Also known as a company’s ability to reconfigure the way work is done, operational agility has quickly become a core strategy for businesses that want to stay connected, flexible and productive both internally (among employees and teams) and externally (among partners, suppliers, and customers). Reliable connectivity and cloud-based solutions lie at the core of end-to-end operational agility because they ensure a resilient infrastructure that can successfully cope with today’s increasing demand for the use of digital channels and advanced technologies.
Process automation enters the scene the moment organizations take that leap of faith towards digitalization. The implications involved are diverse since automating processes consist of changing everything within the structure of a company, starting from the corporate culture all the way to technology and IT-based solutions in use.
In industries like insurance and banking, organizations are rushing to think and act more digital to meet the digital demands of modern, tech-savvy customers. And yet, 34% of US-based financial institutions and 50% of insurance companies still depend on manual data. In this article, we will focus on the way process automation supports end-to-end operational agility to help organizations streamline key business processes, speed loan processing, detect fraud, and delight customers.
Speed loan processing
Process automation can support end-to-end operational agility by speeding loan processing timespan. Many insurers still use paper documents to fill out loan applications, which takes time and is predisposed to human error. Dealing with hundreds of pages of documents on a daily basis can be daunting for both the insurance company and the client. To gain a competitive advantage, automating processes will enable organizations to reduce the time spent on manual work; therefore supporting operational agility and helping insurers deliver the best services a lot faster.
Companies need to address and understand the digital nature of buyers today. AI coupled with RPA (robotic process automation) based solutions accelerates daily processes, taking down manual work and improving workflow to meet the customers’ needs. 71% of home loan lenders in the US agree that advanced technology can help them set themselves apart from the competition.
Intelligent automation software WorkFusion helped one of the top 10 US banks implement the WorkFusion Smart Process Automation (SPA) solution to speed loan processing time by two times. With the help of SPA-trained bots, the bank was able to extract key data automatically from unstructured loan documents, enabling the bots to interpret the data and handle repetitive work a lot faster. The end result was a complete shift of focus of the team towards outcome validation and reviewing complex loans with more accuracy.
Lesson to learn: In a world of advanced technologies, spreadsheets, old-fashioned legacy systems, and disparate databases demand lots of physical work that only makes processing loans tedious and complicated. By automating processes with AI and RPA, organizations have better chances to stand out, speed loan processing time, and become truly agile in a highly competitive FinTech industry.
According to CNBC, 1 in 109 mortgage applications are predisposed to fraudulent claims, and such incidents are on the rise. Applicants have gotten used to lying about their income to get a loan, which is why, to provide better transparency, organizations can battle human errors with automated software solutions. A combination of AI-based solutions and process automation will impact operational agility by greatly reducing the number of forged loan applications. Together with deep learning technology, there’s an increasing chance to become more efficient at performing precise, real-time analyses to take out noncompliant applications following predefined factors like historical data.
Singaporean insurance company, FWD, recently joined forces with Shift Technology to implement FORCE, a fraud detection solution that leverages AI to analyze and structure insurance claims, thus eliminate potential fraudulent claims by analyzing multiple data sources. FWD's CEO in Singapore, Abhishek Bhatia, talked about the partnership, highlighting:
"At FWD, we're committed to leveraging digital technology to make insurance simple, reliable and direct for our customers, and our collaboration with Shift Technology is a strong demonstration of our customer-led approach. Working with Shift also gives us greater confidence in applying straight-through processing to a larger number of claims, helping to shorten the turnaround time for claim payment and ultimately improve the customer experience."
Lesson to learn: In 2017, insurance companies in the US alone lost $34 billion on fraudulent insurance claims. To avoid such loss in your organization, automating processes with technologies like RPA, AI, and machine learning won’t just keep ROI on the floating line; it will also support operational agility, meaning that work inside your company will be done more accurately, which in turn preserves employee engagement and containment.
Delighting customers with seamless services
One of the core challenges of insurance companies worldwide is to ensure a seamless customer experience across the full cycle of the mortgage lending process; a process that must be approached from the perspective of the modern digital customer. The problem is, exceeding expectations without any technological solution in place is nearly impossible in today’s digital world. By automating processes, lenders have better chances at gathering applicant data, drawing documents, onboarding and billing the customer, validating credit, and ultimately collecting monthly payments.
Digital consumers are compelling organizations to implement a fully agile system into their business model to streamline operational agility; a system that will work in the benefit of everyone involved provided automation is done right. Adding RPA and AI into the mix doesn’t just improve internal processes. It also helps delight customers by making their journey across all channels faster, more efficient, and more accurate, the end goal being to build brand loyalty.
In attempt to stay competitive among other digital insurance startups, one of the largest property insurers in the US, Allstate Corporation, implemented Amelia to revamp its customer service strategy with automation. The cognitive, AI-based agent aims to deliver services a lot faster, reduce handle times, and improve satisfaction among its customer base. Senior Vice President at Allstate, Carla Zuniga, mentions that: “Amelia is quickly becoming an important component of our customer service strategy. She provides our call center personnel with the information and procedures they need to address our customers’ questions and concerns.”
Trained to handle over 50 industry-specific topics, Amelia answers customer questions, while also drafting customized policy information. Deployed back in 2017, Allstate officials mentioned that call durations were reduced from 4.6 minutes to 4.2 minutes; furthermore, 75% of customer issuers were fixed during the first call with Amelia, as opposed to 67% when Amelia was not used.
Lesson to learn: AI-based technology has proven to work miracles in customer service departments across numerous industries. In insurance, such solutions can provide consumers with the right information and the right time, delighting them and convincing them to become loyal brand advocates.
Conventional back-office processes ruled by repetitive tasks and piles of paper documents are still present in many of today’s insurance organizations. Those that refuse to adapt to the needs and wants of the digital customer will get left behind. Relocating data from old-fashioned spreadsheets to highly digital systems will soon become the norm. As CEOs and CIOs continue to acknowledge the benefits of automation in supporting end-to-end operational agility, we anticipate a mindset shift in process automation supports operational agility in the years to come.
In fact, the average spending on AI and cognitive-based systems are predicted to reach $77.6 billion by 2022, up almost three times from $24 billion in 2018. According to the most recent IDC Spending Guide, a significant amount is reserved for developing even better AI applications like machine learning, deep learning, and chatbots apps. The end goal will be to automate processes with the consumer in mind, constantly improving experiences and exceeding expectations.
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