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How Insurance Companies Are Using Bots To Improve Work-Life Balance

CoCo Pierce

Here's the stark truth. Productivity isn't where it should be in the insurance sector. In fact, productivity has barely budged over the past decade in many insurance companies. But why? Despite some insurance companies adopting a digital-first, "work smarter, not harder" approach, many others in the industry still depend on dated legacy systems. The result? Employees are stuck with a brutal routine of manual processes. 

Looking at the US economy at large, the picture becomes even more troubling. In the first half of 2022, productivity (real economic output per labor hour) plunged by 7.4%, representing the worst drop in worker output since 1947. In simple words, despite a strong labor market, economic activity has slowed - and this is entirely down to worker productivity. 

Economists are still determining why we're seeing this sharp drop in labor output, but a dominant theory has surfaced. The theory goes that the economy suffers when it's always someone's first day at work. We're not in normal times right now - overall employment has fluctuated dramatically over the last two years, and people are leaving and starting jobs at record rates. 

The overall turnover rate in the insurance industry was 25% in 2020. Fast forward to today, and 56% of insurance companies plan to increase their staff in the next year, with the top cited reasons being understaffing and business expansion. But does hiring more workers make sense in this climate? Insurance companies run the risk of hiring more people but not boosting productivity. 

Whatsmore, If a company hires someone to do tasks that donʼt add value, then the sum total of productivity across all jobs will be lower than it could be. This is a major problem for businesses because it makes them less competitive than their rivals. With this in mind, let's look at how insurance companies can leverage automation to increase productivity and achieve a better work-life balance. 

The Case for Automation in the Insurance Sector

The insurance sector faces serious challenges in today's increasingly harsh economic landscape. Low-interest rates have particularly hit insurance carriers hard, and as a result, many aren't making their cost of capital. The worrying fact is that the sector as a whole is in the red concerning average economic profit. And with growth stagnating, insurers are under more pressure than ever before to boost performance. 

However, one promising trend arises when looking at the data. Insurance companies in the Life and Property and Casualty (P&C) insurance sub sectors have managed to increase labor productivity through investments in automation. That being said, the rest of the insurance industry has been relatively slow in adopting automation. Part of the reason behind this slow uptake in automation solutions is due to adoption roadblocks. 

These are just some of the barriers insurance companies face when looking to implement bots:

  • IT Landscape complexities: The insurance sector is plagued with complex, inflexible, antiquated systems and processes that present additional challenges. 
  • Data complexities: Due to the dated legacy systems, data typically exists in various formats, some being structured (stored in a predefined format) and some unstructured (no predefined format or organization, making it much more difficult to collect, process, and analyze). 
  • Accounting for context and nuance: Claim requests can be nuanced, making it challenging to define neat rules for processing requests. 
  • Senior buy-in: Many high-ranking employees in traditional sectors are skeptical of the benefits of automation or believe it is too risky to pursue. 

But critically, if insurance companies can overcome these barriers, they look to gain significant benefits, including:

  • Boosted accuracy: Robotic process automation (RPA) allows companies to scale growth while ensuring accuracy isn't compromised. Many tasks within the insurance sector demand a high level of data accuracy and integrity. Small mistakes can be very costly. RPA vastly improves accuracy rates by eliminating human error. 
  • Enhanced speed: RPA bots can work on average four times faster than a human worker, and some studies put this figure much higher. Smart bots also don't need breaks, take vacations, or become demotivated, no matter how tedious the task is. 
  • Reduced costs: Automating repetitive, rules-based processes improves efficiencies, reduces costly errors, and accelerates processing costs. Companies can achieve 25% to 50% cost savings by boosting efficiency. 

Improving Work-Life Balance

The last few years have been incredibly tough on insurance agents and brokers. Many have been working around the clock amid a global pandemic, natural disasters, and economic downturn. The result is a highly stressed and burned-out workforce. 

It should come as no surprise that overworked and agitated employees don't produce their best work. Instead, they often feel overwhelmed, demotivated, and less creative. So, if insurance companies want to improve employee happiness and well-being, it's paramount they find a way to foster better work-life balances within the company. 

A recent eye-opening survey by Salesforce found that 91% of full-time workers say automation tools save them time and offer better work-life balance. Moreover, a whopping 76% of workers say they are more satisfied with their stress levels due to automation. 

Top Automation Use Cases in Insurance

Now, let’s look at some of the ways automation is transforming the insurance industry today. 

Claims Management

Claims management (claims registration and processing) involves collecting vast amounts of information from various sources. Luckily, RPA makes gathering and integrating all the different claim-processing information from multiple sources easy. Robotic process automation bots can handle labor-intensive processes like data extraction, complex error tracking, claim validation and verification, and more. 

And critically, insurance companies can vastly speed up their claims processing operations by deploying RPA for claims intake, assessment, and settlement tasks. For example, when done manually, claim processing can take several days, taking insurance agents away from more valuable work. At the same time, even the most careful and diligent insurance agents make mistakes, causing further delays. RPA bots combat these issues and allow faster and more accurate claims processing, driving customer satisfaction. 

Payment Processing 

Many of the tasks involved in accounts payable and accounts receivable are time-consuming and resource intensive. However, many insurance companies still rely on manual labor for these tasks due to the lack of an efficient alternative being available. RPA bots are that efficient alternative waiting to jump in. 

Payment processing bots can capture payments from multiple sources and post them against invoices. RPA bots can also grab incoming invoices, sort invoices with and without purchase orders, and store payment information in dedicated areas like the Accounting/ERP system or elsewhere. 

Data Scrubbing 

Insurers can leverage RPA bots to assist in data cleansing. By using bots in this way, insurers can create and maintain well-structured and correctly classified data across their enterprise applications. This is especially crucial because of the industry's regulatory compliance obligations. How do you assure regulators that you're correctly handling data when you don't have a good grip on where that data is and its integrity? In addition, having clean data allows for more robust data analysis, driving better decision-making in the business. 

Policy Management

Another top use case for automation in insurance is in policy management operations. Here, policy management means issuing policies and updates. When a policy is ready to be issued, the pre-underwriting checks are complete, and the underwriting decision has been finalized. Next, the policy needs to be issued and communicated to the customer, and all corresponding information needs to be updated in the company's internal systems. Done manually, this can take workers several hours. However, RPA bots can automate insurance policy issuance, extract inbound changes from various sources (emails, faxes, documents), and update internal systems, all within minutes. 

Underwriting

Underwriting requires evaluating your client's risks and exposures. To do this, insurance companies need to gather information from disparate sources and assess the risks as they relate to a given policy. This whole process involves a great deal of data collectin and analyzing before any decision can be made. 

RPA can help by automating the data collection process. For example, RPA bots can extract data from both internal and external sites and sources without human input, vastly reducing the time taken for underwriting. Bots can also populate multiple fields in internal systems to produce an audit trail, generate reports, or make new recommendations. 

Final Thoughts

Insurance companies continue to be challenged by quickly evolving customer needs, fluctuating job market dynamics, and fierce competition. For the workers in this industry, these challenges mean longer hours and more stress. Luckily, there's a better way forward. 

The insurance industry is highly dependent on the efficiency of back-office processes, and automation offers a way to supercharge these processes. RPA can help insurers achieve elevated profits, improved compliance, lasting company growth, and world-class customer service while lowering costs and reducing employee turnover rates.

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