Technology And Trends Shaping Insurtech In 2019 And Beyond
InsurTech – Multiple disruptive forces are reshaping the global insurance sector. Technology such as artificial intelligence (AI), machine learning (ML), blockchain and internet of things (IoT) solutions stand on one end, and nimble, innovative insurtech startups sit on the other. These technology advancements are forcing traditional incumbents to rethink their business models and accelerate their digital transformation strategies.
In the coming months, insurance as we know it will undergo rapid transformational changes that include the following trends.
Back-end workflows within the insurance enterprise (including underwriting) will be automated to a large extent using AI/ML. This will lead to shorter and more efficient value chains. Most client-facing processes, such as claims management, quote processing, policy-related queries and more will be automated as well, by way of data capture, document processing and customer conversations.
Personalization And Fraud Detection
Consumer behavioral data (gathered from social media feeds, IoT devices, etc.) will be leveraged to devise more personalized insurance offerings, enable advanced risk assessment and detect and reduce fraud. Blockchain technologies, such as smart contracts, will usher in “trust” fabrics that will enable smooth data-sharing and prevent fraud across both the general and reinsurance domains.
AI And ML
Software’s ability to continually learn and make intelligent decisions based on that learning has the potential to greatly accelerate claims management, customer support, automation routing, underwriting applications and more.
Internet Of Things
New monitoring technology built into automobiles that combines GPS solutions with onboard diagnostics makes it possible to map and record exactly where a car is, how fast the car is traveling and then cross-reference that data with how a car is behaving internally. This will help insurers to provide optimal policy pricing.
Drones And Satellite Imagery
Drones and satellite imagery are being used by the insurance industry today to assist in claims processes and reduce inspector risks. Novarica estimates that 16% of property and casualty (P&C) carriers either plan to or are actively pursuing drone initiatives. Even further, PwC suggests drones will have a $6.8 billion impact on the insurance industry in the coming years.
Intelligent Process Automation (IPA)
IPA is the next generation of process automation that deploys process automation as a service. IPA includes back-end as well as end-user journeys for brokering information and data using advanced AI/ML techniques and conversational automation. According to McKinsey Digital, a number of companies in different industries have been successfully with IPA. They’ve found that automation can be used for up to 70% of current tasks. This has translated into run-rate cost efficiencies between 20% and 35%. It has also led to a reduction in straight-through process time by 50% to 60%. And, as a result, these companies are often seeing an ROI in the triple digits.
Out of all of the new technologies available to the insurance industry today, the one that will likely have the biggest impact is IPA. Today, RPA products are primarily focused around automating high-volume repetitive tasks, such as data entry, extraction, etc., and they use older screen scraping techniques. However, the combination of RPA with AI/ML, natural language processing (NLP) and computer vision is leading to the next “cognitive” stage of its evolution. There are a multitude of processes within the insurance enterprise that are being automated today via IPA platforms, including:
1. Smart Email Triage
A large number of interactions between insurance companies and their customers/partners happen over email. Cloud-based IPA platforms are employing NLP algorithms to classify and triage these emails in real time. By integrating IPA platforms with back-end work management software, incoming emails can be automatically routed to appropriate work queues, thus reducing human dependence and leading to improved average handling time (AHT).
2. Intelligent Data Extraction
Quote intake or claims processes involve the distribution of insurance policy applications, authorization forms and supporting documents such as physician summaries. These datasets typically consist of both structured and semi-structured blobs buried across various document sources such as emails, PDF documents, spreadsheets, scanned images, etc.
IPA platforms use ML with optical character recognition (OCR) and other techniques to extract data across these heterogeneous formats and then employ advanced information retrieval algorithms to extract fields of interest. If values pertaining to certain fields are missing, separate engagements can be initiated directly from the platform to the customer for collecting the remaining data.
Once all of the relevant data is extracted, it is exported to industry standard formats, such as Association for Cooperative Operations Research and Development (ACORD), or passed on to core systems via an enterprise service bus (ESB) bridge or, in most cases, APIs
This article originally appeared on forbes.com To read the full article and see the images, click here.
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