Tag Archives: ING

Forget Big Data; You Need Fast Data

In 1989, Queen released a very successful single called “I Want It All.” The opening repeats the song title twice, then changes subtly to “and I want it now!” This could be a battle cry for today’s fast-moving society.

We’ve all come to expect a rapid response to our requests for service, and we’ve become impatient with those who can’t deliver. We even watch kettles heat up and wonder why they take so long to boil, and we stand and complain about queue lengths.

Whereas consumers might take some comfort (or the opposite) in knowing that most companies they deal with hold vast amounts of data about them, all of this data is historic and, actually, very little is used productively. Yet we are increasingly engaged in real-time conversations with companies either via a mobile app, our PCs or the good old-fashioned telephone, providing real-time data about a need or a problem. So why aren’t companies, by and large, capturing and acting on that data in real-time while they are interacting with their customers? The simple explanation is that acting on data captured in real time is beyond the means of most of the systems built by these companies, and it’s not a trivial matter to change, given that this inevitably means tinkering with legacy systems.

See also: Producing Data’s Motion Pictures  

But there is a solution in sight, and it’s called “fast data.”

Fast data is the application of big data analytics to smaller data sets in near-real or real time to solve a problem or create business value while engaging with a customer or another computer. Fast data is not a new idea, but it’s going to get very important to embrace fast data.

A Fast Data Architecture

What high-level requirements must a fast data architecture satisfy? They form a triad:

  1. Reliable data ingestion.
  2. Flexible storage and query options.
  3. Sophisticated analytics tools.

The components that meet these requirements must also be reactive, meaning they scale up and down with demand, are resilient against the failures that are inevitable in large distributed systems (we don’t want any failures on autonomous cars!), always respond to service requests even if failures limit the ability to deliver services and are driven by messages or events from the world around them.

The chart below shows an emerging architecture that can meet these requirements.

The good news is that you can graft such an architecture on top of legacy systems, which is exactly what ING has been doing.

Unlocking valuable intelligence

Back in the halcyon days, banks were very close to their customers. They knew customers intimately and treated them personally. With the proliferation of customers, products and channels, though, this intimacy has been lost. ING wanted to recapture the “golden era” with a global strategy to make the bank more customer focused, “mobile first” and altogether more helpful.

A typical bank these days captures and processes billions of customer requests, instructions and transactions. In doing so, they capture and store vast amounts of customer data – but, and here’s the startling truth, few (if any) of the major banks use this data effectively for the benefit of their customers.

ING appointed a manager of fast data, Bas Geerdink, to address this problem. His broad international remit is to create a truly customer-friendly, omni-channel experience. To kick start this process, he turned his attention to ING’s vast but disparate data stores, as he was convinced they could unlock valuable intelligence. Historical data can often reveal customer behaviors and trends that are crucial to predictive analytics. For example, past data can be used to plot future pressure points on personal finances – e.g., key payment events can be anticipated and mitigated with predictive analytics.

However, mining this data presents major challenges. Most banks are hampered by disparate and disconnected legacy applications that cannot operate in real time. Confronted with this dysfunctional problem, ING made some fundamental decisions:

  1. Create a single, secure data lake.
  2. Employ a variety of open source technologies (along the lines of those shown in the chart above). These technologies were used to build the over-arching notifications platform to enable data to be captured and acted on in real time.
  3. Work with the legacy application teams to ensure that critical events (during a customer’s “moment of truth”) are notified to this fast data platform.
  4. Trigger two vital platform responses: a. Instantly contact the customer to establish whether help is urgently needed (for example, to complete a rapid loan application); b. Run predictive analytics to decide whether the customer needs to be alerted.

The future role of banks

Partly in response to the Open Banking directive, the bank is now opening up its data to third parties who have been authorized by customers to process certain transactions on their behalf (e.g. paying bills). This is a fascinating development with potentially far-reaching implications. It raises a question about the future role of banks. For example, would the rise of nimble, tech-driven third parties reduce banks to mere processing utilities?

ING is determined not to be marginalized, which is why it has invested in this fast data platform and its building real-time predictive apps – both on its own and with third parties  (such as Yolt). It is a bold and very radical strategy – and, not surprisingly, it raises some searching questions.

Hearing this story made me wonder what types of customer would most welcome this kind of service, and was there any risk of alienating less technology-literate customers?

The bank doesn’t yet have definitive answers to these questions. However, ING is adamant that all technology-driven initiatives must have universal appeal, and that is why ING is introducing change on a very gradual, phased basis.

See also: When Big Data Can Define Pricing (Part 2)  

In the first instance, ING is testing these services on employees of the bank and then on beta test groups of (external) customers. To date, feedback has been extremely positive, and this has encouraged the bank to keep investing. However, Bas emphasizes the need to appreciate customer sensitivities and preferences. For example, there is a fine line between providing a valued service and becoming intrusive – that is why the bank specifically considers factors such as the best, most receptive time of day to make interventions (if at all).

Fraud detection is another intriguing development where fast data is having a significant impact. At the moment, traditional fraud detection systems often lack finesse. When a customer attempts to use a credit card, it can trigger a false positive 90% of the time (or even more). This can be inconvenient both for the bank and especially for the customer (although a false positive is not always perceived in a negative way – it shows the bank is checking money flows). ING is hopeful that its fast data platform will radically reduce the level of false positives as well as the level of fraud.

Other applications of fast data

I’m aware that Capital One has deployed a fast data service and is now able to authorize a car loan in seconds – instant on-the- line confirmation that massively improves the customer experience.

Yet I’ve also heard of instances where data is anything but fast!

Take the Lloyds Insurance market. Currently, some full risk assessments for specialist insurance are completed two weeks after prices have been quoted – quite clearly, this is a risk too far!

We can also see applications in places like the police and military, who often have to capture and act upon a variety of data sources, in real time, in often hazardous and difficult circumstances. Fast data analytics could be used, for example, to predict when supplies of ammunition will run out and to trigger immediate air drops to front-line troops.

The opportunities to change lives with fast data are enormous. Luckily, it’s becoming easier and easier to achieve. The time to start is now.

trends

13 Emerging Trends for Insurance in 2016

Where does the time go?  It seems as if we were just ringing in 2015, and now we’re well into 2016. As time goes by, life changes, and the insurance industry—sometimes at a glacial pace—does, indeed, change, as well. Here’s my outlook for 2016 on various insurance topics:

  1. Increased insurance literacy: Through initiatives like The Insurance Consumer Bill of Rights and increased resources, consumers and agents are both able to know their rights when it comes to insurance and can better manage their insurance portfolios.
  2. Interest rates: The federal funds target rate increase that was announced recently will have a yet-to-be determined impact on long-term interest rates. According to Fitch Ratings, further rate increases’ impact on credit fundamentals and the longer end of the yield curve has yet to be determined. Insurance companies are hoping for higher long-term rates as investment strategies are liability-driven. (Read more on the FitchRatings website here). Here is what this means: There will not necessarily be a positive impact for insurance policy-holders (at least in the near future). Insurance companies have, for a long period, been subsidizing guarantees on certain products or trying to minimize the impact of low interest rates on policy performance. In the interim, many insurance companies have changed their asset allocation strategies by mostly diversifying their portfolios beyond their traditional holdings—cash and investment-grade corporate bonds—by investing in illiquid assets to increase returns. The long-term impact on product pricing and features is unknown, and will depend on further increases in both short- and long-term interest rates and whether they continue to rise in predictable fashion or take an unexpected turn for which insurers are ill-prepared.
  3. Increased cost of insurance (COI) on universal life insurance policies: Several companies—including Voya Financial (formerly ING), AXA and Transamerica—are raising mortality costs on in-force universal life insurance policies. Some of the increases are substantial, but, so far, there has been an impact on a relatively small number of policyholders. That may change if we stay in a relatively low-interest-rate environment and more life insurance companies follow suit. Here is what this means: As companies have been subsidizing guaranteed interest rates (and dividend scales) that are higher than what the companies are currently (and have been) earning over the last few years, it is likely that this trend will continue.
  4. Increasing number of unexpected life insurance policy lapses and premium increases: For the most part, life insurance companies do not readily provide the impact of the two prior factors I listed when it regards cash value life insurance policies (whole life, universal life, indexed life, variable life, etc). In fact, this information is often hidden. And this information will soon be harder to get; Transamerica is moving to only provide in-force illustrations based on guarantees, rather than current projections. Here is what this means: It will become more challenging to see how a policy is performing in a current or projected environment. At some point, regulators or legislators will need to step in, but it may be too late. Monitor your policy, and download a free life insurance annual review guide from the Insurance Literacy Institute (here).
  5. Increased complexity: Insurance policies will continue to become more complex and will continue their movement away from being risk protection/leverage products to being complex financial products with a multitude of variables. This complexity is arising with products that combine long-term care insurance and life insurance (or annuities), with multiple riders on all lines of insurance coverage and with harder-to-define risks — even adding an indexed rider to a whole life policy (Guardian Life). Here is what this means: The more variables that are added to the mix, the greater the chance that there will be unexpected results and that these policies will be even more challenging to analyze.
  6. Pricing incentives: Life insurance and health insurance companies are offering discounts for employees who participate in wellness programs and for individuals who commit to tracking their activity through technology such as Fitbit. In auto insurance, there can be an increase in discounts for safe driving, low mileage, etc. Here is what this means: Insurance companies will continue to implement different technologies to provide more flexible pricing; the challenge will be in comparing policies. The best thing an insurance consumer can do is to increase her insurance literacy. Visit the resources section on our site to learn more.
  7. Health insurance and PPACA/Obamacare: The enrollment of individuals who were uninsured before the passage of Obamacare has been substantial and has resulted in significant changes, especially because everyone has the opportunity to get insurance—whether or not they have current health issues. And who, at some point, has not experienced a health issue? Here is what this means: Overall, PPACA is working, though it is clearly experiencing implementation issues, including the well-publicized technology snafus with enrollment through the federal exchange and the striking number of state insurance exchanges. And there will be continued challenges or efforts to overturn it in the House and the Senate. (The 62nd attempt to overturn PPACA was just rejected by President Obama.) The next election cycle may very well determine the permanency of PPACA. The efforts to overturn it are shameful and are a waste of time and money.
  8. Long-term care insurance: Rates for in-force policies have increased and will almost certainly face future increases—older policies are still priced lower than what a current policy would cost. This is because of many factors, including the prolonged low-interest-rate environment, lower-than-expected lapse ratios, higher-than-expected claims ratios and incredibly poor initial product designs (such as unlimited benefits on a product where there was minimal if any claims history). These are the “visible” rate increases. If you have a long-term care insurance policy with a mutual insurance company where the premium is subsidized by dividends, you may not have noticed or been informed of reduced dividends (a hidden rate increase). Here is what this means: Insurance companies, like any other business, need to be profitable to stay in business and to pay claims. In most states, increases in long-term care insurance premiums have to be approved by that state’s insurance commissioner. When faced with a rate increase, policyholders will need to consider if their benefit mix makes sense and fits within their budget. And, when faced with such a rate increase, there is the option to reduce the benefit period, reduce the benefit and oftentimes change the inflation rider or increase the waiting period. More companies are offering hybrid insurance policies, which I strongly recommend staying away from. If carriers cannot price the stand-alone product correctly, what leads us to believe they can price a combined product better?
  9. Sharing economy and services: These two are going to continue to pose challenges in the homeowners insurance and auto insurance marketplaces for the insurance companies and for policy owners. There is a question of when is there actually coverage in place and which policy it is under. There are some model regulations coming out from a few state insurance companies, however, they’re just getting started. Here is what this means: If you are using Uber, Lyft, Airbnb or a similar service on either side of the transaction, be sure to check your insurance policy to see when you are covered and what you are covered for. There are significant gaps in most current policies. Insurance companies have not caught up to the sharing economy, and it will take them some time to do so.
  10. Loyalty tax: Regulators are looking at banning auto and homeowners insurance companies from raising premiums for clients who maintain coverage with them for long periods. Here is what this means: Depending on your current auto and homeowners policies, you may see a reduction in premiums. It is recommended that, in any circumstance, you should review your coverage to ensure that it is competitive and meets your needs.
  11. Insurance fraud: This will continue, which increases premiums for the rest of us. The Coalition Against Insurance Fraud released its 2015 Hall of Shame (here). Insurance departments, multiple agencies and non-profits are investigating and taking action against those who commit elder financial abuse. Here is what this means: The more knowledgeable that consumers, professional agents and advisers become, the more we can protect our families and ourselves.
  12. Uncertain economic and regulatory conditions: Insurance companies are operating in an environment fraught with potential changes, such as in interest rates (discussed above); proposed tax code revisions; international regulators who are moving ahead with further development of Solvency II; and IFRS, NAIC and state insurance departments that are adjusting risk-based capital charges and will react to the first year of ORSA implementation. And then there is the Department of Labor’s evaluation of fiduciary responsibility rules that are expected to take effect this year. Here is what this means: There will be a myriad of potential outcomes, so be sure to continue to monitor your insurance policy portfolio and stay in touch with the Insurance Literacy Institute. Part of the DOL ruling would result in changes to the definition of “conflict of interest” and possibly compensation disclosure.
  13. Death master settlements: Multiple life insurance companies have reached settlements on this issue. Created by the Social Security Administration, the Death Master File database provides insurers with the names of deceased people with Social Security numbers. It is a useful tool for insurers to identify policyholders whose beneficiaries have not filed claims—most frequently because they were unaware the deceased had a policy naming them as a beneficiary. Until recently, most insurers only used the database to identify deceased annuity holders so they could stop making annuity payments, not to identify deceased policyholders so they can pay life insurance benefits. Life insurers that represent more than 73% of the market have agreed to reform their practices and search for deceased policyholders so they can pay benefits to their beneficiaries. A national investigation by state insurance commissioners led to life insurers returning more than $1 billion to beneficiaries nationwide. The National Association of Insurance Commissioners is currently drafting a model law  that would require all life insurers to use the Death Master File database to facilitate payment of benefits to their beneficiaries. To learn more, visit our resources section here. Here is what this means: Insurance companies will not be able to have their cake and eat it too.

What Can You Do?

The Insurance Consumer Bill of Rights directly addresses the issues discussed in this article.

Increase your insurance literacy by supporting the Insurance Literacy Institute and signing the Insurance Consumer Bill of Rights Petition. An updated and expanded version will be released shortly  that is designed to assist insurance policyholders, agents and third party advisers.

Sign the Insurance Consumer Bill of Rights Petition 

What’s on your mind for 2016? Let me know. And, if you have a tip to add to the coming Top 100 Insurance Tips, please share it with me.