KEY TAKEAWAY:
--The primary value proposition for offshoring – more work at less cost – is declining with digitalization. And AI technologies, when implemented right, can make processes cheaper, better and faster than manual processing and deliver significantly improved customer experience.
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Everyone is talking about artificial intelligence, especially generative AI, the breakthrough technology that brings the capability to learn from experience and to “think” in almost-human terms.
It is certainly true that using AI in the insurance world promises extraordinary benefits. To date, the AI-enabled innovation receiving the most attention is the increase in efficiency by automating mundane tasks. Other benefits that are becoming part of the AI buzz include its potential for lowering risk, improving compliance, gaining business insights from predictive analytics and achieving higher profitability.
One area that has not yet been addressed is the fate of process outsourcing, which has become standard practice for insurance firms over the last two decades. Can generative AI replace the advantages that insurers and brokers sought to achieve by offshoring? Will business process outsourcing disappear? Is there a place for it in the automated world of the future?
The State of Process Outsourcing
Twenty years ago, labor arbitrage was big news. By taking advantage of low wages paid in other parts of the world, American companies discovered that they could save considerable operational costs. Soon, most firms had an office in Ukraine, India, the Philippines or other countries where labor costs were a fraction of those in the U.S. Expenses dropped.
However, over the last two decades, unforeseen developments have clouded this rosy picture.
The initial expense of hiring and training this international workforce was substantial. There was -- and is -- considerable competition for skilled individuals who are fluent in English and who could be rapidly trained to perform the required tasks, quickly and accurately. Over time, labor costs increased as salaries rose to be competitive. The costs of recruiting, training and providing facilities for this overseas workforce have also gone up. Consequently, savings from process outsourcing are less attractive today.
Unanticipated risks and complications associated with process outsourcing can be disruptive. For example, a volatile geopolitical climate can disrupt operations, as has happened in Ukraine, which is the location of many outsourced operations.
As companies grow and acquire other firms, the process of training, adoption, integrating legacy systems and developing workflow processes must be repeated with the offshore organization. These significant efforts detract from the value the acquisition is supposed to bring to the parent organization and can be very frustrating to the staff involved. Similar adjustments must be made with the introduction of new technologies, and opportunities for insights from predictive analytics were not realized because data was siloed and some vendors declined to share data for analysis.
Offshoring also had unanticipated downsides for the American workforce. Employees experienced considerable demoralization as people were laid off (including colleagues they had worked with for decades) and jobs disappeared across an ocean. Fear of losing one’s job eroded company loyalty, and workforce reductions thinned the ranks of skilled and experienced people here in the U.S.
See also: AI: The Future of Group Insurance
In-Country Outsourcing
Not all outsourcing occurred offshore. Some functions were given over to outsourcing centers in the U.S. These arrangements avoid some of the risks of offshoring; however, manual processing still requires resources for staff, takes time and is not scalable.
Regardless of the location of the outsourcing organization, one reality working against efficiency remained.
While costs may have been lower, processing times were still an issue. Having tasks performed by humans still took time. Policy reviews and other tasks required people to review the documents, do the analysis, check their work and perform any necessary research to verify accuracy. Customers and U.S.-based staff could still experience significant time lags in getting documents analyzed and returned, no matter the location of the outsourced workforce.
Comparing Options
A comparison of different options shows the advantages and disadvantages of three approaches: manual in-house processing, manual outsourced processing and processing by artificial intelligence. The task compared below is policy checking and verification.
Manual In-House Processing: Requires approximately 60 minutes of a customer service representative’s (CSR) time. This staff time, especially at the account executive level, could be better spent focused on customer needs. There is no standard output and no future reference on reviews.
Manual Outsourcing Processing: Approximately 30 minutes of time from a CSR, in addition to the time taken by the offshore team to pick up the job and start processing it. The process is not scalable, there may be quality and data security concerns and there is no comparison of language in the forms by the outsourcing company. As seen during the pandemic, offshore teams were unavailable, thereby delaying E&O checks significantly.
AI Processing: Approximately 10 minutes of time from a CSR. Processing is instant, there is no lag time irrespective of volumes or peaks. AI also delivers instant confirmation of variances, there is a broader risk advisory, differences in language are highlighted and insights are offered in real-time.
See also: Overcoming the Challenges Posed by AI
The Value Proposition of AI
The primary value proposition for offshoring – more work at less cost – is declining with digitalization, which is defined as the process of using digitized data (encoding data by converting it into a digital format, like PDFs for insurance policy documents) to improve workflows by process automation. Intelligent automation has significant advantages over outsourcing to humans in any setting. AI technologies, when implemented right, can make processes cheaper, better and faster than manual processing and deliver significantly improved customer experience.
Speed. With AI, complicated data can be analyzed and vetted within minutes and hours, not weeks and months.
Accuracy. The service level standards achieved by AI exceed those offered by outsourcing services, consistently delivering accurate results faster and with fewer errors.
Instant business insight. With insights gleaned from the analytics performed by AI, executives have fast, accurate information to make better business decisions, increase profitability and even capture new sources of revenue. Implementing intelligent automation with AI allows the entire organization to be “flattened,” with few layers, immediate access to information and the ability to share and act on insights right away.
Savings. The savings achieved from no longer funding outsourced centers or third-party vendors can be redirected to covering operational expenses.
Increased value of American jobs. With the AI revolution, unlike the offshoring migration of 20 years ago, the jobs of American employees are not at risk. In fact, their jobs will be enriched because workers are now armed with accurate data much more quickly than before. Employees have more time to spend on tasks that are client-facing and that deliver high value to customers instead of mundane repetitive task work. As these employees deliver greater value, their own value increases, as well, making them worth more. Automation has historically created specialized positions, which improves the workforce production, earnings and morale.
Will outsourcing disappear with AI? The answer must take into account the role that manual process intake plays with AI. An AI model is only as smart as the data fed into it. This data must be input to a level to educate the model and to continue to allow it to become “smarter” over time. So, manual input will continue to be with us, whether offshored or outsourced in the U.S., but on a much more limited basis once insurance companies adopt AI models.
Undertaking this shift from offshoring to in-house automation is critical to the success of every company in the insurance sector. Fortunately, this transition does not have to be as disruptive and painful as the rush to offshoring was 20 years ago, if this shift is approached with an understanding of change management. It’s important to undertake this seismic task with an end-to-end plan, versus spot solutions, and to have partners with insurance sector expertise who can develop the customized solutions that an individual company will require. The first step is to understand the ramifications and benefits of this transformation, and that it is inevitable for companies that want to be the market leaders of the future.
