Cost Structures Shake-Up: Intelligent Automation At Play
In an August 2019 article, it was reported that many industries had been able to capitalize on their investments in digital technologies. However, insurance industry was lagging behind and hadn’t increased overall productivity in the past decade.
In its “Future of Lloyds” prospectus, the Lloyds group had lamented that, “The industry’s 30% or more cost of doing business does not compare favorably to the 4–13% cost of an equity IPO.” The explanation it offered was that while many complex products are inherently costly to transact, the sector has not stripped out other costs by modernising systems and processes quickly enough, leading to higher costs. Acquisition costs can also be high even for more commoditised products. The prospectus further explained, “Our industry needs to get closer to end customers and reduce costs across the distribution chain in areas where it is not adding value to customers.”
Labor Productivity and Cost Ratios
In the August 2019 article, McKinsey partners Bernhard Kotanko et al surmise that while investments in automation have boosted labor productivity, overall cost ratios have not improved.
Carriers have increased labor productivity in many areas of the value chain through investments in automation and improved sourcing. These improvements were particularly high in policy servicing and claims. The flip side of the investments is often higher costs, such as in IT.
In addition, commoditization of some product lines is leading to lower prices, regulations are driving up costs. Standard cost-cutting strategies yield limited results due to complexity.
Besides, emerging risks along with increased frequency and severity of natural catastrophes (as evidenced in combined ratio figure) threaten to further undercut performance.
Incumbent insurers have taken action, but within their existing operating models: tight budgeting, reviews of spends and functional cost programs. Cost reduction efforts are having a positive effect on economic profit — but only for leading insurers due to scale and other conducive effects.
The traditional approach of focusing on functional efficiency and stringent cost management has produced results, but not substantial enough. What the need of the times is to drive a more aggressive, structural approach to reduce complexity and enhance productivity. Beyond efficiency, effectiveness of individual processes (e.g. in underwriting/claims) as well as an excellent customer experience can shake up the cost structures. To enable this, key levers are simplification (of org structure, product offer etc) and transformation (of customer experience, process optimization and intelligent automation). In the rest of this article, we elaborate on the transformative power of intelligent automation aligned with customer experience and process optimization.
Modelling The Impact of Intelligent Automation
As this BCG research paper highlights, intelligent automation will be increasingly deployed at scale, supported by intelligent analysis and decision modeling. Their research identifies customer experience rehaul areas across six core segments of the insurance industry value chain. Using intelligent automation, core segments of:
- Marketing and Sales (Via Cross/Up Selling And Loss Prediction)
- Underwriting and Pricing (Via User Behaviour Evalution and Property Status Evaluation, Underwriting Automation)
- Policy management and services (Via Smart Identification Of Customer Requests)
- Claims (Via Remote Investigation and Workflow Optimization, Fraud detection), along with other such, are expected to improve efficiency in 75% of jobs by 29%, a reduction of 1.8 hours per person per day and reduce the number of jobs by 25% over next few years.
While automation is not new to the insurance industry, in the past couple of years there has been a shift in both the maturity of the tech and availability of additional tools that insurers can use as part of their key processes.
Evolution of Intelligent Automation
Intelligent Automation refers to the combination of multiple automation technologies, such as Robotic Process Automation (RPA), Machine Learning and Cognitive technologies, used together to solve business issues.
While delivering value beyond cost savings, it helps streamline current processes to improve customer wait times and enable skilled employees to focus on high-value tasks, concomitantly enhancing quality, auditability and employee satisfaction.
On average, insurers leveraging Intelligent Automation are reported to reduce operations handling time by 40 percent.
Three classes of Intelligent Automation (IA) include:
- Robotic Process Automation (RPA) — which automates repetitive rules-based tasks and processes by applying a consistent set of rules to structured data to deliver a consistent, efficient outcome. Used in structured repetitive tasks such as reconciliation, billing and policy updates.
- Enhanced Process Automation — which works with unstructured data, recognizes patterns to predict course of action, and learns from interactions to improve performance over time. e.g. a P&C insurance company using bots enabled with text analytics to identify and escalate transactions based on counterparty.
- Cognitive Automation — which answers complex queries and performs tasks previously done by humans.
Swiss Re successfully automated 100 processes with RPA. The solutions perform the work of approximately 65 FTEs every year. Its initial pilot program reduced existing bank account reconciliation process from 15 business days to just three — a 80% reduction.
Other Examples Of IA
AXA Belgium implemented solutions for smart mail classification using IA along with a chatbot for Q&A. One solution extracted handwritten information from the European Accident Form in real-time. It speeded up data entry (10 seconds instead of 4 minutes with manual antry) and enabled end-to-end claims automation.
Metlife Claims made significant strides in improving claims accuracy, costs and in the process, enhanced customer experience. They built an intelligent automation engine to segment and analyze claims, with eligible claims automatically adjudicated in real time, reducing TAT from 12 days to 15 minutes.
Kyobo Life has developed the Best Analysis & Rapid Outcome system to improve efficiency of insurance underwriting. It is designed to minimize evaluation time and maximize underwriting efficiency for simple cases, freeing up underwriters and allowing sales to query the system.
PZU, the winner in the Workforce Transformation category has a RPA factory, that implemented more than 50 robots to perform 250k+ operations per months and interact with 2300 employees in client service and claims handling.
These carriers were recognized in the Efma awards for their pioneering work in smart automation in the latest edition of the innovation awards.
A good set of initial key use cases (based on complexity) being adopted are mentioned alongside here.
Broader Adoption
In an Accenture survey of technology trends involving 400 incumbents and insurtechs, we see broader adoption of IA technologies but also subtle differences in tech focus trends between the two groups. The differences can be partly explained by legacy structures inherent in the former and lesser org / business line complexity of the latter.
End Note
Digitization coupled with intelligent automation, is driving an unprecedented shift towards lower cost structures and greater agility among insurance incumbents and challengers. Market leaders such as Allianz, Axa, Generali and Zurich have all announced cost savings programs in which intelligent automation with digital tech play a major part. Both groups are launching greenfield offerings, wherein cost leadership is driven partly by a monoline focus and absence of legacy but also by digital-by-design products and processes.
Achieving the seemingly ambitious targets of cost structure revamping will require carriers to benchmark current costs, overcome hindrances by redesigning businesses and reshape their current structures following a clear set of implementation actions.
