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Actuaries reduce TAT using AI, ML & Big Data

Andy Rallis, global chief actuary of MetLife and the immediate past president of the Society of Actuaries, shares insights on the evolution of actuaries during the pandemic.

Ashish Verma: How has the actuary space evolved in the pandemic phase?

Andy Rallis: Actuaries are the leading professionals in finding ways to manage risk. The pandemic represents a type of risk that has not been encountered for several generations. It has had an impact across all parts of a company’s financial statements and daily operations, making it crucially important for the profession to use their risk management techniques. It has also led to public health issues, which makes it even more imperative for companies to evaluate risks, especially those associated with finance, insurance and related fields as the frequency and size of claims can spike dramatically. So actuaries have been assessing and responding with new ways to mitigate the health, mortality and financial risks posed by this new form of risk, particularly with respect to the financial security systems and programs.

How has the actuary space affected the job of insurance and risk analysis?

Insurance and risk analysis has become both easier and more difficult. The risks and their interdependencies have become more complex. However, the tools and models that actuaries use have also become more sophisticated. We now have the advantage of big data and artificial intelligence that were not readily available just a decade ago. The opposing forces of risks and risk management are both developing rapidly. Insurance business leaders are aware of these rapid developments and are open to using new models, although most are also cognizant of the need for appropriate governance practices related to model development.

What kind of skills and tools have emerged for the actuary space?

Actuaries already use advanced software to develop new methods of calculating and analysing data. Today, due to an increasing need to respond rapidly, actuaries no longer have the luxury of longer periods of time for risk analysis and planning. Actuaries have always been required to have strong technical skills and knowledge (IQ), and those who would rise to leadership roles also needed strong emotional intelligence quotient (EQ) skills. But the rapidly transforming environment of the past two years also requires adaptability quotient (AQ) skills. With accelerated automation, applying a level of emotional intelligence a machine is incapable of and providing insights from it, will be of utmost importance.

Tools that have been of importance include the ability to manage and appropriately utilize large quantities of data – much larger and more complex than have ever been available before – and build models that properly assess key components of the data and recognize interdependencies.

How much can AI and analytics help in making underwriting and risk analysis stronger?

Underwriting and risk analysis (in addition to marketing) have been some of the earliest and strongest users and beneficiaries of artificial intelligence (AI) and analytics in the insurance industry. In a post-covid world, investments in building the foundation of data are becoming increasingly critical. Insurance companies have been increasing their focus on data transformation initiatives. This evolving data ecosystem has created an opportunity to drive innovation in AI and ML across many operational processes of insurance companies. As AI is further integrated in the insurance industry, the wait times for clients to have their policies approved and issued have often decreased dramatically, and the claims outcomes for the insurers have often improved significantly. These techniques have also been instrumental in detecting fraud in the underwriting and claims adjudication processes.


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