UX Research Cheat Sheet

UX Research Cheat Sheet

One of the questions we get the most is, “When should I do user research on my project?” There are three different answers:

  • Do user research at whatever stage you’re in right now. The earlier the research, the more impact the findings will have on your product, and by definition, the earliest you can do something on your current project (absent a time machine) is today.
  • Do user research at all the stages. As we show below, there’s something useful to learn in every single stage of any reasonable project plan, and each research step will increase the value of your product by more than the cost of the research.
  • Do most user research early in the project (when it’ll have the most impact), but conserve some budget for a smaller amount of supplementary research later in the project. This advice applies in the common case that you can’t get budget for all the research steps that would be useful.

The chart below describes UX methods and activities available in various project stages.




Artificial Intelligence and Risk Management

How Can Artificial Intelligence help Investment Banking Risk Management?

Beyond Just Calculations….

The risk management algorithm has always been more about complex calculations. There are various models such as the binomial model, VaR (Value at Risk), Black-Sholes Morten model. These models are put into different simulation modeling algorithms such as Monte Carlo simulation, GARCH (1, 1) also known as Generalized autoregressive conditional heteroskedasticity model, EWMA, which are currently used by the banks. CME (Chicago Mercantile Exchange) developed risk management algorithms PC-SPAN for portfolio margining

  • SPAN has been reviewed and approved by market regulators and participants worldwide.
  • SPAN is the official Performance Bond mechanism of over 50 exchanges and clearing organizations worldwide, making it the global standard for portfolio margining

Risk management is the application of the risk management process which consists in:


The future challenge to integrate Risk management in every area of a company means “operational,” “economical”, and “strategically, Enterprise Risk Management (ERM) will be a need for the future management processes.

The latest developments that are shaping up in the Fintech focused on the Risk Management is an application of Artificial Intelligence in the Financial Risk Management.

How different methodology of a quantitative risk analysis to develop a formal risk management can leverage Artificial Neural Networks

What is similar between an engineer controlling an industrial facility and a bank operations manager controlling payment processing? Both deal with operational risks that require immediate action at the earliest sign of trouble.  Process for both is same as described in below diagram


Financial Institutions are primarily risk managers and manage a variety of financial risks — market, credit, operational, currency, liquidity, and others. For having a robust risk management the bank need to ensure that it should embrace data-informed technologies that are being applied to the following



Why need the Black Box?

Data-Informed Operations

Data-informed operations are the basis for day to day operations. No matter how sophisticated the data collection and processing systems are, a trained human is ultimately responsible for making critical decisions.  The bank operations managers can perform exception processing and error recovery based upon system-generated communications.

Any analytics applications that are guiding their decisions will submit their findings to a human,  to effect any changes to operations. The reason why operations department run by large sized teams who are challenged to keep improving their effectiveness through improved process and use of the latest cutting-edge technology.

Chasing False Alarms

Risk management teams use expert systems, primarily based on rules, to monitor operations and generate alerts. Expert risk managers set alerts based on rules, historical thresholds, specific KPIs, and the tuning of each of these over time takes up a lot of the time of experts to maintain the balance between risk exposure and team efficiency, and that has its consequences.

One of the biggest challenges of improving effectiveness is false alarms raised by analytics technologies currently used. Not being sensitive enough means that the risk exposure is higher, being too sensitive also means the operations team under much pressure is chasing false alarms.

No algorithm is useful in isolation, but instead from the perspective of how it interacts with its environment (data sampling, filtering, and reduction) and also how it manipulates or alters its environment. Therefore, the algorithm depends on an understanding of the environment and also a way to manage the environment


Any rules-based systems pose a major dilemma to an operations person because; the cost of missing an actual exception, models may be tuned extremely conservatively. As a result of this, it significantly increases operational cost, but they also create “alarm fatigue”, in which operators expect false alarms to such an extent that they miss a genuinely positive and allow an improper transaction.

Harry Henderson proposed an AI model which has both the old rules memory and a working memory where the model intelligently learns from the current environment and the rule matching system quickly re-tweaks the rules so as to avoid false alarms without losing the original exceptions




Trends and Human Processing (What is in the BLACK BOX?)

A robust risk management is about dealing with real-time transactional data and historical trends/learnings; there is an important aspect of time that affects how decisions are made. In general, humans are good at interpreting simple trends by looking at slopes and levels, but human have limitations to describe complex patterns. A solution to the problem is if expert AI systems can encode these trends


The problem with the AI system is when different pieces of information don’t arrive at the same time or rate, incorporating the trends in such data into any AI system tends to be difficult.

For example – In the case of the Monte-Carlo simulation the inputs may be fixed, but the frequency of the inputs A, B, C, and D may vary leading to which the random number generation of the Monte-Carlo model(MCM).  May not follow the probability distribution curve which is a function of (PDF), to ensure that various risk has been factored the outputs of the MCM  would be evaluated and tested for the hypothesis using multiple regressive inputs to validate the confidence level of the model.

A critical aspect for the Risk Modeler is to select the appropriate distribution function according to the data available; it can follow any Log function, Normal distribution, Chi –squared distribution function, etc. The modeler also needs to understand the behavior of the data in the practice; typically it is based on an available historical database.


Monte Carlo Simulation Model for risk assessment

This problem is exacerbated in financial services applications where trends are formed (and change) over periods of days, weeks or even years. Operations users cannot be expected to recognize long-term trends in customer behavior without expert system assistance. The result of such difficulties is it increases the number of effort people has to put into confirming alarms by interpreting patterns.


Expert instead of Learning Systems (Mind in the Box)

The next issue is that expert systems do not change by themselves as they have to be programmed by experts. The main advantage of AI system is that the whole process (training and testing) mimics the human brain reasoning like learning occurs in the minds of experts who then apply the lessons of their learning into the next versions of the rule engine base.


With the rapidly changing financial business and data landscape, the operational systems have not evolved quickly enough. This leads to more risk exposure and less optimized use of the margin money.

For exampleGame of Chess


But then the questions comes Can machine ever have a mechanism to reach a conclusion based on just common sense which is beyond logical reasoning? Can machines present facts which are beyond the mathematical formulas? Can machines make a logical deduction of the cases which has the rarest or the rare possibility of occurrence to ensure optimal use of time and resource?

Would AI system get thumbs up or thumbs down in future, is something that only time will tell, as the commercial application of AI has to withstand the challenge of diversity as different Banks, Insurance companies, funds and financial firms don’t speak the same risk – language. Never the less each one of them performs the cost-benefit analysis, sensitivity analysis, scenario analysis which permits to perform both the quantitative and qualitative analysis


Happy Reading!!

Abhinav Gupta

Product Management Myths and Reality

What has changed, over the years, in the technology industry; which required a role of a product manager?

I did not hear the designation of a product manager 10 years back, there were business analysts, project managers but not the product manager. There is an argument, that somehow end-user needs got detached from the technology-driven product. The product manager enables a company to rapidly deliver products to market since it skims and skips lengthy traditional market research, and consequently bases product design decisions on internal company expertise. Probably yes the business has been changing so rapidly which required this as a specialized role.

So who is a product manager? A business analyst, UI/UX expert, Technology expert, Project manager, Sales associate, Network specialist?

I think the answer is none of them, the commonly used a vague definition of product management misleads and allows many people to place their own personal interpretation on the role of product management, and this is leading to a multitude of diverse definitions in the technology industry. As a product manager, you need to be the like the conductor of the orchestra. You may not know which API’s to call, which would be better to have a server hosted application or a cloud platform, does the customer care about all that?  The Product manager should be as a voice of the customer and should be ready to take tough calls, he should be creative and clear in his ideas and politically correct to get it implemented, should be listening to thought but at the same time should the person who would call the shots.

Does the definition of the role of a product manager in my company same everywhere?

Every company is different and handles product management differently – meaning that the product management discipline is not standardized as much as it could be across the high-tech industry. Further complicating the situation is that in each company there are individual stakeholders who often view and interpret product management very differently from each other. Based on my conversation with various product managers working in different companies, some say that they have been recurrently successful as product manager while others said that they have been just lucky till now, but now they are working on having a consistent understanding of the product management in the organization.

What do you understand by Product manager as the CEO, of the product?

This statement is been used quite often in various blogs, talk’s and books. The product management comprises of all the activities that are responsible for the product to be successful in the market. For example, providing incorrect market requirements, erroneous pricing, or an inaccurate profiling of the target market can all be detrimental and critical. If just one of these aspects of product management is a miss, then the product’s chances of success are greatly diminished and who shall hold responsibility for the failure of the product; The Product manager! And it’s his responsibility to fix it.

How important is the role of a product manager in making a product successful?

Some products are successful because of external factors, timing, or merely good fortune. Not all successful products have had great product management behind them, but it is clear that many product failures have had poor or no guidance from product management. Numerous cases where companies like Google, Apple, JP Morgan’s and Microsoft failed and the most decorated product managers were needed to step down whether it was Apple map or google phone.

 Is it necessary for the product manager to be an Agile/Lean/RAD/waterfall expert?

Well, there is no right or a wrong model for a project, there are instances where the agile model may lead to budget overruns due to continuous change in product requirement, despite having the most amazing product the time to market the product led to product failure. I think everything works, even tossing a coin before choosing the model of development might work for you, but you need to make it work for you.

To conclude, I think there is an increasing need for standardizing the product management as a discipline, and every dollar that a company earns through product development some portion of that dollar they should reinvest in improving the area of product management. Efficient product management practices within the organization increase product managers on job productivity and improve a product’s chances of commercial success.


What steps can Business Ops and Technology department take to achieve synergy and agility?

Primarily the Operations and the Technology departments are working in silos in any organization, both operations, and the technology has multiple global stakeholders requesting for product or process enhancement. It’s hard to get a holistic picture of the product issues for a product and the process manager due to the agility involved in the highly complex process and products.

The stakeholders share their strategic product “needs” directly with the technology for example in the case of any regulatory enhancement this would directly come as an enhancement request to the technology dept. Whereas what the business “wants” for example a report, or some data element on a screen comes from the operations user to the technology dept.

Creating efficient process is now a key concern for business managers and technology architects, and there is a need to respond to disruptive innovation in the Financial Services sector. The technology dept. needs to support growth and return to the emerging “customer centric” world versus the traditional “product-centric” view.

What is needed? And how?

  • Cost efficiency via standardization
  • Faster time-to-market through deployment of integrated and tested components
  • Better operational control and Transparency through operations tracking and built-in performance measure
  • Standardization and use of best practices for product development and process optimization. Various departments need to share their best practices and success stories with each other and share the utilities that could help in improving the overall process.

Ops n technology


To have a fully integrated product and process solution there has to be a constant feedback between the ops and the technology department. Both the ops and the product development should use the same tool for incident management to get the holistic picture of the current state of the business, ultimately both the business goals and the technology goals need to tie to each other.

Ops n technology3

Abhinav Gupta

Public Profile –


Twitter @abhi13aug

Time to check Modi’s test scores!!! India 2014-2015

I am not a political analyst, but it has been more than a year Modi and NDA came into power with a great victory whitewashing the Congress-led alliance UPA.

Did India got the “Achhe Din” he promised?

He has been running a massive India marketing campaign all over the world, which is good but as they say, “Half of the marketing goes waste, and you do not know which half.”

I thought of doing a status check on some of the macroeconomic factors that drive the country’s economic stability and growth. India has been in a sweet spot where China is slowing down, Russia almost at the edge of the war, and Oil Prices at all time low, India poised to 7.4% GDP growth rate based on the World Bank data.

  2012 2013 2014 Result
India GDP Growth ($ 2.1 Trillion) 5.1 % 6.9 % 7.4 % India growing – True
China GDP Growth ($ 10.4 Trillion) 7.8 % 7.7 % 7.4% China Slowing – True
  • Good news– India is way ahead of Russia and Brazil where the GDP growth rate is less than 0.5%, India growth rate increased.
  • Bad News – India no way close to China.

India’s favorite topic of any election campaign is “Remove poverty”, every political party; every candidate has talked about this issue, I think the country has been going fairly well, we can debate, it is not enough if we compare with the developed countries.

But the question that I have – do we see a positive displacement on the ground?

The previous government did a good jo`b from 2004 to 2011; with more than 40 percent people were leaving below the poverty line in the year 2004 that came to 22 percent in 2011.

Mr. Modi would get his numbers in 2015 when World Bank publishes Poverty headcount ratio at national poverty lines (% of the population) numbers.

  • Good NewsSeems like numbers would be better than 2011
  • Bad NewsNumbers way below any of the BRIC nations

S&P Sovereign country rating for India 2015 – “BBB” – Helps countries getting loans at lower rates and the cost of capital reduction

  • Good NewsBetter than Russia and Brazil.
  • Bad News –   Lower than China


Corruption has always taken the center stage in India, with big scams during the Congress rule and was the primary reason Anna Hazare started one of the greatest revolutions in India post independence, which led to the formation of new political parties in India and youth getting involved and informed with the politics in India.  Mr. Modi has debated a lot on corruption during all though out his election campaign, but what has changed on ground India moved nine ranks above from 94th to 85th in 2014.

  • Good NewsBetter than Russia, China
  • Bad News –   Lower than Brazil, and way below the world tally, still much work needs to be done to stop tax leakages and black money

Corruption Perceptions Index

The most used indicator of corruption is the Corruption Perceptions Index of Transparency International (TI). This index is based on 13 independent surveys, measuring public sector corruption for 178 countries. On a ranking of 0 to 10 (0 being highly corrupt and 10 being highly uncorrupt).


Last few months there has been a debate raising the question of Indian Democracy. I think India is one of the greatest democracies in the world, to back my thought I looked at the Democracy Index.

Democracy index measures 167 countries using 60 indicators in five areas: civil liberties, the electoral process, government function, political culture, and political participation. It uses a 10-point scale (0 being least democratic and 10 being most democratic)

  • Good NewsBetter than Russia, China and ranked 27th in the world
  • Bad News –   Election participation is less usually only 55-65% voters cast their vote


How free are you in India?

I think it is the best place in the world; India matches shoulder with all the developed countries in the western world. Middle East, Eastern European and African countries have never been in a high spot regarding the civil liberties.

Freedom in the World is an annual survey that focuses on political rights and civil liberties.


Inflation is the biggest friction force in any developing countries and has been one of the Devils that has toppled governments in past in India, Mr. Modi, and RBI governor is under tremendous pressure to control Inflation in India, there has been some significant moves by the government to control it. Reserve Bank of India (RBI) has reduced 1.25% in Repo rates making EMI’s going down in last 1.5 years, which gives a sense of relief to the common man.

Based on World Bank report

  2012 2013 2014 Comments
Inflation, consumer prices (annual %) 9.3 % 10.9 % 6.3 % Still very high
Wholesale price index (100) 117.7 % 125.1% 130% Very High


Skill Development in India has been Mr. Modi’s focus areas, where he mentioned across the global platforms. India is in a real bad shape, ranks 130th in the world based on Human Development Index, conducted by United Nations, Countries are rated based on the following factors: education level, literacy rate, years of schooling, income, life expectancy, and standard of living.


Ease of doing business – India has made a significant jump in doing business, but it still lags a mile against any BRIC economy.  It is still very difficult to do business in India.


There is some comfort coming in from domestic factors and the economy has slowly started reflecting in the numbers positively towards the policy changes initiated by the Narendra Modi government. The government has done a fairly decent work in most of the areas but missed out on two of the high profile bills like GST and Land acquisition bill. Rising retail prices and the dollar at 67 has been the top concerns as the rupee has not depreciated a lot. We need to wait and watch another year before #Digitalindia,#MakeinIndia, etc. shows some results on the ground.


Disclaimer – I have no relations with any political party, these are my personal views. The reason for this study is to examine the various macroeconomic factors, and how India is ranked today compared to a year before.