Behavioral Analytics | The Digital Transformation’s Impact on Banking and Insurance
Behavioral Analytics and the Digital Transformation’s Impact on Banking and Insurance
In the past 15 years, with the rise of the Internet and the ongoing digital transformation, we’ve seen business transform like never before.
Traditional retail took a huge hit as consumers shift their behavior to custom online experiences.
Direct-to-consumer business models displaced wholesalers.
And customer expectations around transparency and ease-of-use change dramatically.
Why go to a Mall when you can order on Amazon?
Why go to a Mattress King when you can order directly through Casper?
Why go to a car dealership if you can order a Tesla or connect with someone locally through TrueCar?
E-commerce is the easiest and most commonly thought of and mentioned ‘disrupter’, but the Internet has not stopped there.
The customer-driven shift from face-to-face business models to ‘faceless’ business models has forced companies to adapt to new customer preferences.
Like everyone else, Banking and Insurance organizations have been forced to play catch-up and adapt to the changing landscape.
With new internet-based entrants in the space, industries like these are faced with three critical challenges when it comes to transforming their businesses into digital powerhouses:
- The Digital Shift has led to the “Faceless” applicant
- Traditional brick-and-mortar customer experiences have gone online
- Risky behavior is easier to accomplish and harder to catch
Let’s take these one-by-one…
The “Faceless” Applicant
If you think about the process for applying for, say, a Life Insurance policy in 2005, an applicant would sit down with an insurance agent to begin their application.
The agent/employee’s job was to create a positive experience for the customer, sell an appropriate policy (or policies), and mitigate risk along the way.
Given over 90% of communication is body language and tone, risk mitigation was largely done by agents using human intuition.
And now that 55% of applicants are looking for solutions online, especially with the current COVID landscape, the ability to read and react to a customer’s body language has been lost. Meaning, that the “Behavioral Analytics” that was done mostly intuitively by humans no longer exists.
And as businesses attempt to make accurate and cost-effective underwriting solutions, they are doing so with very limited data— the ‘final answer data’ provided by the submission of the application alone and third-party datasets once the user presses submit.
This leaves institutions extremely vulnerable to risky and fraudulent behavior and they often realize they’ve been duped months or years later.
Besides hackers and scammers and opportunistic applicants, internal agents are often guilty of ‘gaming’ the system to ensure applications are approved so they receive higher commissions.
Everyone remembers the well-publicized Wells Fargo example, but companies all across the globe are having the same problem of agents manipulating information in an act of self-servitude.
This is very bad for the customer and the company and could have a lasting impact from a brand and monetary perspective.
Brick-and-Mortar Experiences Have Shifted Online
The days of a smiley welcome, warm cookies, and an offer of ‘coffee or water’ are gone.
Today, customers and agents interact almost exclusively over the phone or online.
With that, digital experiences are becoming more and more tailored to the individual user when they are interacting with a website, mobile app, or application.
Seeing products and services unrelated to what you’re looking for, questions that aren’t specific to you, and requiring users to jump through multiple hoops creates an immediate turn-off and will likely deter customers from choosing your company.
In the age of price shopping and information hunting, having a seamless user experience can make the difference between a happy new customer or an annoyed public detractor.
And the best way to accomplish this is by having a robust behavioral analytics tool that tells you exactly what to do.
Much like Amazon’s “Customers like you also bought…” recommendation engine, behavioral analytics allows you to understand user behavior and intent on a granular level so you can have dynamic experiences on an individual customer level.
Businesses today are getting smarter and tailoring experiences for each individual user, interacting in real-time with a customer through the rise of chatbots, and providing helpful information and resources within the experience so that the user doesn’t need to go searching for the information and never come back.
Risky Behavior is Easier to Accomplish and Harder to Catch
The battle between Marketing/CX teams and Risk/Fraud teams is nothing new.
The desire to increase conversions by removing all friction is real, and marketing teams would likely have their way if their risk/fraud counterparts weren’t inclined to do the exact opposite.
If Risk/Fraud departments had their way, there would be endless screens, background checks, fingerprint scans, airport security-like x-ray machines, and Minority Report-like facial analysis that stand in the way of a fraudster and their desired goal.
Even with the invention of technologies like e-signatures, which are relatively secure, businesses still struggle with identity verification and risk mitigation.
The key to ensuring a safe and effective screening process while maintaining a seamless user experience is balance and dynamic interaction. Watch this vlog to learn how to do this.
How to survive, and ultimately thrive, during the digital transformation with behavioral analytics
The most human element of all, reading and reacting to someone’s body language, has been technology’s Holy Grail since the inception of AI back in the 1950s.
It’s impossible to read, understand, and react to someone’s body language using a computer, right?
Not so fast…
The advances in AI have been rising at an unprecedented level, especially in the last decade.
And predictive behavioral analytics and biometrics may be the map to the elusive Holy Grail once and for all…
Even a few years ago the answer to “How can I operate in a digital world the same way I did in a physical one? would have been…“You can’t.”
Which is why we built ForMotiv.
By combining AI, machine learning, predictive behavioral analytics, and behavioral psychology we created what is now known as “Behavioral Intelligence.”
Our technology is able to analyze a user’s “Digital Body Language” while they interact with a form or application and we use machine learning to predict what their intent is, filling in the dimension of behavioral data that was lost during the shift online.
How a user types, their keystrokes, mouse movements, corrections, copy/pastes, and about 150 other behavioral features all combine to form a digital profile of the applicant. Leading financial service companies are integrating this data set into their accelerated underwriting and claims processes to improve user experiences and predict risk and fraud.
Businesses using predictive behavioral analytics are better positioned to not only survive but thrive in the new digital age.
Example Benefits of Behavioral Intelligence
1. Behavioral Data Collection – we arm your team with hundreds of behavioral “features,” thousands of behavioral data points (multiplied by the number of applications you receive on a monthly basis), and can supply raw or calculated data however you would like to consume it (API, console, monthly reporting, etc.). This digital body language behavioral data has proven to be highly predictive and is being used both in accelerated underwriting as well as pricing and claims.
2. Risk/Fraud – identify high-risk behavior and receive real-time alerts to appropriately mitigate risk. Predict outcomes in real-time to determine deviant behavior and real-time risk/fraud outcome scoring. This data set is proving very predictive at determining risk and fraud both in underwriting and claims.
3. UI/UX – understand application friction and user behavior at a granular level, optimize workflows and forms/applications, and dynamically engage with users. ForMotiv will put a finger on the pulse of your application’s “Health Score”, providing insights such as “chokepoints” and “high drop-off questions”. Not only that, ForMotiv provides recommendations into “Optimal Application Flows” by analyzing the optimal flow from good users and measuring any UX changes in real-time.
4. Agent Oversight – understand agent workflows, high/low performers, benchmark agents or agencies, and spot risky/deviant behavior such as agents “gaming” the system. Want to monitor your internal or external agents? By understanding baseline ‘good’ and ‘bad” behavior companies are able to receive alerts in real-time when a customer or agent is showing signs of deviant behavior.
Some of our more advanced customers have started using our dataset to enable dynamic experiences.
For instance, we can predict with roughly 96% accuracy if a user is likely to abandon the application based on how they are filling it out.
If that user hits an ‘abandonment threshold’, ForMotiv will dynamically engage the user with tooltips and FAQ’s, a “click to call a representative” button or prompt your chatbot to interact with the user to encourage them to convert.
Similarly, when a user hits a “fraud threshold” companies can dynamically add friction questions such as uploading a Drivers’s License or have the applicant diverted to a call center to speak with an agent live. This has proven to be extremely helpful in the life insurance space as they aim to reduce the amount of paramedics interviews and fluid tests given.
Using behavioral analytics, ForMotiv has predicted thousands of potentially fraudulent accounts, leading to millions of dollars of savings for insurance and banking institutions.
That obviously saves the bottom line tremendously, while our form optimization helps increase conversions, resulting in top-line gains, as well.
And don’t just take our word for it, with Lemonade’s recent IPO success, more attention has been brought to behavioral intelligence, which they credit as the key reason they’ve seen their loss ratio drop from 162% to 68% in only two years.
You can read more about Lemonade’s disruptive business model and behavioral analytic strategy here.
Want to learn more about ForMotiv and how we can help you transform your business into a digital powerhouse with behavioral analytics? Email us at email@example.com