The Solvency and Asset Management (SAM) regime, the South African equivalent to the European Solvency II, is due to come into effect in January 2015. While the implications of non-compliance to SAM are unknown as yet, compliance is mandatory and experts have predicted that weaker insurance companies may not survive the transition. Insurance companies of all sizes need to find a cost effective solution which addresses the underlying issue of data management to ensure not only compliance with SAM, but more efficient processes going forward.
Similar to Basel II and III for the banking industry, at the heart of the SAM is the fact that risk calculations must be based on provably correct data. Data is the key here, and insurance companies should learn from the experiences of the banking industry in their early attempts to comply with Basel II. In many cases very large, expensive projects were undertaken that did not address the underlying issue – data management.
According to the Financial Services Board (FSB), ‘the primary purpose of SAM is to improve the protection afforded to policyholders and beneficiaries and encourage insurers to adopt a more sophisticated approach to risk monitoring and risk management.’ Poor data quality will therefore have a significant impact on risk calculations. If insurance companies are not certain of the quality or integrity of their data, they must assume the worst case scenario when calculating risk, which in turn may raise the required holding capital amounts to prohibitive levels which may make doing business impossible.
Assume, for example, that we have two related client records. One record shows the client to be low risk. The other, due to missing information, causes a high risk assessment. Under Solvency II the second record takes precedence and the client must be assumed to be high risk. This then ties up unnecessary capital and can eat into profitability. Because of an inability to accurately assess risk, and a resulting higher capital holding level, the insurance organisation itself may also be seen as a bad credit risk. This in turn means that money borrowed will be at a far higher interest rate. Aside from the increased cost of doing business, non-compliance with SAM is sure to have other penalties, which may include fines and trading bans, and other consequences similar to those around Solvency II.
Compliance is not an option, it is something that all insurance companies must do, and the cost of compliance will require certain systems and processes to be put into place. However, insurers should not make the mistake of addressing SAM compliance as a once-off, standalone project, as this will mean that any solution will not be cost effective.
SAM compliance should instead be viewed as a strategic imperative. Insurers should look towards ensuring data governance, in other words the process of managing data as an asset, within a more holistic and reusable framework. The same systems required for SAM compliance can also be leveraged for other purposes, including addressing other regulatory requirements, such as the Foreign Accounts Tax Compliance Act (FATCA) or privacy legislation such as the Protection of Personal Information bill.
This investment will then not only enable compliance to SAM and other legislation but deliver benefits such as improved operational efficiency. Data quality improvements and a more accurate view of customers can also be used to provide more effective marketing, more efficient client service and an enhanced customer experience.
The bottom line is that a short-sighted, tactical approach to SAM compliance may well have the effect of culling weaker companies from the herd. However, SAM by no means dooms these companies to failure, since a strategic approach centred around data governance can drive significant value for the organisation. Using this approach, investments in data quality and data management can be leveraged to address multiple needs.
SAM compliance need not be a death sentence for smaller insurers, and nor should it be viewed as a money pit that requires huge resources and infrastructure. Rather it should be viewed as an opportunity to improve the quality of data within insurance organisations to deliver positive returns across the organisation.