital transformation in the past, but the disruption seen in the Covid-19 era has pushed the adoption of AI and other next generation technologies up the priority list for many insurers. That said, it’s not as simple as adding something like visual intelligence to the photo estimation process.

Computer vision and the technology that enables it must be underpinned by two fundamental elements: quality data and knowledge of vehicle repair processes. AI-based solutions must be trained and supported by the combination of these two components to ensure consistency of results at every stage. Only then can insurers advance their algorithms to maximize accuracy, ensure faster claims resolution and enhance the customer experience.

 

Evan Davies

Image Recognition and Processing Using AI

For those who have recently filed an insurance claim of any kind, you are probably familiar with the image capture and upload process. While image capture is not necessarily new, the technology at work evaluating and producing the outcomes is quite new and can be complex.

Automation tools improve the first notice of loss (FNOL) and triage processes by speeding up review of damaged photos, identification of total loss vehicles and supports identification of the next best action for repairable vehicles. This means that decisions that affect claims outcomes for the insurer, repairer and insured are made at the beginning of the claims process to streamline the workflow and speed up the claims and repair process for all involved.

When it comes to AI photo based estimating, there is no ‘one-size-fits-all’ solution with more than one way to approach the process. One approach is to train AI models by learning from historical claims data and related damage photos. Another approach is to use a training data set containing annotated or “labeled” photos.

 

Get Quicker and More Reliable Repairs

In addition to customer experience, AI is enabling insurers to maximize the skills and outputs across their own workforce. In the absence of an AI-based estimating system, trained appraisers are required to produce repair estimates. However, with the use of an AI-system, those skilled workers can be reassigned to more complex cases.

Providing an accurate estimate of the size, position, and severity of the damage plays a crucial role in getting the repair cost correct. There are many variables that influence the cost – from material and geometry to accessibility and thickness. Modern vehicles are made of alternative materials, such as different types of steel, aluminum, and carbon fiber, which inevitably impacts cost. Many new vehicles are also fitted with sophisticated advanced driver-assistance systems (ADAS) which need to be considered when assessing damage. This is a lot to consider and, hence, why the repair science element of any AI-based estimating is so important for safe repairs and correct claims valuations.

 

Blending Data and Repair Science

As with any automated technology, the algorithms that power insurance solutions must be trained and supported by the right set of data to ensure consistency of results at every stage and for every touch point served by AI. It’s not just about bringing AI to an existing workflow. Estimating using AI is about blending repair science technology with a database of historical claims and images gathered over years of servicing and supporting the industry that makes this evolution so powerful.

The combined approach of these two types of data enhances machine learning algorithms to drive efficiency and accuracy. It provides an holistics and integrated approach that can effectively increase accuracy and performance across an entire claims workflow, compared to simple AI image recognition point solutions.

 

Future Proofing for Digital Native Generations

Gen Z are pushing the boundaries of digital communication once again – but we know it won’t stop there. Now, more than ever, with the increasing use of digital channels by all generations and younger generations’ expectation for it, AI is becoming trusted by service providers around the world, including those in the insurance industry. Implementation of next generation solutions like the AI now found in many repair estimating solutions is accelerating and must continue doing so if insurers are to navigate ever-changing consumer needs.

It’s widely acknowledged that this is the future of insurance and beyond. Yet, with any new technology adoption, it doesn’t come easy. It takes partners with the right background and expertise to help chart the path, expand adoption and rewrite the standard of service for years to come.

 

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How insurers benefit from digitalisation

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Oliver Werneyer, CEO & Founder, Imburse

 

Insurers need to embrace digital transformation to stay relevant. Customers nowadays are well-informed and expect user-friendly experiences and smart solutions that meet their needs. They are also more demanding than ever, so being able to gain their attention and trust is key to boosting customer loyalty and guaranteeing sales. Delivering an excellent omnichannel customer experience is only possible through the adoption of technology and the optimisation of processes.

Insurers have been facing the pressure to digitalise for a few years now, and it continues to increase. Technology is here to stay, and customers are likely to continue using it for their everyday tasks. The traditional insurance industry as we know it is undergoing a disruptive evolution, driven by customer demand and the rising competitiveness of the industry. To be customer-driven, however, insurers need to place focus on improving customer experience from end to end. This goes from the moment that customers are searching for policies online, to the moment customers file a claim and expect a quick and seamless reimbursement process.

This may not be news to insurers, who are well-aware of the need to embrace a digital transformation journey. However, they are faced with challenges that make it incredibly difficult, if not impossible, to compete with newer, innovative companies that place the customer at the centre of their business proposition. For instance, when it comes to payments, insurers must be able to integrate with various payment providers and technologies so they can offer their customers a wide variety of payment methods, as well as the payment methods that best suit their unique needs.

Oliver Werneyer

While some customers may prefer to receive a voucher for their favourite shop, others may be happy with a bank transfer or a push-to-card payment. Being able to meet customers’ individual needs is crucial to gaining their loyalty, and even more important now that hyper-personalization has become so popular across industries. Integrating with various providers is a complex process, mostly due to insurers relying on old and outdated IT systems that power their entire operations.

These integrations are incredibly time-consuming and expensive and require a lot of internal resources. Insurers don’t typically have these resources available, because they don’t have a dedicated payments team nor the in-house expertise to leverage payments. Equally, the length of these integrations makes it difficult to swiftly adapt to continuous market changes. Speed and flexibility are crucial elements of success and elements that most insurers don’t have.

These challenges can only be solved through partnerships. Thankfully, the Insurtech market is packed with innovative solutions that can enable insurers to solve their most pressing problems. Such companies, for instance, enable end-to-end connectivity to the whole payments world. This means that insurers are able to connect to any payment provider or technology they want, in any market, for both collections and payouts.

Instead of having to deal with lengthy and cumbersome integrations processes, insurers can focus on other key business areas while solutions like Imburse take care of all the heavy lifting. Another key element that insurers must consider outsourcing is expertise. Payments is a niche area and, while crucial to the success of the business, it isn’t considered a core department. Being able to access agnostic payment experts that help insurers navigate the payments world and make the best business decisions is a stepping stone for the successful optimisation of payment operations.

Some of the benefits of embracing digitalisation for insurers include streamlining customer experience and ensuring that customers go through a seamless and quick journey from beginning to end. According to PwC, 80 percent of companies are now investing in omnichannel experiences, powered by the need to ensure customer retention and satisfaction. Customers expect everything to be instantaneous, whether that is finding the most suitable policy for them, making a claim or receiving a payment. Digital insurance makes it possible for insurers to meet and exceed their customer’s expectations, and boost retention and satisfaction. Digitalisation also enables insurers to reduce costs. According to a McKinsey report, automation can reduce claims costs by as much as 30 percent. Insurers can improve their underwriting processes, improve speed to market and generate new revenue streams by, for instance, adopting embedded insurance and partnering with other companies. This will boost sales conversions and lower the costs of distribution.

Large incumbents can more than double profits over 5 years just through digitalisation (McKinsey). These benefits are both in the short and long-term. In the long run, having future-proof systems and processes in place will enable insurers to continue to adapt as the market changes – and it will change. Being able to have this flexibility will prove invaluable.

 

About the author

Oliver Werneyer is the founder and CEO of Imburse. Oliver spends most of his time overseeing the overall operations of the company, but with a strong focus on powering international growth. Before founding Imburse, Oliver held various roles in the insurance industry, with the likes of Liberty Life, Swiss Re and Genworth. He also founded Flynrate, an innovative flight tracking and flight delay insurance app, and became a leading member of London’s startup ecosystem, sharing his industry knowledge and passion for entrepreneurship with London-based startups.

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Finance

The penny has dropped – the finance sector needs Data Governance-as-a-Service

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By Michael Queenan, Co-Founder and CEO at Nephos Technologies

 

In our data-driven world, the amount of data is growing exponentially and it’s predicted that the amount generated each second in the financial industry will grow 700% this year. Leaders of financial services organisations have realised two things since the start of the pandemic – that data on their customers and services is their greatest asset and that they must embrace technology to make intelligent business decisions to grow successfully and outperform competitors.

Since the financial sector holds arguably the most valuable and sensitive information, organisations must do more than just store this data. They need to ensure its security, integrity, and governance so that it’s useful in improving the brand’s customer experience, innovating products and services or predicting future trends to improve risk management.

Yet without a robust data governance model – a strong set of rules and processes for what data means, and how it is categorised, owned, accessed, stored, and used – data is worthless. Only when an effective data governance model has been established, will data meet regulations and be secure. Data leaders must shift gear in their data processes to avoid hefty compliance penalties and unlock potential value from their data assets.

 

The data governance challenges faced by financial sector organisations

The barriers for achieving ‘good governance’ are many and varied. Ignorance of the benefits of data governance is a major hurdle for developing a governance strategy. Many financial firms have invested – at significant cost – in data governance tools, but struggle to deliver the benefits they are looking for. Many don’t have the right skills and resources to maximise or set the right metrics to measure the business value. Some are compromised by unoptimised gaps in their approach.

With many different elements to master, data governance is complex – from identifying the right tools to managing the challenges presented by encryption, all whilst ensuring that data quality is sustained and data is managed responsibly.  The negative impact of misplaced investment in ineffective data governance strategies can be significant, for the short and long-term.

 

Why data governance matters

With the acceleration of digital adoption in the financial services industry, it has become crucial to deliver seamless, intelligent customer experiences. Data governance is the key to managing data flow, ensuring compliance, and scaling up. Proof that data governance matters is evident in the Master Data Management Market growth prediction, from $16.7 billion in 2022 to $34.5 billion by 2027.

Data governance is a comprehensive methodology for ensuring the quality and security of the company’s data. The various benefits of an effective data governance strategy include minimised risk, coherent policies, metrics and processes, and better implementation of compliance and enhanced data value. However, for financial services, there are significant advantages as a result of the following:

  • Data governance saves the company money by increasing efficiency. Precious time can be saved by having good quality data and a single source of truth, with less duplication of data, and less time needed to correct data errors.
  • Good data governance gives the business confidence in having accurate and trustworthy data, the holy grail for delivering outperforming customer experiences.
  • A data-driven culture can also be introduced to your business through good data governance. With the ability to gather critical customer and market insights that can guide the direction of your business, data governance allows financial institutions to drive innovation and gain competitive advantage.

 

Bridging the governance gap with Data Governance-as-a-Service (DGaaS)

Increasingly organisations are turning to the ‘as-a-Service’ model to bridge the gaps in their data governance capabilities, as well as ensure critical alignment between objectives and results. This dedicated approach aims to minimise the risk of investments and delivers the strategy and proven technologies required to ensure data governance success.

DGaaS can be applied across each major component required to deliver good data governance. First, it uses software tools to scan all data within a typically complex financial services data infrastructure in its data discovery and classification phase. Without this detailed insight, organisations can’t always identify their data assets, any data mishandling and the level of risk generated.

The next part of the process is creation and documentation. This means organisations can drive their governance objectives through to execution, while removing the operational and recruitment overheads, which means they can purely focus on value created from data. In doing so, organisations can convert the raw outputs from the toolsets into meaningful business outputs.

With a holistic approach, DGaaS allows financial services organisations to focus on the transformational potential of data while critically staying compliant.

 

Reaping the benefits

Data is a vital asset to enable financial sector organisations to build the right capabilities to deliver their services and remain competitive. With a robust data governance model, financial firms can assess risk, predict trends, and seize market opportunities based on data-driven insights. Only data-driven processes, built on high quality and effectively governed data, will enable them to build outstanding customer experiences. It’s essential that leaders realise data governance is a fundamental discipline, not a luxury, and establish an effective model to formalise processes and responsibilities before their data lets them down.

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