Insurance Quality Assurance Trends 2020

Categories: Insurance, QA & Testing

by Darwin Castro – 

“Build what again.”  This is most likely the reaction you would get years ago when the concept of building an application to test another application (think AI) is brought up with an Insurance Carrier’s IT department.

Insurance companies, especially those in the Commercial and Workers Compensation lines business, were for a time notorious for being slow to adapt to new tech. It’s not unusual to see application updates resulting from substantial regulatory changes or custom development of specialty lines, taking many months or years to get in the hands of end-users because of the industry’s proclivity for the waterfall development methodology.

The past few years saw this change as more and more Insurance companies embrace Agile development and DevOps while embarking on their digital transformation journey. With this, QA organizations are having to rethink how they operate to be able to keep up with the cadence of development and product releases.

In 2020, here are three trends that we will see as QA in the Insurance Industry attempts to transform itself.

1. Intensified Adoption of AI in Testing

It was around 1950 when Alan Turing, widely known as the Father of Artificial Intelligence (AI), set out to answer the question – Can machines think? With advances in automation and machine learning technology, the answer is tipping more and more towards a “yes.” And the application of this “yes” answer is becoming broader to encompass the QA practice too.

Picture this; your Policy Administration application is upgraded to handle changes to a set of coverages. Using AI and Machine Learning, it is now possible to perform validation to help ensure the intended changes are correctly implemented. Code can be scoured to detect changes alongside an examination of the visual aspects of a UI. Changes can then be tied to requirements enabling automatic generation of test cases and its execution. AI can then group the anomalies and failures and report for humans to review.

The above example demonstrates how AI in QA can provide the ability to perform lower-value tasks that take humans hours to do and reduce these to mere seconds, increasing throughput and reducing the overall testing effort in lockstep with the ever-shrinking testing window. Also, offloading these tasks frees up the human worker to focus on more cerebral activities, including validating business capabilities and outcomes.

Although AI holds a lot of promise, The World Quality Report noted many organizations who want to leverage AI, struggle to do so. Challenges include a lack of AI knowledge in-house and difficulty identifying where AI can be used in the business.

In some companies where attempts to implement AI were made, we saw cynicism as investments are seen not bringing about the anticipated value or expected benefits. For a number, the disappointment stemmed from cases of unrealistic expectations set at project onset. For others, the disillusionment resulted from the everyday wrong application of the technology.

This is where companies like RCG can help. Our experienced resources can help develop a strategy to incorporate AI into your QA process and support you with its implementation, helping you realize all the benefits AI has to offer.

2. An Even More Connected World

I am not talking about IoT here, although that is a crucial opportunity area too. I am talking about a system to system integration within and outside of the Insurance domain.

Take, for example, a Claims Administration System. Insurance carriers these days are looking for solutions that come with a host of integration capabilities built-in. Below is a sampling of these essential integrations:

  1. Integration with Sanction Information (Terrorism, Narcotics, Country-Specific, Transnational Criminal Organizations, etc.) Service Providers to support compliance with the Office of Foreign Asset Control (OFAC) regulations. Carriers do not want to be releasing payments to individuals or organizations in the Sanctions List.
  2. Integration with Pharmacy Benefits Management/Medical Case Management Companies for benefits eligibility, administration, billing, and payment.
  3. Integration with Centers for Medicare & Medicaid Services for reporting for Medicare beneficiaries who have coverage under group health plan arrangements as well as for Medicare beneficiaries who receive settlements, judgments, awards or other payment from liability insurance, no-fault insurance, or workers’ compensation, collectively referred to as Non-Group Health Plan.
  4. Integration with Banks like the Positive Pays automated fraud detection tools offered by most Banks’ Cash Management Department.

Microservices architecture and the use of APIs and web services continue to be the approach of choice for these integrations, and as we see more of these come to life, QA organizations will need to develop the ability to automate for these integrations.

Testing of these APIs and web services must account for data that passes through the integration, credentials, access, Database connections, as well as configuration settings (e.g., endpoints) that changes as the integration, is moved from environment to environment.

Today, getting started and developing the ability to automate testing for integrations is easier with the arrival of low code automation solutions and as existing popular automation tools like Selenium and TestComplete continue to evolve and provide new features that make automation much easier to implement

3. Evolution of the QA Resource

Time was when the job description of a QA resource typically reads something like write test plans, cases, and scripts, execute smoke, regression, and integration test, report defects, and manage through resolution. In 2020, such a job description, and to a more significant extent, traditional testing will begin and continue to fade away.

The line separating developers and test engineers will blur even more. Technical (i.e., programming), Agile, DevOps, and Automation skills will become a requirement for QA practitioners. Demand for Software Developers in Test (SDETs) will continue to increase.

Then, new roles will also start to emerge. AI Test Experts will become a thing, and this new breed of Testers will focus on testing AI Applications. Yes, AI applications that test other things need to be tested and the how and the when will be different.

Lastly, expectations that QA Resources is an extension of the end-user becomes the norm. End-user experience and ensuring that it is delightful will be part of QA responsibilities. It will not anymore be enough that QA tests whether an application can perform its intended function, QA must test the that the application is easy to use, fast, produces rewarding results, supports the desired business outcome, and is just overall very good.

Demand and competition for these QA resources who have the right skills will be very high, and attracting them into the Insurance business will even be more challenging. The Insurance industry will be well served to assess the current workforce, identify those who are apt to acquire the needed skills to support evolving QA needs, invest in specialized training, and incent to keep the best and the brightest.

The Insurance Industry is primed to make significant strides in the way it does QA in 2020. Committing to make a change and picking the right consulting partner to help with the transformation initiative is essential. RCG can help make it happen for you. Contact us.


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