Month: July 2019

This has been a fascinating week of discovery for me in the world of AI development.

It was my usual business trip to Yangon for my financial consultancy work after a 2 days period of brainstorming last week in S’pore. We had finally set up a digital transformation road map and game plan for our microfinance company for the next 12 months. In order to service 500,000 clients in 5 years from the current 30,000+, we need to have a quantum leap in innovation. The 8 pillars of innovation action plan we had mapped out – they all point to fintech developments that involve some element of AI evolution. I will elaborate on 2 of them below.

The first is about new chatbots. For most websites, we already have a chatbot button at the corner of the screen for user interaction and assistance. A majority of these are already automated with machines that handle up to 80% of the inbound traffic while the balance of the 20% are referred to actual human call centre personnel if the machine is unable to service further. In the old system, we have to program all the possible questions and answers into the database for the system to figure out the best response to each and every enquiry from a human user.

In the latest re-iteration of a chatbot, AI is added into the equation. What if we can set up a chatbot that is evergreen, learns on the job and stays relevant indefinitely as it builds up knowledge over time? This is possible now. AI helps the system to learn and then it uses statistical probability calculations to figure out the best reply. With NLP (Natural Language Processing) capability, the machine will be able to fully understand all requests and make an educated guess on the likely answer. Over time, it will get better at what it is tasked to do, as it collects more data and learns on the job.

The advantages of using an AI chatbot can also be channelled into many other areas within the company. What if we use this for internal purposes? Employee questions can be addressed and HR is able to outsource this function. For Marketing, they can use this to train new employees or do periodic training certification of staff members.

We are currently talking to a Canadian based company that has been doing this for a number of firms in North America. The initial discussions sound promising. We should be able to do more very soon. They have shared with us that the end to end process can take as little as 3 months, from the initialization of the project to going live.

The next pillar of innovation was on the development of a dynamic credit scoring model. Currently, we have a rules-based credit evaluation system, where only internally collected data from loan officers are inputted into the system. We have to constantly adjust the system as and when defaults increase. Even then, due to the size of the data, adjustments are still patchworks without any degree of certainty.

What if we can gather unlimited amounts of external data into this credit evaluation process, to find out what works and be able to fine-tune it at the push of a button? We can pull in data like geo-tagging of google map information on land size and acreage, weather reports – both current and historical. We can even gather social media data to determine if the repayment probability of a person is high…

AI excels in machine learning and with more data, the better it becomes. With unstructured data, it can detect trends that are invisible to human eyes. Using re-enforce and deep learning concepts, the AI will be able to run the process millions of times to optimize end results.

For our company, this will mean that we can approve more potential loans and lower/maintain the probability of default rates.  We can then predict with a high level of confidence that these approved loans are safe, due to the analysis of internal and external big data gathered.

We had a conference call with a fintech company from South America on Wed evening that had such a credit scoring model. They had been successfully using AI to derive credit scores on a number of agriculture microfinance companies.

As they walked us through their deck, I realized that some of the terms they used were exactly the ones I had learned from my business analytics course! In one of our projects, we were taught the CRISP-DM (Cross Industry Standard Process for Data Mining) :

Using the SAS Enterprise software, we used a structured process to come up with the best model for implementation. Most of the work was in getting the data ready (steps 2 – Data understanding and 3 – Data preparation). Then one will tell the software to use the various models available (decision trees, clustering, neural networks etc.) to crunch the data. Finally, we evaluate all of them to determine the one with the best fit and highest score. This will be the one to implement.

In my project, I had 5 data fields which I used to construct a model that was for the approval of a short term loan. I only had about 3,000+ data in each field but the AI could have easily absorbed a million data points. Once implemented, we could periodically rerun the whole process again with more data or additional fields. Unlike the traditional process which can become outdated over time, this AI-based process has a longer shelf life.

We are now embarking on a live Fintech experiment and journey to transform a traditional business that is so ripe for digital transformation. If we can pull it off, we will set new standards for the rest of the industry to follow. It will enrich the end-users and benefit our bottom line as we optimized all areas using limited resources.

 

 

The past 7 days had been a very interesting week for me. It was a rejuvenating beginning of business enlightenment, followed by a close fellowship of good friends.

I have been a financial consultant to an overseas microfinance company for the past 1.5 years. The company had achieved results that went beyond our wildest forecasts over the previous 12 months. Their loan books had expanded by a factor of 3 times and the number of active clients grown from 7k to 32,000+. There is still a lot of demand out there and it was agreed that we are now ready for a strategic digital transformation if we are to achieve a quantum leap in the next 5 years.

The CEO decided and planned a 2 days brainstorming session with his COO and 3 of us external consultants in S’pore this week. We had lots of ideas but no overall strategy yet. Over the past 6 months, there were a lot of fintech firms which had approached the company with different ideas on how we can advance. They all looked promising but we really did not know how they all fit into a coherent strategic scheme of what we want to achieve.

Digital transformation is confusing and exciting. It is hard to implement but yet we know that it has to be done asap. Our big-picture goal was to service at least 500,000 active customers in 5 years time. A brick and mortar strategy is not enough, hence we need to think out of the box and digital transformation is key.

The country of Myanmar is ripe for this. It opened up to the world only 7 years ago, having closed up for  50+ years. Everyone now has a smartphone. If you ask anyone if they have internet access, they will tell you that they have Facebook accounts. The country is primed to digital transformation via cashless mobile eWallets. With cloud computing and 4G speeds, development can be turbocharged.

Over the 2 days, we developed the 8 pillars of digital transformation which we required and put action plans around each initiative. We will involve our senior management team in project groups to execute these strategic objectives. The excitement at the end of the 2 days of brainstorming was contagious to everyone.

We now have a coherent plan to implement in order to bring the company to the next stage of its quantum evolution. Hopefully, the impact will also help bring a nation of farmers out of the vicious poverty cycle and into the 21st century. Profitability is good, but witnessing the financial success of rural families is even more rewarding. With financial support to address cashflow bottlenecks, farmers are able to address and remove uncertainties from their agriculture equation. It is time to execute our digital transformation plan now.

The following 2 days from midweek were long 6-hour lunches I had with a bunch of good friends. This was courtesy of the only one working amongst us. He is a successful banker who has always been generous to the rest of us. We had a lot of food via the new hotel loyalty program he had just signed up. I am grateful to have quality time with this group of friends whom I have known for 20+ years.

It has also been a rewarding Myanmar journey for me over the last 18 months, thanks to an ex-colleague that had brought me into his company. It is the crystalizing of my second half career road map, to give back to society as I have been lucky to have had a good banking career. I count my blessings for what I have been given.

Whenever one door closes, many others will open. I have to actively seek those new doors and be mindful of not withdrawing into myself and closing my mind to new experiences. The world is just too big out there to not explore.

 

 

 

 

 

 

Warning: Long blog ahead…

I am pleasantly pleased with myself for finally managing to complete 2 tasks this week. They may not look like much to an outsider, but personally, it had enabled me to connect the dots in more granular detail with regards to my AI learning journey. It has also helped me understand where we are now and what lies ahead.

Firstly, I completed the AI in Finance MOOC (Massive Open Online Course) which I signed up for in Mar. https://cfte.education/aifinance/ It consisted of 18 modules and took me about 3 months to complete. It re-enforced AI concepts which I had studied about previously. It also helped me to conceptualize the AI big picture, on the direction it is likely to move in the immediate future.

While the course was also a good introduction to AI, the market professionals presented a roadmap as to where they believe the areas of finance will most likely see the greatest impact. The underlying theme is clear. Current AI is narrowly focused – it does very well when directed to a specific purpose. This is due to its ability to review unlimited unstructured data, to be able to detect trends that no humans can.

We had supervised learning where AI is given a set of data and told of what the final outputs must be. What is more interesting is unsupervised learning, where through deep learning techniques, the program seeks to find meaning and trends by itself. For example, the machine learning program can be given millions of images to review and over time, it could correctly identify pictures of cats and dogs on its own. Effectively, it learns on its own.

With reinforced learning, we can move to the next level. This is now possible as technology has finally caught up. The programmer basically provides the AI machine with positive and negative rewards (incentives and disincentives) to drive its behaviour in order to optimize its performance. The AI is free to make its decisions towards a final goal. Over time, it will become better as it gathers useful experience going through the processes again and again.

The Alpha Go phenomenon https://www.alphagomovie.com/ that happened in 2016 was created by Google DeepMind based on this concept. It started to analyze Go games played by humans and slowly, it developed strategies which no human in history had ever thought of. It went on to beat the top human player in the world and started a mad development scrabble for AI everywhere. The successor to it was Alpha Go Zero, which took the giant leap of learning by itself without any human inputs. It beat Alpha Go by a resounding 100 to 0 games.

Since then, China had committed a national policy to AI. Gamers have also moved on to more complicated games to challenge AI. Earlier this year, a Starcraft AI managed to outsmart humans. Just yesterday, it was announced that an AI had beaten the best humans in Poker! https://www.theverge.com/2019/7/11/20690078/ai-poker-pluribus-facebook-cmu-texas-hold-em-six-player-no-limit

The other thing that I completed this week pertains to something I did as a teenager many years ago. I started to read science fiction books as the topic interested me then. The name Isaac Asimov constantly pops up as the finest author of such books that tries to predict the future. I began to read as many of his books I can get my hands on. During the 1980s, the only way to do so was to find them in 2nd hand bookshops or in public libraries. After trying to finish the “Foundation” series, my interest waned as the concepts became too abstract to me. I had moved on to other genres by then.

With my current interest in AI, his book “I, Robot” came into my mind again. It was a collection of short stories he compiled when he was in his thirties, way back in 1950. I was curious to understand how a futurist could be describing robots more than 70 years ago. This was way before they had basic functioning computers and this man was already projecting 100 years into the 21st century and letting his imagination run wild. I wanted to connect with him again after so many years, to hear about his words of wisdom on AI.

In this book, he elaborated on the development of robots through the years via the Robopsychologist called Dr Susan Calvin over 9 short stories. Robots had positronic brains that had the 3 robotic rules hard-coded into it. (1) Robots cannot harm humans, (2) Robots must obey humans except when it conflicts with the First Law, and (3) Robots must protect its own existence as long as it does not conflict with the First or Second Law. I was always very impressed that the Laws were so elegantly well thought out and to be able to encompass everything in a nutshell.

In the final 2 chapters, the robots finally caught up with humans. Eventually, humans relied on the machines to run everything. Humanoids became world co-ordinators and they become indistinguishable from humans. The fear of machines taking over had diminished over time. The timeline of the book was between 1980 to 2060, which is where we are today in 2019, the halfway mark.

As I mentioned earlier, the AI as we know today is what we call narrow intelligence. It does well in a narrow frame of reference and does not cross into multiple fields of human domains. It does a particular task extremely well and the more data you feed it, the better it becomes.

It is not that difficult to program AI solutions given the powerful software that is easily available nowadays. During my 1-year Business Analytics evening classes, we had projects used software like SAS Enterprise Miner that were crunching hundreds and thousands of data points in seconds, using various statistical formulas to optimize end results based on the steps we had directed the program to execute. Little did I know then that this was part of machine learning and it was part of my AI learning journey.

The current futurists predict that General AI will only be possible in 30+ years time, where narrow AIs combine together in a meaningful way to become what Isaac Asimov was talking about in his book. Androids and Humanoids will only be possible then.

AI has been the buzz word for the last 3 years and the advancements already achieved has been incredible. We are only at the start of an amazing journey that will continue to surprise all of us for years to come. AI Ethics and fine-tuning of unwanted consequences are some of the things we will still need to address. But what we will take for granted in the near future will seem to be impossible now. The future is so bright, I’ve got to wear shades!

 

 

 

 

 

This has been a happy week of get-togethers with old and new friends for me, to celebrate past and new experiences as we laugh and reflect over things we had done.

The party started on Tuesday. A generous ex-colleague had been sponsoring an annual get together of Treasury colleagues who have worked in the American bank over a 30+ years period.

Thanks to technological tools like WhatsApp, we have been able to connect with many others via the grapevine approach. Instead of just one administrator to the chat group, everyone has administrator rights to add new participants. The maximum is 299 and we actually hit that number 2 years back! One can join or leave whenever you want too.

To spice up the nostalgia this time, we encouraged everyone to post photos or videos of our time in Citibank. The Treasury team had started in the late 1980s till today, so there are 3 distinct periods of time where people came and left : (1) before 2000 (UK ERM, AFC, Russian meltdown), 2000 to 2008 (Y2K, Tech bubble, 9/11, GFC) and from 2009 till today (Global easing, banking downsizing, Trump).

After 2 days of sharing, we had 80+ RSVPs and it felt like this will be a record reunion. Tuesday evening came and we have people streaming into the big hall in a private club that was booked for the event. With a buffet and free flow of beer and wines, it quickly became a big and boisterous class reunion of sorts.

There were so many people I knew and have not caught up with in years. I just moved around and said hi to everyone, taking pictures to post in the chat and reminiscing about things we had done in the past – some crazy and politically incorrect stuff which would have been shocking in today’s PC world.

We probably had at least about 100 persons that night. The total number of years of work experience that we accumulated within the room that evening was easily 1,000 human years. Throw a stone in the room and you would likely hit someone who had spent more than 30 years in Citibank. The record was 43 years. Imagine starting your career with the first job and working till you retire in the same company! It is really unheard of nowadays as millennials believe that you have to constantly move on to gain experience.

Personally, I was in the bank for 19 years that covered 3 departments within Treasury. The life long friends and incredible business network that I acquired had enabled me to accomplish goals will would be unimaginable elsewhere. I struggled to assimilate in my last 2 jobs after Citi. Before I could establish a new network, circumstances had pushed me out of the toxic environments. This had made me realise how valuable a network I had lost when I left Citi.

A gathering of ex-colleagues and old friends with a free flow of sponsored booze really drove up the nostalgia meter for all of us. We reconnected, talk about the crazy shit we did and the impossible situations we experienced in the midst of the various financial crisis over the years.

At times, we really thought that we had reached the end of the financial world but surprisingly, the world would spring back to life again. The stress we went through made us much stronger in the end. Been there, done it. We became jaded, having seen it all. Yet nowadays, the new world does not seem to value work experience anymore as the machines and AI seek to replace the slower humans.

That evening, we collected yet another memory of another happy and successful annual reunion, hoping to have many more in the future. It amazes me that I had worked for almost 29 years now as I face the tail end of my career. I am indeed proud to have been a part of this ecosystem of people who had contributed to my rich work experience.

For the rest of the week, Thursday was another 2 celebrations of sorts. Lunch with a group of buddies – our regular get together for a 4 hours lunch. No matter what, we always have things to discuss and share as the flow of the wine and whisky happens. The get-togethers recharge all of us.

In the same evening, I had another event with new friends we had gotten to know during the recent China tour we went in Apr. My wife and I met like-minded people in our age group who enjoys their drinks. One of them decided to organize a meeting this evening and I suggested a drinking hole within walking distance from my home. It was a nice catch up with live band performances.

At this point in our life, it is always good that we continue to expand our circle of friends. We need to make an effort to meet new people to enrich our second half. There is an easy tendency for one to withdraw into a hermit lifestyle and stay in a cocoon. We have to resist that. At the same time, we must treasure the life long friends we had made by constantly reaching out to them on a regular basis. With the arrival of social media, this has made the job easier.