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There's more to gain from regulations than just compliance
Get real business value from the Solvency II exercise
By Thorsten Hein, Risk Center of Excellence, SAS
You can’t make the right business decisions without a clear understanding of your real risks related to customers, products, regions, capital market activities, reinsurance strategies, etc. Now, there’s an additional need for this information – Solvency II requirements. And the regulatory authorities will drive the timing and level of detail for collection and disclosure. From 2016 onward, the information will also be needed to calculate the regulatory capital requirements. But in terms of the type of information, there’s nothing new.
The things you are doing now to prepare for Solvency II implementation can benefit your business in many other ways. For instance, do you know which customers, regions or products are your most profitable? Do you know where you are leaking profits? Are you really sure that your current reinsurance strategy is closely aligned to your real risk exposure? Do you know how much money goes out your door due to claims fraud?
Insurers have lagged behind other industries in adopting analytics across the organization – isn’t it better to get out in front of this thing – and get some extra benefits?
You need to start thinking and acting in a far more integrated way and align your data, processes and resources.
According to an FC Business Intelligence Survey from June 2014, 72 percent of insurers believe “analytics is the biggest game-changer for the insurance industry in 2014-2015.” But only 26 percent say they are using analytics across their entire business. Here’s the ironic part: 92 percent of those polled said that they are using analytics in at least one area of the business. Here are the top six areas where they’ve found the most gains:
- Underwriting – 50 percent.
- Pricing – 45 percent.
- Claims – 36 percent.
- Marketing – 34 percent.
- Fraud – 27 percent.
- Customer insight – 21 percent.
If there’s so much to be gained across those very important areas, why are so few taking advantage of it? According to the report findings, “Overcoming the silos and getting your data in the right place at the right time” is one of the key challenges insurers still need to overcome. And “using analytics to drive efficiency and collaboration across the business” is the next biggest challenge.
But there are some huge benefits: Faster collection and analysis of underwriting data can help you get a more accurate and timely estimation of economic capital requirements that might influence the overall profitability. Finding the right balance between price, claims reserves, risk mitigation and – again – economic capital requirements taking into consideration carious market scenarios can result in much faster development of profitable products ahead of your competitors. And this is just the beginning…
Big data, bigger advantage
Given the magnitude of data – i.e. customer behavior, claims projection, most probable economic and environmental scenarios, etc. - at your disposal, now is a great time to expand your analytics use across the entire organization. Those insurers who build a robust analytics program that capitalizes on their big data will significantly improve pricing precision and go-to-market capabilities. Such big data could, for example, come from the vast field of telematics and mobile phone usage. Insurers might be able to track vehicle usage of the insured person and get a better idea of the overall mileage and the travel patterns (i.e. many short term trips within a city district, vs. few long-distance trips including crossing borders into other countries). You could also design products in a ‘pay-as-you-drive’ fashion and charge a premium that reflects the underlying risk of the real vehicle usage – including putting penalties on higher risk activities such as frequent traveling to other countries or areas not covered by the insurance, or speeding incidents. Of course, this would require to make use of existing data and, for example, train a predictive model that will suggest the appropriate rate and terms & conditions, based on the existing vehicle usage of an applicant. In extreme situations, you might also be able to deny coverage if via predictive modeling you detect a high risk applicant.
Summing it up, you will be able to design more individually attractive insurance products that meet both the individual requirements of your customers and that will enable you to better chose the profitable ones. You will have a far deeper understanding of your customers and a more effective loss prevention strategy and you will be able to manage your risks more proactively.
Further on, big data analytics techniques can also provide significant benefits to fraud prevention and detection. The key points that each insurer should think about are: Why in the first place should we do business with fraudulent customers? Can we avoid it or at least control and prevent the upcoming loss? In order to enable insurers to tackle organized claims fraud rings, they need to embrace Social Network Analytics techniques for identifying fraudulent ring schemes, within their underwriting and the claims processes. These techniques require massive volumes of historical data with both great veracity across all business lines and products and high velocity for instant or even ‘real time’ decisioning. This enables you to avoid doing business with potential fraudsters and dramatically minimize your fraud costs.
The external market drivers are getting more and more complicated and dependent on each other. So you need to stop thinking and acting in that old-fashioned silo-based approach in order to keep up with the market and be faster than your competition. You need to start thinking and acting in a far more integrated way and align your data, processes and resources.
Don’t just sit back and wait for the regulators to judge on your risk management models and processes. Check out SAS' insurance solutions that will enable you to make the necessary changes required for both achieving compliance and having a huge impact on your profitability!
Contact the contributors to this article on LinkedIn:
Thorsten Hein, Risk Center of Excellence, SAS
Stavros Stavrinoudakis, Professional Services & Presales Manager, SAS
Stefan Ahrens, Business Expert Analytics, Analytics Center of Excellence , SAS