Aegon Life Insurance has performed well on major ratios pertaining to the insurance industry. The persistency ratio, which defines the amount of business retained during the year is close to 95 per cent. The policies sold using the digital medium has jumped to more than 100 per cent in 2017. The claim payout ratio has also improved. Martijn de Jong, Chief Digital Officer, Aegon Life Insurance, shares about the company’s digital initiatives, IT-enabled preventive healthcare, plans for 2018 and more
What are the initiatives taken at Aegon to use digital in cutting the middleman out?
Ease of use is at the center of what Aegon does: Make it as easy as possible to use the website; understand and purchase the product, issue policy etc. Aegon has done website personalisation in the form of Data Management Platform. It has segmented customer data and accordingly the best products are suggested to the customers.
Aegon has built an analytics platform that can hyper-personalise and target the right policy at the right time to the right customer – targeting customers of a certain age / certain phone model etc. We do a Dynamic Creative Optimisation (DCOS). For example, a customer visiting Facebook and has two siblings will be shown a banner ad having a policy information with a two-sibling scenario. Thus, the offer becomes more personal. Machine Learning (ML) is used for Google Adwords and certain keywords. They are followed in real time and culminated with either bidding higher or lower, based on what is the bounce rate it gets. The higher the bounce rate, the lower the bid.
At times, certain keywords seem to have a high probability for response, but they don’t result in expected leads. AI and ML are also used for automatic underwriting and for providing personalized consumer content. Many leads get generated, but not all of them are converted. Leads are nurtured based on the number of mails sent. Subsequently, based on how many mails are read, opened etc, a follow-up action is taken by sending SMSes and calling the customer. Aegon has a venture fund and has invested in an AI company viz. H2O.ai. It’s one of the top three companies, globally in the space of automatic underwriting and marketing optimization, which is a dedicated field in AI. By February 2018, we are targeting a surge in 50 per cent conversion rates of the leads, using H2O.ai. The company calculates and recalculates the customer propensity to buy based on the response on mails, SMSes, Facebook, Google etc. An appropriate action is taken accordingly. Significantly, Aegon has a lean analytics team of just five data analysts. In spite of such a small team, they are handling three global analytics projects for Aegon.
Usually, after checking the quote from Aegon, the customer goes on a discovery mode. After the customer comes back on the Aegon site, checking the quotes offered by others, the website immediately pops up the quote, the customer checked before he left the site.
The processes are set such that a policy can be issued in 48 hours. A number of processes are STP enabled. We are able to measure the number of customers leaving the website and then coming back to purchase the policy.
What are the digital initiatives to be taken by Aegon Life in 2018?
Forty eight hours issuance process – for straight-through processing cases it will be immediate issuance – for cases with medicals it will be maximum 48 hours after the medical. Open APIs to partners – eight APIs in total – significantly reducing time to integrate with distribution partners. We are also going to undertake multiple ML / AI projects and pilots including SEM Bid Optimization, Automatic Underwriting and Personalization lead nurturing; alongside personalized web journey including DMP, Data Lake in AWS with ML / AI Datarobot, Blockchain consortium with B3i, new website and user journeys, ARC digital – for certain offline products it will be 12 minutes issuance for straight-through processing cases, large customer driven innovation project, and a number of pilots on preventive health (IoT, wearables, ML / AI) and customized pricing.
Could you share the top five use cases, implemented by realtime digital marketing platform Plumb5?
One is relevant dynamic product banner display: Every new visit on site – Plumb5, displayed the product banner based on the product page viewed by the visitor in previous sessions. For example, if in previous visit, the visitor viewed icancer product pages, in his next visit the homepage banner depicts icancer related banners. The banners were displayed with dynamic quote values (sum insured, premium etc, as per the quote created by lead). Some of the other use cases are automated mails for leads bouncing off; capturing email click as leads for the hot-leads; automated birthday banner, with dynamic delta premium; and automated webpush notification, with dynamic quote values (as per the quote generated by lead).
Could you elaborate on the project on IT-enabled preventive health?
We are running a number of pilots on preventive health and customised pricing. Insurance has traditionally been a reactive industry. It should take a proactive stance, going forward and our preventive health and customised pricing is a step in this direction. Usually, the insurance company-policyholder relationship is where an event happens and the payment is made. Aegon wants to change this paradigm. The objective of the customer is to live long and healthy and our goal is to create an ecosystem around him to make him live a healthy lifestyle. The company is running a pilot on measuring the policy holder’s health realtime in partnership with health-tech partners, using wearables and based on the various health related performance metrics the company will reward the policy holder. For example, cheaper gym membership, vouchers, access to health coaches, doctors, do diabetes testing and other rewards are given after completing 10,000 steps or running for a certain distance daily. This is done in accordance with the customer’s approval.
We give an ecosystem to the customer to do the sports, measure the health, access to the doctors, sports, health and nutrition coaches. This offering will be attractive to a large number of new customers. India’s young population is extremely health conscious. The moot question asked in India to every transaction made, is ‘what’s in it for me?’ and in the case of insurance, it’s always not exactly visible, in spite of the policy cover, because the payout only happens after certain events.
Aegon, in partnership with a health-tech partners, is running a pilot of an app for diabetes patients. Aegon is working with an Indian company that owns a health-tech platform. It helps the customer to stay healthy.
Please brief us about the APIs for enhanced service delivery.
Aegon works with a number of partners – brokers, agents, aggregators, health-tech companies, robo advisories. It’s important to connect with them fast and transact information. We have developed eight APIs – two of them are live. API enablement helps in turbo charging the information exchange. In the case of one of the aggregators with whom the company works, earlier to the API formation, to enable a particular feature, it took four weeks for the integration and testing. However post the API enablement, we have run 35 test cases in eight hours.
The policy set up, medical appointment, lead setup, lead premium call etc have been automated. These features can significantly boost the engagement level with the customer. The idea is to take the engagement to the next level. Rather than calling the customer every month for asking the premium, it’s more apt to touch base with him to check for how would he like to connect with the healthcare ecosystem created by Aegon. Based on the various metrics set by the company, how has the customer performed on the amount of running done / steps walked, calories burnt etc. Creating a healthcare ecosystem and engaging with the customer is a better relationship than just sending reminders and asking for information. This model of preventive healthcare has worked for Aegon globally. It also helps in customised pricing. IRDA is supposed to clear customized pricing, which lets insurance companies reduce their premium on the basis of health metrics. The customer can earn a low risk premium if the metrics are improving. Some of the European countries are already offering customized pricing.
AI should be introduced much earlier in the insurance lifecycle. It will help in faster policy issuance, at times even without a need to do the medical. AI has prospect in finding proxy data and evaluate whether or not there is a need to do the medical examination of the customer before the policy is issued. In majority of the cases, medical is done, which is time consuming and results in bad customer experience. AI can help in arriving upon a risk score based on certain algorithms run over the proxy data. There are certain correlations which can be established based on the conclusions and inferences. In the US, there is a correlation set between late credit card payments and car accidents. It is said that customers who pay their credit card bills late are more likely to suffer car accidents because of the mentality of the characteristic of late payment will also reflect in driving.
The objective of the company is to issue the policy as soon as it is bought; for which, the medical has to be avoided. Hence AI has to be introduced early in the process. A good risk assessment in the beginning will result in much lesser problems at the end.