It took a deadly virus to force multiple industries to accelerate their digital journey and leverage the potential of its untapped data.
One such industry is the Insurance Industry that sits on a mine of data. It gathers a humongous amount of data regularly, owing to the nature of the business. Today, insurance companies across the globe are adopting newer and better ways to analyze this data, convert it into insights and make accurate data-driven decisions through innovative means.
Data and Analytics are constantly changing the way insurance companies operate. It has always been a fuel for this sector for decades. Actuaries and Statisticians used mathematical models to predict various metrics and parameters relating to insurance, for example, property loss and damage. However, the new wave of analytics has enabled more frequent and real-time views of the traditional reports, supports qualitative assessments, along with predictive and prescriptive capabilities. This new era of analytics also addresses the new kind of questions – ones that you once found difficult to answer due to the cost and time related to the technologies available in the past.
You can now transition from “what happened” to “why is it happening” and ultimately leading to “what will happen.”
Saksoft, with its expertise in big data and analytics can help your company in expanding its analytics framework beyond traditional ad-hoc reporting and make predictions about future trends. By continuously monitoring the data, you’ll be able to uncover crucial insights like detecting fraud, proactively predicting the incoming disasters, getting insights into customer behavior, and warning them about the impending dangers. Through Saksoft’s vast experience in big data and analytics, you can gain a comprehensive understanding of markets, customers, products, services, and competitors on a perpetual basis, streamline the insurance process through data-driven decisions and surpass the competition. In short, Saksoft can successfully bridge the gap between the conventional insurance methodology and the new-age insurance ecosystem.
Impact of Analytics in Insurance
Client-centricity and Improved Customer Services:
An insurance company’s growth strategy is mainly latched onto customer acquisition and retention, cross-selling and up-selling. This can only be achieved if the insurer provides client-focused offerings and an improved customer experience. Data Analytics can be leveraged in multiple ways to accomplish the same.
Clients look for a trusted partner for their insurance needs. With the help of data and analytics, insurers and agents can now generate key insights using consumer data and help their clients with a strategic action plan. One way in which this sophisticated technology may help the insurers in improving their services is by tailor-making policies to fit every client’s need individually and avoid selling fixed policies. Today, insurer’s technology and computer system gather client’s personal data (using telematics that picks the GPS tracking data and sends it via the cellular network to central computers). Hence, if a client is going on holiday but has health problems, the system will automatically offer the person medical coverage that is suitable for them according to the destination they’re travelling to.
Advanced data analytics enables companies to cater to their client’s exact needs, provide timely and efficient services and make them feel valued. This increases the client’s stickiness to the brand and chances are that he/she would recommend it to his friends and family as well.
Detecting Frauds:
Fraudulent cases are increasing in the insurance industry at an alarming rate. It is crucial for these companies to detect fraud applications at an early stage since it causes a whopping amount of money to them, forcing the prices of premium to be up n order to cover for it.
Data and Analytics enables these companies to study the past data patterns which allow them to conclude if the applicant is likely to make a fraudulent claim and an additional investigation is required. Past patterns include the frequency and nature of the claim made by the applicant and his credit score. This kind of data could be anything from a profile picture on a person‘s social media showing information that contradicts what they have said in a claim, to location data from a smart car that shows a person was home at the time they claimed their home was burglarized. Predictive analytics detects any red flag in the claim process, halts the system and alerts the agent.
Mapping Risks and Pricing the Policy:
The insurance sector is instantly related to be a high-risk sector. One of the most important uses of Data and Analytics in the insurance industry is assessing the risk and pricing the premiums before issuing the policy to the applicant. Insurance companies have a variety of data sources (police crime reports, social media accounts, data captured from smart devices, etc) to fetch the applicant’s personal information and rigorously track individual behavior to measure risks and all the unfavorable events which the applicant is facing currently or will face in the future.
For instance, a customer wants to buy an insurance policy for his new car. Traditionally, he would undergo a risk assessment based on factors such as his age, the making, licenses and age of their car etc. But today, insurers can gather data on the areas where his vehicle travels the most, the number of accidents involving that kind of car, and whether the area where the applicant lives have seen a spike in car crime recently. Further, with the help of predictive analytics the insurance company can gain insights on how prone the car to accidents is or getting stolen. All these factors help the insurers in mapping risks and pricing their policies accurately.
Optimizing the Internal Process:
The ability of data analytics to optimize internal processes saves insurance companies massive sums of money each year. Wouldn’t it be nice if businesses could accurately predict which lines of insurance were most profitable and which ones weren’t worth selling? Which policies receive the most claims and which policy is attracting more applications?
Insurers can use real-time data and analytics to address such questions on a perpetual basis. With fluency in data and analytics, insurance companies can also understand how profitable their business is (policy-wise, region-wise etc), refine their products and services to suit the market demands, alter selling/promotion techniques based on customer response, increase per customer and agent profitability and boost its overall performance.
Data and Analytics is continuously taking the insurance sector forward. Saksoft’s vast experience and peerless expertise in Data & Analytics can help your data-rich insurance company to modernize its claim processing practice, make use of real-time data and take strategic and winning decisions to confirm the attainment of their business goals.
