Application and Challenges of Financial Technology in the Digitization of the Insurance Industry

The advancement of technologies applied in the financial sector is profoundly impacting the traditional insurance industry. A survey report by PwC reveals that 74% of the surveyed companies believe that the development of financial technology will pose challenges to their business [1]. Whether driven by external environmental changes brought about by the rise of the sharing economy or operational improvements resulting from technological innovation, it is clear that the insurance industry is undergoing transformative innovation. McKinsey & Company’s report on the insurance industry in 2016 highlights that each step in digital insurance has become an inevitable choice for operators to enhance their competitiveness [2]. Furthermore, Ernst & Young’s latest report on the prospects of the insurance industry in 2022 indicates that after years of rapid development, insurance companies have demonstrated their ability to undergo rapid large-scale reforms, despite facing severe macroeconomic and structural challenges, intense competition, and continuous technology-driven advancement. The insurance industry is gearing up for a new phase of purposeful growth [3].

Digital Applications in Insurance

Currently, the digitization of the insurance industry is supported by three key technologies, the Internet of Things (IoT), blockchain, and artificial intelligence (AI). These technologies play crucial roles in business growth, business production, and business infrastructure. Figure 1 illustrates key aspects of these technologies and their applications in these three areas:

Business  TypeContent
Business InfrastructureData Interoperability and Security (Blockchain)
Business GrowthCustomer Personas and Precision Marketing (Big Data Analysis, Machine Learning)
Business ProductionPolicy Formulation and Pricing (Big Data Analysis, Artificial Intelligence Algorithms)
Underwriting (Facial Recognition, Big Data Analysis, etc.)
Claims (Image Recognition, Cloud Computing, etc.)
Risk Management and Early Warning (Machine Learning, Data Analysis) Customer Communication and Service (NLP, Recommendation Systems, etc.)
Figure 1. Application of financial technologies in different aspects of the insurance industry

In terms of business growth, the analysis of massive user behavior data enables insurance companies to gain deeper insights into their customers. AI models assist in generating detailed customer personas, leading to improved customer conversion rates. Massive user personas are a potential valuable resource, which gives large internet companies an inherent advantage in insurance marketing. For instance, as early as 2017, TouTiao, a news and information content platform in mainland China, began exploring the profiling of individuals interested in insurance, describing their basic attributes and interest. Companies such as Shenlanbao and Duobaoyu, use customer personas to create targeted insurance content on social media platforms to directly acquire customers and facilitate seamless payment conversions.

In the realm of business production, the analysis of massive data and AI models can be applied in policy formulation. By predicting potential risks based on customer risk characteristics and historical data, personalized premiums can be created, delivering greater value to customers. For example, Metromile, a car insurance company in the United States, uses IoT technology (smart onboard diagnostic systems) to access user vehicles and obtain driving data to reprice auto insurance. This breaks the traditional fixed pricing model and implements dynamic data correlation pricing based on big data and user profiles; Underwriting processes can now determine online whether a customer meets the coverage conditions and verify customer identity through facial recognition technology. This functionality is now a standard feature in nearly all self-service underwriting applications available in the market today. Furthermore, during the claims process, image analysis technologies can be employed to assess losses, while data analysis models expedite the claims processing workflow. In the customer service and communication process, intelligent chatbots powered by natural language processing (NLP) can address frequently asked queries and provide real-time support. Data from China’s technology insurance giant, Ping An, shows that in 2022, AI chatbots handled over 2.6 billion requests, accounting for 82% of the total customer service volume. AI chatbots drove product sales of approximately 344.4 billion Yuan, a 25% year-on-year increase [5].

In terms of business infrastructure, the use of blockchain technology can effectively ensure the security and privacy of customer data while providing traceable data exchange processes.

Digitization of Insurance: A Case Study of Ping An Property & Casualty Insurance Company of China

Ping An Property & Casualty Insurance, a leading technology-driven insurance company in China, officially established its “Finance + Technology” dual-driven strategy in 2017. With artificial intelligence, blockchain, cloud computing, big data, and security as its core technologies, Ping An focuses deeply on the fields of financial technology and medical technology, using technology to empower financial development. One of Ping An’s subsidiaries, Ping An Property & Casualty Insurance, applies AI technology throughout the entire process of car insurance claims, enhancing operational efficiency and optimizing user experience.

The application developed by Ping An Property & Casualty Insurance uses internal and external data such as customer driving habits, traffic violations records, accident records, vehicle maintenance records, and credit history to intelligently profile customers and assign different credit limits. Within the eligible range of claim amounts, customers have the convenience of directly filing claims and conducting self-assessments through a mobile app or WeChat mini-program. Users only need to take two accident photos, undergo facial recognition verification, and then can receive claim settlements automatically within a short period. This functionality has significantly reduced the average processing time for similar traffic accidents from 10.59 days to 188 seconds, resulting in a remarkable net promoter score of 89% for user experience, surpassing the traditional auto insurance claim rate of 75.85% [5]. After reporting the incident using the “Smart Flash Claims” feature, the system can automatically upload standardized loss photos, assessment documents, and liability information, allowing the claims adjuster to quickly review and process the claim. Once the user confirms the amount, the compensation can be quickly disbursed within a short period, achieving fully automated claims settlement. Additionally, the system incorporates a risk control engine, which includes features such as image duplication checking, daily data monitoring, and abnormal data alerts, to ensure effective risk management.

Effects and Changes Brought by FinTech

FinTech has brought many changes to the insurance industry, profoundly impacting areas such as enhancing customer experience and changing company operations.

Blockchain technology has had a breakthrough impact on project management, cross-platform integration of resources, and ensuring the security of information flow. For example, Guardtime, a blockchain technology company, collaborated with Sinolink Worldwide Holdings Ltd. (0732.HK) on a blockchain-based marine insurance platform project, integrating different data and processes to reduce data inconsistency issues and decrease error rates. [4]

In recent years, companies that have successfully seized the opportunity of FinTech transformation have generated substantial profits. Take ZhongAn Online P & C Insurance Co., Ltd. (6060.HK), a renowned insurtech company in China as an example.

ZhongAn Online P & C Insurance is China’s first and largest internet-based insurance company, established in November 2013. It was jointly funded by Ant Group, Tencent, Ping An, and other enterprises, with a registered capital of 1.241 billion Yuan and a total workforce of over 3,000 employees, with more than half of them being research and development personnel.[7] The company fully utilizes big data analysis in its business growth process. It leverages links embedded in partner companies’ websites or apps to allow data traffic and accurately push insurance information to customers through big data analysis. It achieves personalized pricing for certain products and strives to improve the experience and efficiency of automated underwriting processes. Additionally, the company provides technology services, profiting by offering customized digital solutions to clients. Figure 2 shows the changes in ZhongAn Online’s technology service revenue and total premium scale from 2017. It can be observed that ZhongAn Online’s technology revenue has consistently grown over the past five years, steadily increasing from less than 30 million Yuen in 2017 to nearly 600 million Yuen in 2022. The total premium scale has also shown steady growth, doubling over the five-year period from 2018 to 2022.

Figure 2. Changes in ZhongAn Online’s technology service revenue and total premium scale

Challenges and Prospects in the Digitization of Insurance Business

Challenges in the digitization of insurance business:

Network data security: Insurance companies hold a large amount of sensitive customer privacy information, making them attractive targets for cybercriminals. According to Indusface’s report “The State of Application Security”, the insurance industry experienced the highest number of cyberattacks in the first quarter of 2023, with 49,844,877 attacks on 114 websites, nearly 12 times the average of other industries. In 2020, an attack on Arthur J Gallagher (AJG), an insurance company in the United States, resulted in the direct exposure of data of 3 million customers, including social security numbers and health details. The company now faces lawsuits and fines for regulatory violations.

Regulatory and compliance risks: The digitization of insurance business applications needs to comply with laws and meet regulatory requirements, which often becomes challenging for insurance companies as they strive to adhere to complex rules and legal processes.

Integration of data resources: Data in the insurance industry is usually scattered in various systems, posing challenges for integrating and cleansing massive industry data.

Prospects in the digitization of insurance business:

Desheng Kang, CEO of ZhongAn Technology, mentioned in an interview in November 2022 that the level of digitization in the entire insurance industry is still lagging behind the banking industry. He described a phenomenon in the industry as a “chimney-style” system, where different business areas and modules are independent systems without integration. To truly realize the value of digitization, it is necessary to “use various data to clearly depict customer personas, fully understand customer value, and not just focus on a single product.” [6] Effectively integrating data resources across systems to achieve system convergence and development will be a new challenge for many technology-driven insurance companies.

The insurance industry will face a time of transformation and innovation, presenting opportunities and challenges simultaneously. With the emergence of new concepts and technological advancements in multiple areas such as the Internet of Things, data mining, and blockchain, more possibilities for business innovation in the insurance industry have arisen. The digitization of insurance business serves as the carrier of this transformation. Based on a comprehensive understanding of relevant applications and challenges, establishing a clear and executable digital strategy to embrace the digital age is undoubtedly a crucial challenge for many companies. Insurance companies need to innovate continuously and actively respond to challenges to ensure the successful implementation and healthy development of digitization, securing broader prospects for enterprise development in a competitive landscape.

Reference

[1] PwC Global Research Team, PricewaterhouseCoopers. (2016) Opportunities await: How InsureTech is reshaping Insurance.

[2] McKinsey&Company. (2016) Harnessing the power of digital in life insurance.

[3] Ernst & Young. (2022)  2022年全球保險業展望: 關注人才培養、目標設定和科技賦能,實現增長

[4] Leo Ronken. (2018) 用區塊鏈技術,為保險業上保險

[5] 財通證券 (2023.06.28). 保險+AI 深度報告:看好豐富數據積累及應用場景驅動下,保險+AI大模型的受益機會

[6] 雜誌:陸家嘴 (2022.11). 眾安科技CEO康得勝: 助力企業數字化轉型,從保險到大金融到全行業

[7] 盧偉傑. (2017.09.26) 東方日報. 科技公司估值大不同

The work described in this article was supported by InnoHK initiative, The Government of the HKSAR, and Laboratory for AI-Powered Financial Technologies.
(AIFT strives but cannot guarantee the accuracy and reliability of the content, and will not be responsible for any loss or damage caused by any inaccuracy or omission.)

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