Getting Personal: How artificial intelligence and personalization are reshaping insurance

As the insurance industry continues to embrace insurtech, use of artificial intelligence will no longer be a novelty, but the norm. Insurers will have higher expectations for customized experiences and a higher degree of personalization.

Looking toward the next decade, insurers and brokers will have to consider how to use blockchain and artificial intelligence as a tool to transform the most important piece of all—user experience. They can do that in several ways:

Moving toward personalized insurance. Artificial intelligence makes it feasible for insurers to personalize coverages and rates. To do this they need AI and access to trustworthy, accurate data sources. Those sources, including sales databases, data from wearables and user preference data, offer companies much deeper insight and allow them to contextualize behaviors to make more rational decisions.

Studies show that nearly 80% of customers are happy to provide their insurers with additional data if it means they could benefit from a lower premium. Trials are being done on wearables data to help insurers accurately price individual travel, life and health insurance.

Enhancing customer experiences. The sheer volume of calls and transactions that insurers process daily is sparking movement toward AI. Chatbots and other AI-based insurtech applications are fielding more of these calls and communications. The industry is quickly moving toward customers self-managing claims. AI is providing more guidance to customers, and it has become increasingly difficult for them to differentiate between machine and human interaction.

As the industry evolves, big data and AI are combining to create new efficiencies that are transforming the customer experience. For insurance industry executives, a passing knowledge of AI isn’t enough.

It needs to be viewed as a cornerstone of company culture.

Investments to take insurers’ insurtech strategies to the next level are needed as part of their ongoing business strategy, or they’ll run the risk of lagging behind their more progressive competitors.

Data scrubbing and personalized sales. Insurers can’t serve customers well without correct individual information. It’s labor-intensive for humans to find and correct errors. With group plans, for instance, census data obtained during quoting is often incomplete. AI can analyze a census to make smart decisions regarding each insured’s missing and incorrect data. It also can boost sales by analyzing group attributes and providing customized options to maximize the attractiveness of the offer.

But AI can do more than just correct and input census data. A group insurance carrier may receive requests for proposals in many different formats, such as email text, Microsoft Word documents, and PDFs with text or embedded images. Recent advances in data extraction from unstructured digital sources include novel techniques, such as “deep biaffine attention for neural dependency parsing.” Dependency parsing is a technique for annotating sentences to make it easy for both humans and computers to understand, frequently used in algorithms for image captioning and language translation. Biaffine attention increases performance, resulting in a more reliable method for extracting quoting information from a PDF or an email. This new method improves straight-through processing and personalization in group and individual insurance. With the help of AI, the industry is finally moving from one-size-fits-all to a more personalized approach.

Check out the full article in AM Best’s Monthly Insurance Magazine

The Golden Rules of Digital Transformation

API, Microservices and the Data (R)evolution: exchanger technology lets insurance companies manage data flow

By Cristian Marcov

Insurance systems need to talk to each other. They must be able to store, share, retrieve and use the same data. Data should flow unimpeded from the first collection of information, from a prospect or census, through underwriting to policy administration to claims.

Failure to integrate data adds cost and complexity and introduces errors. These errors can slow everything down, potentially leading to loss of business in an increasingly competitive environment for employee and voluntary benefits.

Integration with many other systems is a must. Our clients often have chosen other best-of-breed systems: CRM, policy administration, claims, enrollment systems, risk and lead scores and self-built software. No one wants to re-enter data. Everyone requires an automated streamlined solution.

Systems today often still can’t use the same data for a variety of reasons.

Legacy systems for employee benefits may still be great workhorses, but they are less flexible. It takes extra work to get them to communicate with other systems. Insurers that have gone through a merger may have two sets of systems and often find their systems are incompatible. This means data must be reentered multiple times.

Even if carriers decide to implement their own integration, the dynamic nature of the group insurance market can quickly make a recent system integration obsolete. For example, carriers may be forced to consider a new insurance product or to retrofit old ones to meet the market demands. Usually, such changes will trigger a cascade of updates for many, or sometimes all, integrated endpoints. Micro-services can alleviate this kind of problem. Breaking down software into smaller components can lead to better modularity, which in turn may reduce the implementation effort because smaller portions of the system have to be changed.

Sometimes even micro-services are not enough – many carriers have implemented complicated data pipelines with complex business logic. Changing or updating a single stage in this pipeline can thus have dramatic consequences on any downstream endpoint. And this is where the new IQX Exchanger platform can be really helpful: instead of software updates and changes in micro-service application programming interface (API) (), the Global IQX Exchanger lets carriers to easily change or update the data structure that flows through the pipeline.

The Global IQX Exchanger was designed with compatibility in mind: both backward compatibility (it is compatible with data structures produced by any Exchanger version) as well as external compatibility.

Managing data flow is a growing priority for both IT and business users. And each of those groups of users has specific requirements and/or constraints. IT users are focused on data formats, data security and system performance while business users are more focused on business rules and data validation.

Each of these aspects is configurable in the IQX Exchanger platform. One particular characteristic of integration systems for group insurance systems is the size of data that often flows between endpoints. For very large groups with a complex insurance product structure, the amount of exchanged data is very large. For this reason, the Global IQX Exchanger can operate in both synchronous and asynchronous mode with built-in protection against system overload.  Data flowing through the transformation pipe can be formatted in either XML or JSON and can be restricted to certain users, based on their authorization level.

The Exchanger platform offers a powerful tool to build more specialized applications that fit more specific needs. Many carriers are now embracing cloud solutions like Salesforce or Amazon Web Services (AWS). Although in the long run, this reduces IT operating costs, it still requires integrations with existing systems that are not yet deployed in cloud-like policy administration, claims, payroll and archive.

For all these endpoints, insurance carriers can now use one of the many Global IQX Connectors built on top of the IQX Exchanger platform. Connectors are specialized applications ready to be deployed and integrated with a specific endpoint. For example, the Salesforce connector allows bi-directional communications with Salesforce cloud applications. Salesforce users can leverage Global IQX Salesforce Connector to initiate “ratable quotes” and receive final rates whenever these are made available by the carrier rating system.

Other IQX connectors do not have a “live” endpoint for integration. They include the archive module (which extracts complex data from a production system and saves it in an archive repository) and the migration module (which extracts complex data from one environment and makes it available in another environment.

Having a stable, backward-compatible web-service API becomes even more important given the lack of an established and effective data-exchange standard with third-party information providers. Data-exchange standards should encompass data aggregation, format and translation, and frequency of delivery.

Without standards, chaos can develop, and costs can ratchet up. Unfortunately, data-exchange standards have not become universal. Industry groups such as LIMRA, CLIEDIS, and ACORD are trying.

One encouraging sign of progress: in 2019, LIMRA launched the prototype of the LIMRA Workplace Benefits Electronic Data Exchange Standards. This is something we look forward to seeing develop as we enter the next decade.

About Cristian

Cristian Marcov is a technical architect at Global IQX (www.globaliqx.com), a leading software provider of web-based sales and service solutions to employee benefits insurers.  He is an expert in Java technologies, oracle database programming and complex web applications. Cristian received undergraduate and graduate degrees from Politechnica University, Bucharest, and completed postgraduate training at the University of Manchester and the Oracle Education Centre.

Five ways cloud adoption will make your business more competitive

Security, scalability, support, cost savings and innovation 

In the past decade, a number of organizations have adopted cloud technology. As reported by Forbes in 2018, 83 per cent of enterprise workloads will be in the cloud by 2020.

The benefits of the cloud become especially valuable for SMEs (small-to-medium enterprises) without the infrastructure to support their own systems, let alone the staff to dedicate 24/7 to uptimes. Cloud computing allows insurance SMEs, including brokers and smaller carriers, to offer enterprise services without the overhead.

Cloud opens the door to digital systems without constraints. Cutting-edge tech used to be reserved for large organizations with the funds and capacity to deploy, manage and maintain their systems. It’s is now open to organizations of all sizes through the cloud.

Here are five key ways cloud-based systems allow insurance SMEs to become more competitive:

1. You avoid costly upfront investments

One of the most limiting factors for the growth of a small business is the upfront capital to invest in competitive technology. Traditionally, engaging on the same level as enterprise competitors meant investing many thousands of dollars in infrastructure to support the technology of the day. Cloud computing companies generally bill month-to-month for the use of their infrastructure, which is more manageable for growing organizations.  You rent rather than own. If you ever become dissatisfied with your cloud provider, you can switch.

2. You get the benefits of a built-in support team

Once you’re working on a cloud system, you get the benefits of an extended team. Not only does this reduce strain on yours, but it will also reduce your long-term IT costs. Depending on your contract, you won’t have to worry about the time, costs or staff required to make system upgrades or fix any hiccups in the system. Almost all cloud providers guarantee upwards of 99.95 per cent service level uptimes, which means their systems are always available and your clients will always get the services they expect. This will reduce strain, allowing you to better serve your clients and do what you do best.

3. You can lean on reliable security

Those same teams taking care of your system updates also work around-the-clock to ensure their cloud platform is secure. In addition to resources, cloud solutions bring to the table operational best practices and security standards, along with regular monitoring, patches and system fixes to ensure robust security you can depend on without added investments.

4. The system can scale to your business needs

As your organization grows and your software needs evolve, you’ll have an external partner whose system can grow with you. You won’t have to reinvest in new infrastructure to accommodate the needs for more storage or capacity. Cloud applications offer virtually infinite growth to meet the demands of your business and clients – at any size.

5. It will drive innovation and offer a better experience for your customers

Many of these benefits save money and time: two of the most critical factors in business. The cloud makes it easy to streamline processes and can replace common tasks through automation and workflows. This frees up employee time, allowing a better focus on innovation and customer service while you grow your business.

Adopting cloud computing is a key way for smaller businesses to level the playing field with large enterprises and remain competitive in the insurance industry. Cloud can provide access to cutting-edge technologies and innovation without the burden of traditional IT costs.

3 Big Challenges on the Way to Nirvana

We hear almost daily how insurtech is disrupting the once-staid insurance industry. The main ingredients are big data, artificial intelligence, social media, chatbots, the Internet of Things and wearables. The industry is responding to changing markets, technology, legislation and new insurance regulation.

I believe insurtech is more collaborative than disruptive. There are many ways insurance technology can streamline and improve current processes with digital transformation. Cognitive computing, a technology that is designed to mimic human intelligence, will have an immense impact. The 2016 IBM Institute for Business Value survey revealed that 90% of outperforming insurers say they believe cognitive technologies will have a big effect on their revenue models.

The ability of cognitive technologies, including artificial intelligence, to handle structured and unstructured data in meaningful ways will create entirely new business processes and operations. Already, chatbots like Alegeus’s “Emma,” a virtual assistant that can answer questions about FSAs, HSAs and HRAs, and USAA’s “Nina” are at work helping policyholders. These technologies aim to promote not hamper progress, but strategies for assimilating these new “employees” into operations will be essential to their success.
Managing the flood of data is another major challenge. Using all sorts of data in new, creative ways underlies insurtech. Big data is enormous and growing in bulk every day. Wearables, for instance, are providing health insurers with valuable data. Insurers will need to adopt best practices to use data for quoting individual and group policies, setting premiums, reducing fraud and targeting key markets.

Innovative ways to use data are already transforming the way carriers are doing business. One example is how blocks of group insurance businesses are rated. Normally, census data for each employee group must be imported by the insurer to rate and quote, but that’s changing. Now, groups of clients can be blocked together based on shared business factors and then rated and quoted by the experience of the group for a more accurate and flexible rating.

Cognitive computing can also make big data manageable. Ensuring IT goals link back to business strategy will help keep projects focused. But simply getting started is probably the most important thing.

With cognitive computing, systems require time to build their capacity to handle scenarios and situations. In essence, systems will have to evolve through learning to a level of intelligence that will support more complex business functions.

Establishing effective data exchange standards also remains a big challenge. Data exchange standards should encompass data aggregation, format and translation and frequency of delivery.
Without standards, chaos can develop, and costs can ratchet up. Although there has been traction in the property and casualty industry with ACORD standards, data-exchange standards for group insurance have not become universal.

The future is bright for insurers that place value on innovating with digital technologies and define best practices around their use. It’s no longer a matter of when insurance carriers will begin to use cognitive computing, big data and data standards, but how.

API, Web Services and Microservices and Their Usage in Digital Transformation

Often, insurance services opt to have in-house solutions or go for third-party products to automate some if not all of their processes. These solutions or products take the form of software applications.

When choosing or developing software for an insurance company, there are three aspects to keep in mind: API, web services, and microservices. These three terms are incredibly important in web applications, and considering how they are used, can be confusing to understand the three concepts.

Application Programming Interface

Application Programming Interface (API) is the core of any online automated connectivity. It is the medium through which multiple applications, devices, and data interact with each other.

In practice, an API defines a set of rules and protocols that allows two or more systems to communicate with each other. Every API needs to have documentation specifying the information that gets transferred between two systems.

For instance, let’s assume you are working with an insurtech company to build software that integrates with Facebook to help you know if users are breaching a policy term. To build such software, you will need to use Facebook Graph API for you to have access to data inside Facebook, including users, comments, posts, and more. With this API, you will have an easier way of accessing the data you need.

Web Services

This refers to the actual software that implements an API like the one described before. This software can respond to requests coming from .www (World Wide Web), hence the name “web” providing responses (“services”) without requiring human intervention.

There are several ways in which two systems can engage in exchanging data via webservices. The most popular ones are using text formats like XML (eXtensible Markup Language) or JSON (JavaScript Object Notation). Web service implementations can also use different transport channels, for sending data over the network, HTTP being widely used.

The HTTP protocol is implemented by most web servers available today and many of these servers can be configured to wrap the HTTP protocol in SSL (Secure Socket Layer) to encrypt the web service communication.

Microservices

This is one of the popular ways to build a complex software system. It involves breaking down software into smaller components, rather than having one huge software application. The main reason for using microservices is modularity, which can make even sophisticated software easy to understand and/or develop. The success of a microservice implementation is heavily dependent on how truly loosely coupled are the components. In an ideal world, each component could be deployed and scaled independently

Let’s assume that, for instance, your insurance company deals with employee benefits products. Instead of manually looking at your catalog to see who has paid their premiums, one can automate the process to see who needs to be reminded, etc. Suppose the line of business extends because you decided to also include voluntary benefits insurance.

If the previous implementation was designed as a monolithic application, you now have to re-think how the application works and deploy a new one that includes the new functionality. Instead, you could have the software broken down into two or more loosely coupled components (e.g. one for Group insurance and Employee Benefits and one for worksite and individual voluntary products), so that adding the new functionality would not affect the existing one. This would also have the benefit of allowing more granular scaling: you would only need to scale up the component that is in high demand. Let alone the ease of implementing cross-selling opportunities.

The inputs and outputs flowing from each component to another are defined by an API, so now you could swap any component with another implementation, hopefully with better performance, as long as is using the same API.

Which of the Three Is Best For Your Project?

The right structural design for your project depends on your requirements.

If you simply want to delegate some functionality of your own software to another party, you could have your application act as a webservice consumer. For example, an online payment system is a complex system, subject to many regulations and security constraints. An insurance company may not be willing to spend the required effort to implement such systems, but that doesn’t mean such functionality cannot be embedded in your software (like web pages or smartphone apps). The way your software could connect and communicate with a 3rdparty online payment system is through webservices. The online payment system has to have a public API that your system can use.

If you think that your software could become complex in time, maybe you should consider breaking down in smaller, simpler components that you can develop or deploy gradually over time. Microservices will be ideal for that. So, yes, software can use both web services and microservices simultaneously.

In a nutshell, APIs are software-to-software interfaces with a set of verbs instructions on how to access and relay data.

Web services are service between two end-points; they communicate over the internet and are optimized and encoded by formats such as XML or JSON.

Microservices is where software is broken down into loosely coupled distinct components that communicate with each through an API.

All three can be used as part of the framework for future digital transformation.

Four Ways to Boost Cybersecurity

Reboot your approach

Cybersecurity threats faced by insurance companies are growing and evolving at an alarming rate. This has been spurred by many factors, including the internet of things (IoT). While the IoT presents opportunities for insurers, it also exposes security gaps. The severity and frequency of cyber-attacks are likely to increase.

Insurers must commit to protecting sensitive customer information in a compliant and reliable way. The cybersecurity threat is huge. It is time for insurance companies to reboot their approaches to cybersecurity.

Common cybersecurity threats facing the insurance industry

Cyber-extortion

Cyber extortion is increasingly becoming a common problem. Some types of ransomware attacks are so effective that victims may be forced to meet the attacker’s demands and pay a hefty bribe to get their system running again.   

Automated threats

Credential cracking, vulnerability scanning, bad bots, credential stuffing, and denial of service can potentially shut down a company’s systems quickly.   

Identity theft and loss of confidential data

Identity theft may result from system vulnerabilities to data breaches. For instance, files stored on a firm’s local servers may not be protected adequately. Insurers collect and store sensitive personal client information. This information can be particularly valuable for attackers to sell in black markets. They can use it as a tool for fraud, extortion, unauthorized borrowing, and many other financial crimes.  

Business disruption and reputational damage

Cyber-attacks can seriously disrupt business. For instance, a cyber-attack on Sony Pictures erased its computer infrastructure, including telephone directories, emails, voicemails, and business records like contract templates. A malicious attack like this on an insurer could disrupt operations for months.

The foundation of any insurance business is policyholder trust. If an insurance company were to suffer a data breach exposing policyholder information or a cyber-attack that renders it unable to conduct normal operations, that trust would be shaken. This, in turn, can lead to reputational damage that may negatively affect the confidence of investors, consumers, policyholders, and rating agencies.

Four tips for boosting security:

Assess your defense capabilities realistically

Pressure-testing the company’s defenses can determine whether they can repel targeted, high-impact attacks, whether external or internal. It includes vulnerability assessment, testing programs, penetration tests, and scenario-based testing. Consider hiring a cyber-security firm to test your defenses.

Invest in early detection

Insurers need to continually invest and innovate to thwart potential attackers. Early detection is crucial. Otherwise, a cyber-attack can sit undetected for weeks.

Efficient and quick detection and response will help determine the source of the attack, the systems targeted, extent, and cause. Then, the threat can be neutralized before damage is done. Insurers need to invest in technology. There is a wide range of software solutions that provide near real-time threat detection.

Making cybersecurity everyone’s job

While implementing sophisticated systems will reduce external threats, insurers tend to neglect internal threats such as human error, which could include revealing customer data in response to a convincing phishing email. Cybersecurity awareness among employees can significantly decrease the risk of cyber-attacks resulting from human error.

Alert employees can provide early detection. An Accenture survey found that up to 98% of security breaches that are not detected by a firm’s security team are discovered by employees.

Learn from the past and evolve

Effective cybersecurity requires insurers to learn from previous cyber incidents and use this to improve planning and technology investments. Solutions include:

  • Upgrading systems: using last-generation or unpatched security software provides easy fodder for cyber attackers. Speak to your IT consultant about upgrading your systems.
  • Migrating systems to the cloud: the cloud provides users a wide range of compliant and secure storage solutions.  Choose a cloud provider that offers the highest possible security.
  • Implementing appropriate security software, protocols, and appliances: this will effectively shield data and systems from automated threats.
  • Establishing a disaster recovery plan: despite all efforts, systems can be breached. Have a detailed up-to-date plan so that you can respond effectively to any problem, major or minor.

Cyber-crooks are relentless and determined. Security is an ongoing battle. You can’t afford to let down your guard a second.  Staying one step ahead of hackers takes constant effort.

Wearables and Fitness Devices Offer New Opportunities and Challenges for the Insurance Industry

Wearables and fitness-tracking technology have witnessed rapid growth in recent times. International Data Corporation reports that one in every five people in the U.S owns a wearable fitness device. It also estimates that annual shipments will exceed 250 million devices by 2021.

Given the ability of technology to provide critical data, the wearables revolution continues to spark interest in the insurance industry. Data collected from wearable devices can provide critical health and fitness information. This information is vital to the development of interactive life insurance policies that track fitness and health data through wearable devices and smartphones. The technology hence holds the key between insurance firms and technology-savvy clients who value a modern, updated experience and digital engagement.

Industry giant John Hancock recently announced that it would begin selling interactive policies. They’ll require new life insurance policyholders to use activity trackers and share their fitness data. Insureds will, in turn, enjoy discounted premiums and other benefits.

Benefits and Opportunities

Wearable and fitness technology can be advantageous to both insurers and their customers. Wearables encourage insureds to become accountable for their health and fitness, and insurance companies stand to gain healthy clients with longer lifespans.

Most life insurance policyholders pay their premiums for an average period of 20 years. With the adoption and use of the trackers, they will be able to lead healthier and longer lives. Lower mortality means higher insurer profits.

Wearables also provide companies with a simplified way of collecting underwriting information. The data simplifies the risk-assessment process by offering metrics that would have taken longer to obtain through a full medical test. The data collected also acts as an additional source of information for new product development.

In addition to discounts on premiums, clients are also given the tools to boost their quality of life and well-being. Wearable devices can help detect conditions such as heart disease and high blood pressure and help insureds get treatment before things get worse. The technology can also be used to detect a client’s unhealthy lifestyle habits, such as smoking and excessive drinking. With lifestyle conditions becoming prevalent, wearable devices will go a long way in promoting a healthy lifestyle.

Risks and Challenges

The rapid growth of wearables and fitness devices comes with the risk of infringing on privacy. The insurer has access to very private information whenever the customer is wearing a device. The ever-present risk of the information leaking to other parties is also high.

Another challenge is the reliability of the data collected, as the devices may not always report accurate information to the insurer. For example, devices may be tailored to indicate the motion patterns like walking or running and may not be able to record other activities such as cycling. The elderly may also be victimized by errors, as their exercise regimes may be less demanding.

Finally, Wearables and Fitness Devices Are A Force to be Reckoned With

While there are various data safety and accuracy concerns with wearables, they can be overcome with proper protocol. Insurers have always dealt with sensitive information and will need to continue to handle such data with care. As for inaccurate heart-rate and other readings, studies show that fitness data is evened out over time. For example, a wearable device may not provide an accurate reading of the user’s heart rate during fast-paced or high-intensity exercises, but it can provide a comparable average over the period of the workout.

The use of wearables and fitness devices as data collection tools in the insurance technology sector is increasingly gaining popularity. Their role in shaping industry trends can no longer be understated. As software and reliability keep improving, insurance companies will further embrace wearables as the future.

 

AI and Robotic Process Automation Can Automate Insurer Grunt Work—and Do Much More

Top Five Trends for the Industry

Insurance companies are only beginning to harness the potential of artificial intelligence (AI) and robotic process automation (RPA). AI refers to computer systems that can mimic human capabilities by learning and solving problems. RPA is an emerging form of business process automation technology based on using software robots or AI “workers.”

Here is a look at the top five AI/RPA trends in the insurance industry.

1. Machine Learning for Fraud Detection and Risk Assessment  

Humans learn from experience and thus can predict outcomes. Insurers are beginning to use AI algorithms with big (and small) data to accurately predict outcomes.

Machine learning, or AI, is being used to improve customer service, guide the development of new products, detect risks and cross-promote products. It is helping insurance companies to improve their efficiency by facilitating damage assessment, identifying billing anomalies, boosting fraud detection, and identifying lapsed policies.

2. Chatbots Offer Personalized Customer Care  

Chatbots use AI to work as autonomous, internal customer-service agents that respond to customer queries. They keep a log of most frequently asked customer questions.

Chatbots can efficiently handle many routine requests, such as changing the policyholder’s address or adding a beneficiary. By handling grunt work, they can free up skilled human advisors to offer the kind of guidance they do best.

But there’s more. Using AI, chatbots can talk with customers to identify their needs and recommend the most appropriate coverages to them. They can even cross-promote products based on the customer’s needs. Then, the customer is turned over to a human advisor to answer any questions and complete enrollment.

3. AI Uses Data to Better Predict and Mitigate Risk  

Insurers depend on their ability to predict and manage risk. The more information they have access to, the better their ability to assess risk.

AI enables the collection of both structured and unstructured data. Besides the insurer’s own data on insureds, structured data includes information collected through sensors wearable devices and other IoT devices. Unstructured data is collected from public spheres such as social media pages and search engines. This data can then be used to create insights that not only help insurance companies protect their bottom lines, but also give them a true competitive edge.

Employee benefits is a particularly promising area. AI is now being applied to streamline pre-approval workflow. For instance, before an insurance-company employee replies to a customer, the response can be passed through smart compliance system that reviews it and makes any necessary adjustments before it goes out.

4. Automating Routine Processes

Other processes that are now being automated using RPA include copying and pasting data to spreadsheets, logging into applications, transferring data from one database to another, and opening emails and processing them.

5. Claim Processing  

AI and RPA are now being used to automate claim processing, especially in property-casualty insurance and employee benefits insurance. The system notifies assigns adjusters, integrates the disparate claim information, and facilitates claims payments. For instance, ClearPay is an InsurTech product that insurance companies, agents and brokers can use to integrate the settlement process and monitor claim payments in real-time.

AI and RPA are only beginning to transform how business is done in the insurance industry. We can expect to see burgeoning usage in operations, customer service, risk assessment and mitigation, and regulatory compliance.

Mike de Waal is president and founder of Ottawa-based Global IQX (www.globaliqx.com), a leading software provider of web-based sales and service solutions to employee benefits insurers. He has deep experience in both software development and business management skills. Early in his career, he worked as a computer programmer and then went on to become a financial planner and a benefits consultant before becoming a tech entrepreneur. He can be reached at mike@globaliqx.com.

 

Eight Top Insurtech Trends for 2019

The insurance industry used to be a tech laggard. No more. Though there’s still much work to be done, most insurers are now better positioned to capitalize on their investment in technology.

Here are eight key technology trends that continue to shape the industry.

1. Greater stress on cybersecurity

An Ernst & Young security survey revealed that 59% of respondents had encountered a significant cybersecurity incident in their organization. Because insurers store so much sensitive personal and business data, they’re a prime target.

Cybersecurity strategy should be focused on proactive measures rather than reactive strategies. Cyber-crooks are relentless and inventive. Security has to be a top priority for insurers of all types and sizes.

2. Filling a gap in employee benefits automation

While group proposals and policy administration are both well automated, between the two comes group onboarding, which has not been automated.

But solutions are being developed and implemented. Onboarding solutions will be built on automated data capture and importing. Data integrity is crucial. Employee information must be correct and complete when entered.

The solution must also offer robust data security and comply with privacy regulations to securely to gather and store employee information. Flexibility is also mandatory because integrating onboarding closely with both proposal and policy systems is essential to efficient workflow.

3. Cloud computing grows

Cloud computing will continue to be adopted widely by insurers and insurtech providers as it is cost-effective, speedy, and flexible. Cloud providers will continue to improve their technology to deliver sophisticated capabilities.

The security risks associated with housing data off-site via a third-party, however, can present challenges. While cloud storage companies are expected to protect data, ultimately insurance IT departments are responsible for their cybersecurity. That requires constant vigilance, hiring skilled people and spending enough money.

4. Internet of things and Big Data become more important

IoT continues to become more useful. Insurers can use real-time data to meet and enhance business objectives. This can boost efficiency and revenue and promote better customer service.

As the Big Data revolution continues to expand, IoT adoption in the insurance industry is expected to grow. It will enable collection of data in real time, resulting in lower premiums for insureds willing to participate. There will be ongoing adoption of connected devices for loss prevention and pricing in property-casualty, life and health insurance.

5. Analytics advance

Analytics can transform Big Data into actionable insights. As analytics and data science advance, insurers can better extract value from the huge amounts of data that now exist. Insurers can then leverage on the sophisticated information analytics to gain a competitive edge in the market.

For insurtech providers, there is a huge opportunity in the coming years to develop advanced analytical technologies that can make sense of unstructured data such as real-time video, social posts and live blogging.

6. Artificial intelligence: the future is here

In 2018, more insurance and insurtech companies found effective ways to integrate AI. In 2019, companies will complement a significant part of their structured data decision-making with AI data analysis and decision-making.

Robotic process automation will begin to gain a wider application facilitating automation of repetitive processes across the entire IT infrastructure. Robotics and AI can offer improved productivity, shortened cycle times and better compliance and accuracy.

7. Augmented reality blooms

Augmented reality is starting to have a presence in insurance. An article by software development company Jasoren identifies several AR use cases, such as using it to warn of risks, explain insurance plans, estimate damages and increase brand awareness. Alternate forms of AR such as virtual reality, mixed reality, and extended reality are shaping AR how it is being used.

8. Blockchain evolves 

The technology behind cryptocurrencies will be adopted for more promising applications. They include “smart” contracts, and secure decentralized data collection, processing and dissemination. While I do not expect to see a full-scale implementation of blockchain technology any time soon, many insurers, and insurtech companies are in the process of launching projects and initiatives to test its applicability and effectiveness for insurance, especially claims.

Implementing Successful Technology Projects: A Short History of Agile Development (Part 1)

Agile methodology has a long history with deep roots. It evolved across decades from an array of research and writing by individuals with diverse backgrounds. One thing they all shared was the desire to quicken the pace of development – whether it be for a product, a manufacturing line or software.

When you think about insurance, project methodologies may not be the first thing that comes to mind. Yet, as business and IT professionals find themselves increasingly working together toward the shared goal of digital transformation, the topic has gained importance in the boardroom.

And with good reason. Many projects have cost much more and taken much longer than expected.  Scientists, product managers and engineers have been investigating what determines a successful project ever since Walter Shewart of Bell Labs began using Plan-Do-Study-Act (PDSA) cycles to improve products and processes in the 1930s.

Shewart taught his young apprentice W. Edwards Deming the iterative development methodology that he used to create the famous Toyota Production System, the seed of today’s “lean” mentality.

In 1986 Hirotaka Takeuchi and Ikujiro Nonaka published an article called “The New New Product Development Game” in Harvard Business Review. They examined manufacturers like Fuji-Xerox, Honda and Canon that were releasing innovative technologies faster and more successfully than their competitors.

These companies were not using the traditional “relay race” or “waterfall” method of development where individuals or teams hand off products after completing each phase. Instead, they were using what Takeuchi and Nonaka coined a “rugby” approach, “where the entire team tries to go the whole way as one unit, passing the ball back and forth.”

As personal computers and then the Internet became mainstream in the late ‘80s and ‘90s, it was crucial that developers find a way to quickly implement their innovations, obtain feedback, and launch their technologies in order to stay competitive.

This was referred to as “the application development crisis” or “application delivery lag” where the estimated time between a validated business need and solution could be up to three years.  In some cases, it was much longer, which meant that projects were often cancelled or no longer met the original business need when finally completed.

In 1993 agile co-founder Jeff Sutherland found himself with an incredible challenge working for the Easel Corporation: develop a new product to replace a legacy system in six months. Sutherland was well versed in rapid application development, object-oriented design, PDSA and skunkworks methodologies. He set out to foster this kind of culture and began learning everything he could about optimizing productivity when he came across Takeuchi and Nonaka’s rugby approach.

Sutherland embraced many of their ideas and established a novel way to develop software based on the rugby metaphor, calling his approach “scrum.” This method allowed him to complete seemingly impossible projects on time and with fewer bugs. He then joined forces with colleague Ken Schwaber to structure the approach, which they presented to the public in 1995.

In 2001 a group of 17 developers, including Sutherland, met in Snowbird, Utah, to discuss their views. Sutherland was a proponent of scrum. There also were advocates for a number of approaches such as extreme programming (XP), adaptive software development (ASD), crystal, feature-driven development and the dynamic-systems-development method (DSDM).

The group finally agreed on a new name for the movement – agile – suggested by a member who was reading the book “Agile Competitors and Virtual Organizations: Strategies for Enriching the Customer.” The “Manifesto for Agile Development” was born and hinged on 12 key principles that are being applied across industries worldwide, including insurance.  Agile development has proven to be a major advance.

In my next post, I’ll discuss the top challenges and key success factors for agile development in insurance.