Design Thinking – Task – Evaluating the Financial Risk bearing capacity of an  Individual

Challenge:

We see a lot of individuals who fail to make financial plan in their early career stage, leading to failure to  manage their finances in the later stages of their life. They become dependent on their children or  government for financial support. Based on the observations of spending habits of Individuals and  discussion with certain aged population who have experienced similar financial failures, we have realized  that the fear of not understanding finances and mind-set that it is a complex concept has resulted in the  behavior of not wanting to manage one’s own finances. In order to demystify this problem, we have  realized that we need to spread financial literacy in a simplified manner which does not involve complex  calculations on spreadsheets and lot of financial background. The most important factor is the disciplined  approach of saving and investing and controlling the expenses. We have developed an application  (Custom Risk calculator) which does all the complex calculation in the backend based on the inputs from  the user, which are mostly in the form of simple Q&As. Our main problem was to figure out whether we  have gathered all the relevant information for suggesting a risk profile of the individual using our  application. Since each individual is different and their current financial situation, financial commitment  and risk profiling is very different, how do we ensure that we are able to offer the right risk indicator to  them. This Risk indicator is the key element to their financial plan.

Selection:

We have decided to apply Learning launch as a tool to go to the market and test our application based on  real life situations. We had already brainstormed and made a simulation of various individuals  characteristics based on which the individual will be categorized such as the age group, monthly income  category, financial responsibility and commitments and used these characteristics to arrive at the  appropriate risk score ranging from 1 to 10 (1 signifying risk averse and 10 extreme aggressive risk taker).  We now want to test whether this ranking or risk profiling is appropriate and the portfolio suggestion  based on this risk profiling is truly valuable to our customer. Learning launch will help us get real life use  cases which can give good insights for testing our model and obtaining a feedback from the customer on  their risk profiling result.

Application:

We created a group in the social media (facebook) to gather individuals who would like to receive free  information on their risk profiling. We do not share investment portfolios with them, rather ask them to  answer a quick Q&A survey questionnaire and share some information which are very case specific – For  Eg: Individuals are shared a scenario and requested to make a financial decision, this will give information  on their behavior and help us assess the willingness to take risk. Their ability to take risk is determined  from the financial information shared by them. We ensured that we maintain anonymity while collecting  information, since it included personal financial information. With this learning launch tool, we gathered  the information and used it on our application (Custom Risk calculator) developed internally and derived

the output. We did the calculation manually along with the team of experts to cross validate the output  from our application (Custom Risk calculator). The whole idea was to test our application using real life  use cases. We even conducted a personal interview with few interested group participants and  understood their financial background in detail, which helped us understand the information that is  missing in our application (Custom Risk calculator).

Insight:

Based on the information gathered via Q&A and also from the personal interview, we collected various  data/information which was really useful in assessing the capability of our model and the diversity of the  individuals with varying risk profile. Especially with the personal interview, we recognized that there were  certain parameters/information which the individual really places a lot of significance but was not  captured in our model. We could then use such information to refine our model and make it even more  useful. We realized that our application was mainly designed for a particular geographical region focusing  on particular age-group people. Though we wanted our solution to be age agnostic, we realized that it  was biased for individual who were in the age group of 30-40. We then made modifications to it and  incorporated more information.

Approach:

We believe the tool has really helped us gain a lot of information, however going forward we would want  to test the application by gathering population from various groups. For which, we will approach  individuals using various mediums (Eg: facebook for age group 20-40) and other mechanism for other age- groups. This will help us get a holistic picture and model the application (Custom Risk calculator) in a more  appropriate manner. We believe, we will apply the same tool but to improvise the results we would refine  our reach by using various mediums to reach the customer.


Design Thinking – Task – Evaluating the Financial Risk bearing capacity of an Individual Challenge : We see a lot of individuals who fail to make financial plan in their early career stage , leading to failure to manage their finances in the later stages of their life . They become dependent on their children or government for financial support . Based on the observations of spending habits of Individuals and discussion with certain aged population who have experienced similar financial failures , we have realized that the fear of not understanding finances and mind - set that it is a complex concept has resulted in the behavior of not wanting to manage one ’s own finances . In order to demystify this problem , we have realized that we need to spread financial literacy in a simplified manner which does not involve complex calculations on spreadsheets and lot of financial background . The most important factor is the disciplined approach of saving and investing and controlling the expenses . We have developed an application ( Custom Risk calculator ) which does all the complex calculation in the backend based on the inputs from the user , which are mostly in the form of simple Q&As . Our main problem was to figure out whether we have gathered all the relevant information for suggesting a risk profile of the individual using our application . Since each individual is different and their current financial situation , financial commitment and risk profiling is very different , how do we ensure that we are able to offer the right risk indicator to them . This Risk indicator is the key element to their financial plan . Selection : We have decided to apply Learning launch as a tool to go to the market and test our application based on real life situations . We had already brainstormed and made a simulation of various individuals characteristics based on which the individual will be categorized such as the age group , monthly income category , financial responsibility and commitments and used these characteristics to arrive at the appropriate risk score ranging from 1 to 10 ( 1 signifying risk averse and 10 extreme aggressive risk taker ) . We now want to test whether this ranking or risk profiling is appropriate and the portfolio suggestion based on this risk profiling is truly valuable to our customer . Learning launch will help us get real life use cases which can give good insights for testing our model and obtaining a feedback from the customer on their risk profiling result . Application : We created a group in the social media ( facebook ) to gather individuals who would like to receive free information on their risk profiling . We do not share investment portfolios with them , rather ask them to answer a quick Q&A survey questionnaire and share some information which are very case specific – For Eg : Individuals are shared a scenario and requested to make a financial decision , this will give information on their behavior and help us assess the willingness to take risk . Their ability to take risk is determined from the financial information shared by them . We ensured that we maintain anonymity while collecting information , since it included personal financial information . With this learning launch tool , we gathered the information and used it on our application ( Custom Risk calculator ) developed internally and derived the output . We did the calculation manually along with the team of experts to cross validate the output from our application ( Custom Risk calculator ) . The whole idea was to test our application using real life use cases . We even conducted a personal interview with few interested group participants and understood their financial background in detail , which helped us understand the information that is missing in our application ( Custom Risk calculator ) . Insight : Based on the information gathered via Q&A and also from the personal interview , we collected various data / information which was really useful in assessing the capability of our model and the diversity of the individuals with varying risk profile . Especially with the personal interview , we recognized that there were certain parameters / information which the individual really places a lot of significance but was not captured in our model . We could then use such information to refine our model and make it even more useful . We realized that our application was mainly designed for a particular geographical region focusing on particular age - group people . Though we wanted our solution to be age agnostic , we realized that it was biased for individual who were in the age group of 30 - 40 . We then made modifications to it and incorporated more information . Approach : We believe the tool has really helped us gain a lot of information , however going forward we would want to test the application by gathering population from various groups . For which , we will approach individuals using various mediums ( Eg : facebook for age group 20 - 40 ) and other mechanism for other age- groups . This will help us get a holistic picture and model the application ( Custom Risk calculator ) in a more appropriate manner . We believe , we will apply the same tool but to improvise the results we would refine our reach by using various mediums to reach the customer .