BY NATHAN GUMA
ZIMBABWEAN insurance companies have been urged to adopt blockchain technology in the short-term insurance sector to solve crucial issues such as claims handling, sales, and distribution of premiums and premium payments.
This comes at a time when the short-term insurance sector has experienced significant growth amid evolving technology, which has opened opportunities for advancements in claims processing and predicting customer behavior through the use of Artificial Intelligence (AI).
Blockchain technology is a computer program that operates on a decentralized network of computers working together to maintain a shared ledger of transactions.
The technology functions like a digital, shared record book managed by multiple computers, keeping track of transactions as they happen, making it easier to promote transparency.
Each transaction is secured with a special code (cryptographic hashing), which makes any changes highly noticeable, ensuring the information remains accurate and unaltered. Every computer in the network holds a copy of this record book, enhancing its security and transparency.
According to Dr. Shepherd Fungura, ZB Financial Holdings CEO, blockchain technology is crucial for improving various aspects of the insurance sector, including claims handling and premium payments.
“In sales and distribution, decentralized digital ID enables frictionless quote generation as personal data can be safely shared with multiple insurers. For premium payments, smart contracts automate payment processing and policy updates,” he said in his presentation at the 2024 Insurance Institute of Zimbabwe (IIZ) .
“In product management, blockchain and smart contracts could streamline the inception and administration of reinsurance, swaps, and securitisation. Also, in pricing and underwriting, decentralized data provides a large, varied dataset for product pricing.”
Complementary Technologies: AI in Insurance
Dr. Fungura said technologies like blockchain and AI are being used to detect issues such as fraud.
“AI can be used for fraud detection. This can be done using algorithms to analyze patterns and anomalies in claims data. Predictive models can also be used to assess fraud risk and identify fraudulent behavior early.
“It can also be used to meet customer expectations. This is done by implementing AI-powered chatbots and virtual assistants for personalized customer support. These can analyze customer data to understand preferences and behaviors, offering tailored products and services.
“This can also enhance customer experiences by leveraging AI for personalized interactions and services. These can also analyze payment patterns and customer behavior to optimize premium collection strategies. Predictive tools can also forecast premium payments and identify at-risk accounts.”
Dr. Fungura said that AI can be deployed to detect fraud, using algorithms to analyze patterns and anomalies in claims data.
He also said Machine Learning (ML) is also important in predicting customer behavior and preferences to tailor product offerings and pricing, which will enhance market penetration through ML-based customer insights and personalized offerings.
“ML can automate manual tasks such as data entry, document processing, and underwriting. It can also implement workflow automation for claims processing, policy issuance, and customer service while streamlining operations and improve efficiency by leveraging it for process automation,” he said.
Other short-term insurance companies have already started using technology to promote dispute settlement and claims disbursement.
For instance, Minerva Risk Advisors, an insurance broker, is now using geo-spatial data to promote accuracy in quantifying damage while predicting potential risks, revolutionizing short-term insurance in the agricultural sector.
Geo-spatial data typically involves large sets of information that identify the geographic location and characteristics of features on Earth and can include information such as census data, satellite imagery, weather data, cell phone data, drawn images, and social media data.
The data is accessed through free tools like Google Earth and Google Maps. Minerva has been using this data to promote accuracy in insurance payouts.
“There were disputes on claims assessments and settlement, especially on insured yield and insured hectarage; for example, a farmer would insure 100 hectares yet on the ground it is 50 or 150 hectares,” says Simani Wadi, Minerva Risk Solutions managing director.
“Geo-spatial technology addresses issues of moral hazard where farmers might misrepresent the size of their crop or engage in poor agronomic practices to claim higher insurance payouts. By providing real-time and historical data on crop conditions and land use, the system ensures transparency, making it difficult for either party to manipulate claims, thus promoting honesty and trust in the insurance process.”
