Oliver Plaistowe, Vice President of EMEA and APAC at Angoss, regards data as a key facet to increased growth for insurance companies. “We have equipped insurers to leverage the data flow from various sources and decipher it for useful risks analysis,” says Plaistowe. Insurers are utilizing analytics technologies to make sense of the growing amount of internal and market data. In order to understand the dynamics and importance of data storage, Angoss is employing a two-pronged strategy. This involves combining multiple sources of information for predictive data analysis, in addition to striving for insights from data and understanding customer behavioural models. The analysis that is derived is then put into practice to deploy business rules and apply customer strategies in real time. Customers are always keen to put their faith in the brand value and pricing regime offered in insurance plans that are based on Angoss’ analytics and insights.
With every passing year, insurance companies continue to incur greater losses due to the increase in fraudulent claims. As a result of this, they are driven to reach out to Angoss for fraud detection solutions.
We have equipped insurers to leverage the data flow from various sources and decipher it for useful risks analysis
“We are investing resources to weed out fraudulency from the insurance system,” says Plaistowe. By assessing customer losses with reactive, real-time data analysis, Angoss’ fraud detection gets management to deploy the expertise of the Angoss’ platform. Angoss’ platform is working to incorporate data from ever-expanding sources, such as social media and call centers. Angoss attempts to extract information that varies in nature, e.g. customer needs and customer apprehension towards pricing regimes. This gives an upper hand to insurance companies in understanding the customer’s preference for flexible pricing.
Angoss continues to gain market coverage and create increased margin opportunities with great success and efficiency for its customers. As such, a slew of insurance companies have lined up for their insurance analytics platform. One noteworthy success story involves a top 5 British insurer that sought a price optimization model so they can identify new streams of revenue. “The client produced an eight week data of the purge and needed us to build a working solution that they could incorporate in their business strategies. We did that in 2 weeks,” says Plaistowe.
Moving forward, Angoss’s continuous focus will be developing new algorithms and predictive models, while making room for coding languages like Python, Java, and C among others. As the insurance sector sees a lot of potential upheaval from global economies reforming their policies and regulations, data analytics will become an imperative asset for this industry in offsetting disruptions in their services.