With requirements for increased data capacity and systems to match within the framework of the incoming IFRS 17, insurance companies will have at their disposal a treasure trove of information that remains very relevant in the running and growth of the business.
NAIROBI, Kenya, Dec 7 – The insurance industry in Kenya is in a transition phase and will remain so for the next few years as Insurance Companies grapple with the understanding and implementation of IFRS 17 – Insurance Contracts.
The standard was released May 2017 and takes effect 1 January 2021, bringing with it significant changes in the industry.
Insurance companies will now have to re-look at their valuation models, capability of current systems and assess the changes to be made to ensure compliance with the new standard. Salient among these changes is that Insurance Companies will require more data at a granular level to meet the new reporting requirements.
This represents a big opportunity for the Industry to grow its data analytics capability. Data analytics refers to the analysis of data with the aim of discovering existing trends in business data and drawing conclusions that inform future decision making. The risk – price relationship in insurance places data analytics at the very core of the insurance set up.
With requirements for increased data capacity and systems to match within the framework of the incoming IFRS 17, insurance companies will have at their disposal a treasure trove of information that remains very relevant in the running and growth of the business.
Through data analytics, insurance companies can assess products based on factual historical data and can even narrow down to a geographical location. This is an opportunity to move away from the one-size fits all approach and instead tailor make insurance contracts to the insured’s needs. Different locations and demographics in the Kenyan market face varying perils and have unique insurance needs. The analysis of data allows for a strategic and informed re-think of product packaging to more relevant, affordable and need centric insurance covers.
Could it be that the low insurance penetration in the Kenyan market is driven by amongst other things, the generic nature of available products? The marketing function could well make use of such data and roll out ‘targeted marketing’ to reach the populace with a personalized message and relevant products.
Insurance companies that will strategically invest in the data analytics space will differentiate themselves from their competitors. With increased comparability and results transparency being at the fore of IFRS 17, the competition for market share in the insurance sector will increase.
Through the analysis of existing data, insurance companies are already looking to re-evaluate and disintegrate risks attached to various products. This will ultimately lead to a superior pricing mechanism that is bound to give them competitive edge. The separation of underwriting results from investment income in the new framework will distinctly bring to the fore the true source of earnings for insurance companies. Stiff competition in the past has resulted to some players in the industry resulting to price undercutting – offering lower prices to lock down business instead of pricing based on the risk insured.
Insurance companies that will assess risk supported by insights from data analytics will therefore be ahead of the curve in complying with future potential guidelines from the regulator to clamp on price undercutting based on the shift in reporting requirements.
Fraud in the insurance sector remains a reality. The numerous players in a typical insurance contract does little to alleviate the risk of collusion. Through data analytics, Insurance companies can establish trends based on historical transactions and in particular loss making contracts to assess for indicators of fraud. Trends and analytics will allow for comparability among intermediaries enabling insurance companies to interrogate the quality and cost of business from specific intermediaries.
Fraud remains a perennial challenge due to the lack of data sharing across insurance companies. Be it the non-existence of data, lack of uniform data or the high set up and maintenance cost of a centralised set up to house and stream data to and from the various insurers, none of these challenges measures up to the ever increasing cost of fraud year on year.
Consider an insurance market where the details of a new potential motor insurance customer can be queried in a centralized database to reveal a detailed claim history from past insurers, or a database that shows the cost of various drugs as captured by different insurers from their medical providers to be used as a basis for the market price? The benefit of such data would far outweigh the set up cost.
Every large business struggles to preserve business value and arrest any revenue leakage. Those charged with governance, in preserving shareholder value, must ask of their management, “For every business written in premiums, how much of it translates into claims and how much of that goes to claimant?”
Data analysis will enable insurance companies to review the value of written business against associated costs and implement relevant controls around key risk areas of revenue leakage.
The ability of an insurance company to anticipate claims has far reaching implications in ensuring proper pricing, accurate reporting on loss making contracts and increased efficiency in claims processing. By leveraging on data and analytics, insurers can assess the nature, probability and likely quantum of claims arising from written business. This represents a potential quick win in curbing loss making contracts and better insights into the profitability of insurance companies.
The potential gains of data and analytics in the insurance sector will require commitment and investment by players in the industry. Insurance companies face a significant challenge in the collection of relevant data in a usable format.
Use of data and analytics will introduce the need for more advanced business intelligence tools. Insurers will have to invest in the training of resources capable of correctly analysing, interpreting and applying the data.
This shifting landscape of data in insurance heralds the dawn of a new age of opportunity, innovation and differentiation whose impact will undoubtedly translate into gains for the insurer and insured.
Frank Mumo – Regional Financial Analyst, Jubilee Insurance
