FRICTION INDEX REPORT...ﬁnancial institutions and how they can increase conversion rates, reduce abandonment and recognize potential fraud attempts. The report uncovers key ﬁndings

FINTECHFRICTION INDEX REPORT

Scientifically measuring the current levels of friction along the digital customer’s journey

2019

© 2019 Neuro-ID. All Rights Reserved.

PRESENTED BY

™

FINTECHFRICTION INDEX REPORT™

Executive Summary

Friction and the Digital Gap

About the Friction Index™

Friction by device type

Key speedbumps in digital onboarding

The product offering and UX

Friction indicative of fraud

Verification friction

What’s next?

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TABLE OF CONTENTS


Digital onboarding is out-of-step with technological advancements

Almost 20 years into the digital transformation, we’ve seen remarkable advances in scalability, technology and integrated services, yet friction within the digital customer experience continues to drive even the best of customers away, frustrated and unserved.

We must go beyond the symptoms of friction and understand the underlying causes

While retroactive analytics have scrutinized the rudimentary click paths of the digital customer and heatmaps of an interaction, Neuro-ID’s real-time ability to measure friction across multiple dimensions digs deeper into the actual mindset and intentions of the person on the other side of the screen.

Wholesale high friction should be replaced with a customer-level, risk-appropriate approach

A blindness persists between FI’s and their digital customers, forcing an unfortunate level of friction and high drop-offs. Neuro-ID’s next gen source of customer data provides a much-needed window into the intent and state of mind behind online interactions, to see the individual customer more clearly, and pave a more personal, appropriate path, controlling the dial on friction.

© 2019 Neuro-ID. All Rights Reserved. neuro-id.com

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Executive Summary WHY IS THIS REPORT IMPORTANT TODAY?

FinTech Friction Index™ Report | 2019

Is all friction bad? While the market has taken on a ‘reduce friction’ battle cry, it’s important to realize that not all friction is inherently bad. Friction can provide important meaning to an interaction between a customer and application

A user’s device plays into the amount of friction introduced We look at friction based on the characteristics of the device and the background context in which it is used

Usability matters We explore how language, device considerations and ease-of-use of forms and specific elements can lead to confusion and, at worst, abandonment

Friction is contextual This is especially seen at key points of commitment in the application process – questions and inputs related to personally identifiable information (PII), account creation and financial or banking information top the list as leading points of sensitivity

Verification friction continues to kill conversion Inflicted by increased friction along the customer journey, droves fall out of a perfectly healthy funnel during verification

Fintechs are increasingly disrupting traditional financial institutions in areas such as banking and lending in order to give consumers greater access and more control over their financial health. But these advancements have created unintended consequences for both consumers and lenders. Even with today’s tech-savvy consumer and the proliferation of online business, the loss of personal, human interaction has led to low conversion rates.

Many experts tout ‘friction’ as the primary culprit. Until now, friction has remained an elusive dimension, evaluated by gathering historical data over time, or through a series of educated guesses.

Neuro-ID’s inaugural FinTech Friction Index™ Report uses proprietary behavioral analytics and neuroscience, created and deployed over the last decade, to give unprecedented insight into where, how and why friction occurs. Based on tens of millions of applicants, analyzing over one-trillion neuro-metrics, the report answers many questions concerning the customer’s digital interaction with financial institutions and how they can increase conversion rates, reduce abandonment and recognize potential fraud attempts. The report uncovers key findings such as:

Our goal with the Friction Index™ is to scientifically baseline the level of friction a consumer experiences during each step of the customer journey…to inform changes and improvements to optimize CX and conversion.

– Jack Alton, CEO, Neuro-ID

Nearly a decade of ground-breaking research and discovery in human-computer interaction (HCI) around anomoly and intent detection

Over 1 Trillion ‘Neuro-Metrics’ collected from 10s of millions of applicant starts

Patented technologyto remove noise in digital interactions to reveal meaningful and nuanced behavior

Provider of in-session actionable Neuro Confidence Scoresto inform real-time decisioning around CX and verification friction

More than 26,000cumulative times, our founders’ research has been referenced by other scientists (Google Scholar)


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FinTech’s rapid transition to digital creates significant friction for customers

NEURO-ID: PIONEERS IN QUANTIFYING FRICTION


PROBLEM: THE ‘DIGITAL GAP’As businesses and financial institutions (FIs) continue to move processes online to meet customer demand, a digital gap between brands and their customers has emerged. Consequently, the inability to clearly see and understand the digital customer has led to:

UNDERSTANDING LEADS TO ACTIONThe goal of the FinTech Friction Index™ Report is to shine a light on the state of friction in the industry from the digital consumer’s perspective. Revealed through a new and compelling lens, Neuro-ID’s proprietary, scientific and data-driven analysis exposes true causes of friction, abandonment and customer intent.

Conducted by capturing and studying over a trillion ‘neuro-metrics’ across many of the top fintechs in the world, the report offers a wealth of knowledge and awareness to drive positive change in the digital customer journey – especially the forms themselves that serve as the critical interface in a ‘new account’ scenario.

The aim is to facilitate two primary areas:

Friction-filled processes that result in poor CX and low conversion

Ever-increasing instances of sophisticated fraud and risk

See and reduce friction in online forms, where it contributes to frustration and unwanted abandonment

Help foster a better understanding of friction – the types and the context from which it is experienced

MEASURING FRICTION FOR THE DIGITAL CONSUMER

NOT ALL FRICTION IS THE SAME

Often misunderstood, ‘friction,’ as a concept, permeates just about any conversation around today’s digital customer journey. Addressed only as a vague culprit to issues such as low conversion, high abandonment, etc., Neuro-ID employs proprietary algorithms to quantify the friction users experience with online forms, calculating a multidimensional Friction Index™. This individual, session-level data provides clear insight into the customers’ journey through a new lens, presenting rich, faceted behavioral data used to calculate the score in real time. Segmented by cursor and mobile/touch users, the report illustrates compelling trends and a powerful narrative not seen using traditional analytics.

B E H A V I O R A L C O M P O N E N T S

B E H A V I O R A L C O N T E X T

Total Interaction Time

Idle Time

Number of Answer Changes

Typing Hesitation

Auto-fill Frequency

Copy/Paste Percentage

Frequency of Exits

…and much more

The unending search for the perfect website occurs because A/B tests are driven by hunches and guesses. Rather than guesstimating what is good or bad, the Friction Index helps direct action with clear insight about your customer’s journey.

– Joe Valacich, PhD CSO, Neuro-ID

The Friction Index allows you to objectively evaluate the strengths and weaknesses of your site relative to industry best practices; game changing.

– Jeff Jenkins, PhD CTO, Neuro-ID


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Identity (PII)Related

Income & Employment

Product or Offer

About the Friction Index™

ABOUT THE STUDYThe FinTech Friction Index™ Report is comprised of studying tens of millions of digital consumer and/or applicant online sessions from many of the world’s top fintech institutions during the 2nd quarter of 2019. Per protocol of Neuro-ID’s proprietary technology, no personally identifiable information (PII) was collected.

Through a contextual lens, the nuanced metrics begin to paint a picture of how users experience friction within an application or form. In some cases, signals of confusion and frustration lead to high abandonment and low conversion. In others, we see behavioral patterns indicative of fraud, gaming the system with questionable self-reported data and disengaged ‘shopping.’ In short, not all forms of friction are the same and each points to its own unique cause or ‘intent’ of the user.

Friction Index™

A score that indicates how efficiently end-users interact with and provide answers to specific questions.


The environment of the digital customer and the devices with which they interact can be split into two high level groups: touch and cursor. Touch devices include smart phones, tablets or any device utilizing a touch screen, while cursor devices include laptops and desktop computers using a cursor through either a mouse or touchpad.

Fundamental differences contribute to friction experienced in each group:

Inherent characteristics of each device, their modalities and ease-of-use:

• Text size

• Keyboard or input mechanisms

• Screen size and visible area of forms, and ability to explore additional tabs

• Level of engagement and commitment (e.g., waiting in line, browsing on smart phone vs at home)

• Availability of information

The nature of how the device relates to the digital consumer in their world – the where, what, why and how of the experience:


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Looking at friction by device typeFRICTION WITH TOUCH vs CURSOR

DEVICE PLAYS A ROLE IN THE CUSTOMER JOURNEY

2 1to

This rise of mobile and touch usage has prompted a shift in UI design – away from designing mobile as an afterthought to a “mobile-first” strategy.

The critical shift has proven effective, as we see comparable levels of friction across touch and cursor devices.

APPLICANT STARTS

TOUCH vs CURSOR


It is not uncommon for users to take multiple sessions and employ multiple devices to complete an application

Specific types of friction can influence the environment and device choices of a customer at different points in the process

Attention must be given to creating a customer experience that fosters fluidity across devices, promoting engagement and confidence every step of the way

Studying digital customers and how device type fits into their narrative is an important exercise.

Overall time to process information is greater on touch; a natural result of smaller text, screen size and input mechanisms

Login related inputs are also a leading point of friction on touch; reflective of the ‘anywhere’ nature of mobile devices, where engagement and commitment levels can be at their lowest, and login credentials may have been misplaced, or not captured well at account creation

Bank Details stand out as the largest category of disparity; most likely driven by lack of readily available information that is not memorized or familiar

Longer time taken for identity related fields on touch could be reflective of hesitancy to provide PII with low engagement and commitment

Key observations:

The speed at which users process application information and answer questions often is an indication of friction. Looked at through the lens of context and the device used, it can present a more clear picture of what the person on the other side of the screen is experiencing.


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Looking at friction by device type, continued

5.35seconds

8.64seconds

60% longer

AVERAGE TIME TO PROCESS QUESTIONS

FRICTION IN PROCESSING INFORMATION

Median Time to Process (seconds)

Login Info

Loan Info

Income

Identity

Housing

Employment

Bank Details

0 5 10

Inpu

t Cat

egor

y

Cursor

Touch

MEDIAN TIME TO PROCESS BY INPUT CATEGORY


Negative values represent applicants typing slower than their individual baseline – indicative of more difficult questions to type

Positive values represent applicants typing faster than their individual baseline – indicative of easier questions to type

Login Info consistently exhibits high friction. In this case, we see what could be hesitancy to engage in the process, confusion, unfamiliarity or difficulty in creation of login credentials, or potential fraudulent behavior

Bank Details, on cursor, are slower than touch, possibly resulting from challenges in typing from a horizontal keyboard vs the compact numeric keypad on mobile devices

Answers to questions related to income are often typed in ‘number-by-number’ from a paystub or other financial statement with little fluency. Again, the numeric keypad could explain the slightly higher value for touch

Measuring typing fluency: Key observations:

Another meaningful measurement of friction is typing fluency. Like spoken words in a sentence, the nuanced speed, time between keystrokes and fluidity of typing provide cues into the state of mind and intent of the user.


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TYPING FLUENCY AS A DIMENSION OF FRICTION

(< Slower / Harder) Average Typing Fluency Value (Faster / Easier >)

Login Info

Loan Info

Income

Identity

Housing

Employment

Bank Details

-0.4 -0.2 0 0.2

Inpu

t Cat

egor

y

Cursor

Touch

AVERAGE TYPING FLUENCY BY INPUT CATEGORY


In general, we see more changes taking place on touch devices; with significantly more in-line changes, indicative of a more challenging input mechanism

The login area consistently shows more signs of friction, namely on touch devices, with a stand-out number of changes

Loan information, particularly the amount requested, is manipulated consistently across devices, which is not a surprise

Identity-related fields are comparatively high for answer changes, which can be indicative of potential fraud

Bank details are changed much more on touch devices compared to cursor, likely due to the potential lack of accessible information, details typically available at home and and/or on the computer

Key observations:

Answer changing can mean a number of things – from a simple and innocent ‘typo’ to an intentional effort to game the system. In all cases, there is a level of friction experienced, where the efficiency in the response is affected. We weighed its significance by the magnitude, frequency and context of the behavior.


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FRICTION THROUGH ANSWER CHANGES

Proportion of Applicants0 0.05 0.10 0.15 0.20

Proportion of Applicants0 0.10 0.20

Login Info

Loan Info

Income

Identity

Housing

Employment

Bank Details

Login Info

Loan Info

Income

Identity

Housing

Employment

Bank Details

Inpu

t Cat

egor

y

ANSWER CHANGES BY INPUT CATEGORY

Returns to Input Fields to Make Changes Inline Changes - Per Character

Number ofIn-line Changes

41+

31-40

21-30

11-20

1-10

Number ofChanges

5+

4

3

2

1

TOUCH

CURSOR


There is a point in any online application where the commitment level increases along with the level of vulnerability – when an applicant crosses over from anonymous shopper to identifiable person. We see clear indications of friction and hesitation to commit across all applications when it comes to revealing PII. When and how PII is requested can affect the user’s comfort level and likelihood to continue the process.

The wording of a question can impact the level of confusion and friction experienced – both in its understanding and level-of-effort to answer.


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Key speedbumps when onboarding digital customersFRICTION IN PROVIDING PERSONAL INFORMATION (PII)

FRICTION FROM CONFUSING LANGUAGE AND UI

We have seen occurrences where users transition from entry pages with only product selection fields to pages requesting PII. This would be in contrast to the more standard entry page combining both product and PII-related fields.

The scenario provokes a significantly higher level of friction, as many users see no risk in exploring product options, but become hesitant and noncommittal as PII questions come up.

Income questions on a ‘household’ level have notably higher friction – requiring more effort, and possible communication and involvement with another individual

The clearest and simplest wording creates the least amount of friction

Confusing questions can and do trigger abandonment

Key observations:

CAN A REQUEST FOR PERSONAL INFO BE

TOO ABRUPT?

Average Friction Index

Household Income

Monthly Net Income

Monthly Income Before Taxes

Annual Income

Annual Individual Income

Individual Annual Income

0 2 4 6 8

Inpu

t Tex

t

FRICTION BASED ON ‘WORDING’ OF INCOME AMOUNT QUESTION

COMMON PII-RELATED QUESTIONS

Email

Social Security Number

First Name

Last Name

Email is typically the lead capture and first contactable piece of PII

SS# is consistently a highly sensitive PII element

First Name is often the first PII question introduced

Last Name follows First Name, naturally with less friction

Key observations:Question:Friction level: 10

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6

4

2

0



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Proportion of Applicants

Bank Name

Routing Number

Income Amount

Account Number

Employer Phone

Housing Payment

Employer Name

Length of Employment

Confirm Account Number

Bank Name

Routing Number

Income Amount

Account Number

Employer Phone

Housing Payment

Employer Name

Length of Employment


0 0.03 0.6 0.09

Item

Tex

t

MAGNITUDE OF ANSWER CHANGES


Routing NumberBank Name

Account NumberIncome Amount

Housing PaymentLength of Employment

Employer PhoneEmployer Name

Confirm Account NumberHousing Type

Length at AddressAccount TypeIncome Type

Employment StatusPayroll Frequency

Payroll Type

Routing NumberBank Name

Account NumberIncome Amount

Housing PaymentLength of Employment

Employer PhoneEmployer Name

Confirm Account NumberHousing Type

Length at AddressAccount TypeIncome Type

Employment StatusPayroll Frequency

Payroll Type

0 0.05 0.10 0.15 0.20 0.25

Item

Tex

t

RETURNS TO INPUT FIELDS TO MAKE CHANGES

Number of Changes

5+

4

3

2

1

Like PII, there is consistent friction around questions related to all things financial. Perhaps the inherent nature of procuring a loan or a policy and the sensitivity it involves makes this a unique catchment area for friction and suspect behavior.

Key speedbumps onboarding digital customers, continued

FRICTION FROM INCOME, EMPLOYMENT + BANKING DETAILS

Percentageof Change

81-100%

61-80%

41-60%

21-40%

1-20%

Overall Friction Index of banking, income and employment-related fields consistently among the highest

Banking and employment details are typically less familiar to an applicant, requiring effort to gather information

Income can be confusing to calculate based on input format, and applicants tend to inflate and manipulate income

Key observations:

The magnitude of changes for bank-related fields is disproportionately higher than other areas

Income is manipulated with high frequency and high magnitude of changes

Magnitude of change is high, proportionally, for employment-related fields

Key observations:


When the Loan Amount element is more prominent and closer to the top of the page, we see a higher level of engagment and interactivity

When the Loan Amount field lives near the bottom of a long page, it runs the risk of not being answered. This could stem from waning engagement levels and hesitaton to commit to continue on with the process – a common issue at the end of a page

Key observations:


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Across applications, the UI treatment of inputs related to the loan product, specifically the loan amount requested, falls into two approaches:

Unlike the majority of the information-gathering fields on a loan application, product centric inputs are unique in giving the user the ability to ‘choose’ their response in the moment. For example, it is not uncommon for a requested loan amount to be adjusted several times.

The product offering and UXFRICTION THROUGH INTERACTIVITY

1. A prominent UI element, possibly a slider: Displayed early in the application near the top of the page, clearly standing out both visually and with clear language

2. A simple text field: Appearing alongside other similar elements; in some cases, located near the end of the page

$

DESIGN AND LOCATION. IT DOES MATTER.


Loan Amount

Loan Purpose

0 0.05 0.10

Item

Tex

t

NUMBER OF CHANGES ON LOAN TERMS RELATED FIELDS

Number ofChanges

5+

4

3

2

1

Loan Amount is clearly an area that a significant number of applicants are interacting with. Unlike ‘factual’ elements, this form of friction reflects a level of engagement, but potentially cognitive conflict

In comparison, Loan Purpose sees much lower interaction

Key observations:

2

1


APPROPRIATE QUESTIONS

SUSPECT QUESTIONS

City

Zip Code

Last Name

Primary Phone Number

Email

1.81%

1.75%

1.5%

1.22%

1.37%

Applicant usage of autofillApplicant usage of autofill


Bank Name

Housing Payment

Confirm Password

Employer Name

.08%

.02%

.02%

.05%

.05%

APPROPRIATE QUESTIONS

Email

SUSPECT QUESTIONS

Routing Number

Account Number

Email


Employer Phone

6.81%

6.17%

5.52%

4.22%

4.08%

Applicant usage of copy/pasteApplicant usage of copy/paste

Primary Phone Number

Loan Amount

Bank Name

Date of Birth

Social Security Number

.29%

.22%

.14%

.04%

.63%

We’ve all experienced the ‘autofill’ function when filling out an online form. It’s a time-saver, and to many, a way to reduce friction. It’s normal, at least in its typical application around identity-related data fields. So, when should autofill trigger concern? We look to context in determining potential fraud with this browser feature. Below are several examples of both normal and suspicious behavior using auto-fill:


Anomalous behavior indicative of potential fraud WHEN IS AUTOFILL NORMAL & WHEN IS IT SUSPECT?

Like autofill, digital users save time and effort by utilizing the copy/paste function from their saved clipboard to avoid manually typing. For hard-to-remember values, such as a bank routing number, it is quite useful and can help eliminate typos. But there are instances where it simply doesn’t make sense, which again raises concern of potential fraud. The grouping below communicates what we would expect as typical candidates for copy/paste and the outliers which draw attention as indicators of potential fraud.

STUDYING A SIMILAR CASE WITH COPY/PASTE

When a user changes their email 2 times, it might be friction in the form of a typo or confusion around which account to use. When a user changes their email 10 times (and it does happen), it is a clear indicator of potential fraud.

FRICTION, ANSWER CHANGING & FRAUD

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APPLICATION FRICTION

VERIFICATION FRICTION


Verification friction continues to kill conversion


Even 15 years into the digital transformation, we still see single digit conversion rates in the fintech space. Companies continue to lean on high-friction verification practices to compensate for a lack of visibility into the digital consumer. Unfortunately, this has cultivated a systemic issue with the best potential customers being pushed away, unserved.

SYSTEMIC WOES PERSIST FOR THE DIGITAL CUSTOMER

OF APPLICANTS LEAVE BEFORE SELECTING AN OFFER OR PRODUCT

OF APPLICANTS ENTER TOP OF THE FUNNEL VIA MARKETING ACTIVITIES

50-60%

100%A TYPICAL SCENARIO

OF APPLICANTS LEAVE DURING PHASE 1 VERIFICATION

25-35%

OF APPLICANTS LEAVE DURING DOCUMENT UPLOAD REQUIREMENT

15-20%

APPLICANTS BOOK OR PURCHASE

6-9%

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Contact us to start analyzing your own digital customer journey with a custom Friction Index™ Report

[email protected]

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FRICTION INDEX REPORT...ﬁnancial institutions and how they can increase conversion rates, reduce abandonment and recognize potential fraud attempts. The report uncovers key ﬁndings