In today’s world, technology has cut reaction time down to almost nothing when it comes to banking. You can quickly and easily respond to fraud alerts, overdraft warnings, and many other notifications. But what if your bank was proactive? It would do the thinking for you ahead of time, so you don’t have to do as much worrying in the present.
What if we can make beneficial decisions on behalf of our customers? What if we can prevent our customers from making bad decisions?
Before meeting the client's desire of creating a product that is "visually striking and interactive", our team first set out to understand many of the cognitive decisions and errors people make when considering their finances. How does the bank define an error and how do people define errors? What about the definition of a crisis? What drives trust in automation? This research process lasted 4 months and included extensive secondary and primary research.
We began with a literature review of 24 academic articles, an exploration of four analogous domains, and a competitive analysis to identify gaps in the market as in analogous spaces. Following this secondary research we began our primary research by recruiting and interviewing 17 target users (upper middle class US residents). We also did Card Sorting, Matrix Diagramming, and What's On Your Radar exercises with users. We continued with guerrilla research, follow up surveys, and created an affinity diagram and story-based personas.
Studying various domains through an extensive literature review helped us to gain an understanding of the human nature of the decision making process, and where it can go awry.
People do not make decisions based on rational thought alone, but instead are universally affected by a set of errors that have been proven to influence the way they think about and approach choices. These decision making heuristics, or shortcuts, allow for quick decisions but can backfire in situations that require more thought.
People place disproportionately high focus on examples or information that immediately come to mind.
People seek out only information that supports our existing beliefs and expectations, and will interpret all available information to fit those beliefs as well.
People prefer to rely on a single, most salient, piece of information—generally the first or last given.
People place greater emphasis on avoiding losses than on acquiring gains.
People prefer a sure outcome rather than a gamble, even if the gamble has a higher end value.
People place too much confidence in their own decisions.
We studied the competition through the lens of managing both income and spending habits, and evaluated tools across domains of savings, investment, debt management, bill payment, and financial education. We found that small companies are taking the biggest risks with innovative financial technology and tools, and it is paying off. While the threat to large banks is small, they are driving higher expectations in the retail banking sector.
Our team conducted interviews interspersed with structured activities to better understand where people obtain financial information and how trust influences decision making.
We used a flexible structure of both questions and activities, to help build rapport and keep participants engaged. This also allowed us to improvise and cater to the communication style of each participant.
This is an activity where participants arranged a set of pre-made cards into groups of their choosing and labeled them. It offered information about how finance fits into the broader context of life.
Participants generated sticky notes to illustrate where they turn for financial knowledge, advice, and assistance. The closer these notes were placed to the center of the chart, the more important they were to that individual.
We spoke with passersby on a busy upscale retail street in Pittsburgh about their sources of financial literacy and assistance. We used the "What's On Your Radar?" activity as entry point to initiate conversations.
We sorted and grouped over six hundred notes in an affinity diagram to find patterns throughout the interviews we conducted. Grouping these patterns led to over eighty separate insights into the financial mindsets and situations of our target population. Further abstracting these insights and focusing on the most powerful and impactful items led us to derive a series of key themes as one method of organizing our findings.
Overall findings from our interviews in primary research revealed a number of common themes and patterns, and in particular, a couple of interesting tensions. Pursuing higher education, for example, is viewed as crucial to achieving financial success while also imposing an overwhelming burden.
As themes emerged from our affinity diagram analysis, our team noticed that many insights within these themes were in direct conflict with one another. These conflicts led us to additionally organize our findings by way of a series of powerful tensions, both internally to a single individual, and externally among different groups within our target demographic population.
We found external tensions result from opposing knowledge, values, and behaviors between separate subgroups within our participant pool. These external tensions are important to consider because they play a role mediating between different perspectives and values within the population as a whole. I created a model of these tensions in Adobe Illustrator.
Internal tensions describe conflict resulting from incongruent knowledge, values, and behaviors within a single individual. These tensions were observed across genders, geographic locations, generations, and income levels. Many of these tensions were not directly acknowledged by participants but came about through our team’s affinity diagram analysis of the data. Below is a model I created of these internal tensions in Illustrator.
From our interviews, we heard people speak about their financial decisions in the context of their lives. Participants shared stories teeming with details about life events, personal relationships, and emotional states. To illustrate the varied needs at different life stages, I created a financial journey map based on stories taken from our interviews.
While we developed a series of personas, there were two we felt were most in need of design help. Here is an abridged version of a much more extensive set our team developed.
The definition of visioning involves "the development of a plan, goal, or vision for the future." For our project, we wrapped the research phase of our project in the spring with a 45-minute presentation to faculty, students and our clients. Immediately afterwards we jumped into a visioning session with two members of our client team, beginning with a sit down Q & A. From there, I lead a structured an ideation session around three key activities:
Goal: Tackle the problem space
Method: Everyone folds a sheet of letter-sized paper into quarters and spends two minutes writing what they think the problem is, then passes it to their left. The next person writes a solution to that problem. Repeat two more times.
What we learned: Building trust and value, dealing with context in decision making, and helping users understand their future selves and needs are key.
Goal: Generate as many ideas as quickly as possible
Method: Draw an x-axis for different user types we might design for. On the y-axis list different possible platforms. Work in pairs to generate ideas on sticky notes and populate the grid.
What we learned: People got excited about empathy building, tools for power users, and ways to simplify financial decision making.
Goal: Determine the ultimate value to the customer
Method: This individual activity involved spending 5 minutes sketching a better future for BofA’s core customer in the form of an ad.
What we learned: The biggest concern for the client was delivering a financial future without worry. Additionally, building trust and empathy through technology, and easing the tedious burden of tracking finances.
Our creation process subdivides itself into three tiers based upon the fidelity of the prototype produced: low, medium, and high. With each increase in fidelity, details become more and more crucial. During our initial low-fidelity stage, concepts were given focus over implementation, and no idea was deemed too wild or implausible. By contrast, our high-fidelity stage prioritized details and feasibility in order to create a product that could be deployed within eighteen months.
To begin gathering and evaluating solution possibilities, we needed to begin with extensive exploration. Note, throughout this part of the project I cannot describe or depict any of the actual prototypes created because our work is currently undergoing patent review and is protected under an NDA.
After visioning our team took a bit of a break, so I thought it important to begin by taking stock of the problem space as a whole. What were our key design opportunities? What problem areas were closely related? We drew a kind of spider web and wrote our names in the web at the end to use this as a launch pad for further ideation.
Each team member sketched ten separate concepts that fell within the intersections we found in our web. Sketches varied in fidelity, refinement, and format, ranging from storyboards to advertisements to wireframes. All expressed different ways to solve the many sub-problems identified from our research and our web diagram. The solutions we explored were just as wide ranging as the sketches, covering everything from mobile apps to robot advisors.
From these grouped sketches, we pulled core concepts which became a series of refined set of nine storyboards. Each storyboard represented a group of initial sketches and expressed the way each a concept might actually impact a user’s life and finances. A single concept was explored in three or four panels by describing context and interactions without becoming overly focused on the mechanisms of how a concept might work.
Refined storyboards were speed dated with a series of eleven fellow students to understand emotional reactions to our concepts. Each of our fellow students saw all of the refined storyboards for a brief time, and then described their gut reaction to the concepts they saw. Reviewing our speed dating results showed us reactions ranging from privacy concerns to excitement over new concepts. Overwhelmingly positive or negative reactions led us to safely focus on some ideas while discarding others.
Based upon our speed-dating results, we determined the core ideas and concepts that we felt showed promise or would benefit from additional testing. These became physical, tangible low-fidelity prototypes - everything ranging from ambient displays to paper prototypes of mobile apps.
We set our sights on finding ways to enable affluent retail bank customers to make better, more informed financial decisions. To meet this goal, our team developed a series of questions that we needed to answer as a foundation for creating a solution. For each of the questions, we analyzed and identified the best research method for finding an answer and deriving insights. From those insights, we used an iterative design process to arrive at a solution. Due to a non-disclosure agreement, I am unable to show or describe our prototypes while patent applications are in process.
In order to test our prototypes with our peers, we conducted informal expert reviews with one individual at a time per prototype. These expert reviews showed us strengths and weaknesses of both concepts; where one offered simplicity, the other offered increased control and detailed information. While we found promising aspects of each prototype, they were not without drawbacks, and simply selecting one of the two to move forward with was not an easy choice.
After this stage we tested one additional mid-fi concept as a 30 minute think-aloud test with 11 real users that we recruited in Pittsburgh and in Washington D.C. I participated in two of these sessions. We also used a matrix activity to plot users' response for possible additions to our design, that matrix was plotted against high effort to low effort, and high reward to low reward. Based on that feedback we made additional adjustments to our prototype as well as worked to prepare a final usability test that we performed with 12 additional real users in Charlotte, NC with our client observing.
While I cannot describe or show the final prototype, I can say that I began by creating the branding and initial UI styling along with wireframes for several sections. We iterated on our design over the course of a week and a half and two teammates and myself built our prototype with Atomic.io. Our team developed a script for the final think aloud test, and my teammate also developed a final activity to test the proper tone of voice.
We performed our usability test over two days in Charlotte with 12 real users in a lab facility, with our client observing. I personally conducted three of the tests. We were able to make several changes to our prototype between the first and second day which ended up resulting in several key findings. After the testing was over we combined our individual notes and two other members of our team worked to distill the findings. Finally, after testing was over I made final tweaks to the design of our prototype and ran a small A/B test with fivesecondtest.com and was able to double the success rate of our key feature.
A working prototype built with Atomic — Designed and developed by myself, Michael Anderson, and Raghav Anand
A 36 page report of our process and findings — Designed and written by Dan Shilov, Alicia Silvano, and myself
"Guidelines Going Forward" White Paper — Designed and written by Dan Shilov and Alicia Silvano
Team Website — Designed and developed by Michael Anderson
Two minute pitch video — Storyboard, script, production and editing by myself and Michael Anderson
A 45 minute presentation, given in Charlotte to client and internal stakeholders — Developed by team