Life Insurance International lists the top five terms tweeted on insurtech in September 2020, based on data from GlobalData’s Influencer Platform. The top tweeted terms are the trending industry discussions happening on Twitter by key individuals (influencers) as tracked by the platform.

1. Fintech – 480 mentions

The ways in which different emerging technologies are impacting industries and how the insurance industry can recover from the pandemic through innovation were popularly discussed in September. According to an article shared by Kirk Borne, a principal data scientist, technologies are disrupting every landscape including finance and insurance. For instance, AI-powered chat bots have enhanced consumer messaging experience, while holographic workstations are becoming a standard tool for traders and analysts.

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Mike de Waal, the CEO of Global IQX, a computer software company, further tweeted about how the insurance industry could better survive the pandemic through innovation. For instance, the dramatic fall in driving during the successive lockdowns prompted auto insurance carriers to return a part of the premium payments to their customers.

Insurance providers can also cut costs and improve accuracy and speed of processes by deploying artificial intelligence (AI) and even leverage third parties who may be using disruptive technologies, the article detailed.

2. Artificial intelligence – 266 mentions

How data and AI will become the new normal for the insurance industry and how insurance companies are moving past the pilot phase of AI adoption were some popularly discussed topics during the month. According to an article shared by Mike de Waal, data and machine intelligence will become the new normal in insurance as the industry gradually embraces digitalisation.

AI and machine learning tools have the pre-emptive ability to improve decision-making, and the technology works well when applied to humans, the article stated. In the insurance industry particularly, AI and machine learning have the ability to automate every area of the supply chain. Personalisation will be a key factor, as a major demographic of the digital insurance consumers base will be millennials in the next three to five years, the article added.

Among other discussions, Spiros Margaris, a venture capitalist, discussed how various sectors were moving past the pilot phase of AI adoption. The article detailed that although most organisations had begun investing in AI, only a handful are able to scale and reap its benefits. Sectors such as insurance, telecom, and manufacturing, among others have deployed AI, but they are yet to scale their use cases entirely, the article noted.

3. Startups – 109 mentions

Insurtech start-ups raising new financing and insurance partnerships to improve insurance and payment methods were popularly discussed topics in September. According to an article shared by Lex, an entrepreneur and futurist, Amazon-backed auto insurance start-up Acko has raised $60m in a new financing round.

Acko entered the healthcare protections space six months ago, selling to employers and businesses, and has approximately 1,50,000 employees covered under its health protection plans, the article noted. The company also sells insurance to its customers, either directly or through partners such as Amazon.

Among other discussions, Mike de Waal, discussed the partnership between Google’s subsidiary Verily and Swiss Re Group, a reinsurance giant. Verily has launched a new subsidiary, Coefficient, under the partnership to integrate health technology solutions with insurance and payment options. The new company will be supported by Swiss Re’s subsidiary Swiss Re Corporate Solutions, the article detailed.

4. Cybersecurity – 62 mentions

The use of blockchain in insurance for better risk visibility and cyber insurance being used to solve cyber-related incidents were popularly discussed during the month. According to an article shared by Michael Fisher, an analyst and tech evangelist, blockchain technology has numerous benefits for the insurance value chain. Right from fighting fraud to data transparency, blockchain use cases in insurance are immense.

The insurance industry has been sluggish in adopting the technology and the legacy systems have resulted in operational inefficiencies. Additionally, the possibilities of human error caused by manual entries often leads to misinterpretation, loss of data, and even cyberattacks. Blockchain adoption in insurance can streamline market operations and improve collaboration between the various stakeholders.

In other discussions, Dr Robin Kiera, an insurtech and digital transformation expert, shared an article on whether cyber insurance will be able to solve cyber-related incidents in the next few years. The next 12 months is riskiest for the insurance sector, as cyber-related losses across various businesses are expected to rise.

In addition, technological advancements in 5G and IoT are adding more complexity and risk to an already risk exposed landscape. Cyber insurance and a partnership approach is the best way to close coverage gaps of clients and ensure continued coverage for new cyber threats, the article detailed.

5. Deep learning – 56 mentions

How machine learning, deep learning and AI applications are paving the way for a data-centric era of discovery in healthcare and enabling insurers to achieve digital transformation were popularly discussed during the month. According to an article shared by Spiros Margaris, a venture capitalist, AI, deep learning and machine learning models are taking precision medicine to new levels of accuracy and prediction in patient outcomes.

These technologies have been able to classify all precision medicine factors using different algorithms to detect, diagnose, predict, and derive treatment options for diseases, the article detailed. As a result, the technologies are making treatments more accessible and affordable for those who cannot afford the cost or insurance during emergencies.

Deep learning was also mentioned in the context of leveraging technologies for digital transformation. AI along with machine and deep learning models will witness a strong interest in the coming years, according to an article shared by Andreas Staub, head business development and digital transformation at Raiffeisen, a banking company. Deep learning can help insurers in detecting fraud by finding implicit correlations in data and can also assist in quicker claim settlements and in understanding claims cost.