How does one account for the phenomenal success of companies who consistently outsmart their competition with data? We are talking about the likes of Google and Amazon, and even those back home in India - like Zomato and PayTM.

In fact, why is this simple 4-letter word ‘data’ so important at all?

The answer lies in another 4-letter word - ‘bias’.

‘Cognitive bias’ essentially refers to perceiving a distorted reality due to personal preferences, beliefs or other subjective influences. In business, this means that if your decisions are considerably biased, they lose objectivity and deviate from reality. Depending on how critical the decision is, it can be incorrect at best and disastrous at worst. You will be indeed amazed to know the extent to which cognitive bias can impact business decision-making and strategy formulation.

In this exclusive feature article, we at FORMCEPT, would like to share with you two common biases that most business decision-makers exhibit, along with relevant industry examples.

Last, but not the least, we are here to throw a lifeboat at you - to defeat biases with actionable analytics.

Let’s get started.

Confirmation Bias - Example from Insurance Industry

In October, 2008 a TDWI case study shed light on the plight of a large insurance company. To quote an excerpt from the case,

“The company possessed volumes of information about its customers but had no process in place, nor did it have a comprehensive way to cull the information necessary to enable segmentation of its customer base. Without the capability to look at the individual customer, LIII (the insurance company) would continue to spend money, perhaps unnecessarily, by targeting the wrong people at the wrong time. This lack of insight had several negative implications, including customer dissatisfaction, increased risk, and faster attrition.”

A decade has passed since this case was published, and lack of customer insights is still an excruciating pain-point for this industry that virtually sits on an ocean of data. Lapsation models, even if in place, are grossly inadequate, and thus, premature lapsation is near impossible to predict and prevent at scale.

The result? Without data as the guiding compass, cognitive bias creeps in - affecting decisions ranging from product design, channel strategy, portfolio structuring, marketing, and premium management. For example, a life insurance manager may have come to believe that policy lapsations are closely tied to the economic status of the customer, whereas in reality, lack of customer engagement and consumer education about insurance might be the two most pervasive factors leading to premature lapsation. Even if he has all the data in front of him, his beliefs will influence which data he chooses to act upon, since objective interpretation is not possible in the absence of in-depth insights gleaned from analytics. This kind of bias, wherein people tend to absorb information more often that confirms or boosts the beliefs that they already have is known as Confirmation Bias. We have used the insurance industry merely as an example here - decision makers across a wide range of industries are prone to suffer from this bias.

Actor-Observer Bias - Example from Banking Industry

What is the number 1 problem that bankers face today?

Well, the jury is still out on that, but bankers continue to be at the mercy of an acutely agonizing problem - the challenge of Non Performing Loans (NPLs).

Simply put, loans generate income for banks in the form of interest. When the loanee, or the person who has availed the loan is unable to pay it back, the loanee is said to ‘default’ and his loan account becomes defunct or non-performing - hence the term ‘Non Performing Loans.’

Now, take an example of a banker, who has issued 1000 loan products, of which 625 are NPLs. The Actor-Observer bias suggests that it is more likely that the banker will focus on the reasons that are external to him - for example, lack of sincerity among loanees, economic downturn, and so on. He is less likely to consider the factors that are internal to him or to the bank- for example, his inability to identify a potential NPL beforehand, lack of objective insights made available to him in a timely manner, flaws in repayment strategy, and so on.

The repercussions of this bias can be huge and catastrophic. Banks will continue to spiral down in the whirlpool of NPLs until an objective analysis of the situation is carried out, and inferences are made available at the right time.

Indeed, not just in banking, this bias plagues professionals globally, and we couldn't really blame them - it takes data, analysis, and insights to break the barriers of cognitive bias. Right intelligence at the right time is a luxury today, and we at FORMCEPT are committed to revolutionize the industry landscape by solving this puzzle.

But how?

Introducing Constellate

Constellate is an augmented analytics platform built on top of our flagship unified analysis product MECBOT. Constellate essentially deploys high quality, machine augmented first party data on top of industry-specific ontology and knowledge to enable smart data discovery and auto-visualization of patterns.

With Constellate we have stepped up diagnostic and predictive analytics to the next level where built-in customer loyalty indices such as Net Promoter Score (NPS), segmentation analysis, lapsation model for banking, fraud prevention in insurance claims, NPL detection and prevention in banking, and similarly many other crucial indicators specific to different industries that are made available through a few clicks. The best part? All your queries are searchable in simple english language.

Constellate for Insurance

With Constellate for Insurance, insurers are empowered with better lifecycle management, reduced premature lapsation, detection and prevention of fraud, targeted cross-sell and up-sell, attain higher personalization and engagement, and decision makers receive early signals to manage claims better.

Constellate for Banking

Constellate for Banking helps to design and issue the right loan to the right customer, increase repayment of loans, promote cross-sell and up-sell across segments, capture increased share of the customer’s wallet, and predict and prevent churn.

Concluding Note

Are there cognitive biases that you have experienced or witnessed in decision-making at work? We would love to hear your ideas and anecdotes.

If you are looking to beat biases in business with advanced analytics and cutting edge technology, you could begin by exploring our state-of-the-art products MECBOT and Constellate. Our mission is to enable businesses become market-intelligent with smart data analytics and to make insights available on a near real-time basis.

To know more about what we do and how we can help you, please visit www.formcept.com or write to us at contactus@formcept.com.