Of preaching health bands, talking tennis rackets and more…

Advanced Analytics software companies like SAS have been around for over 30 years now, helping corporations and governments analyse data and make better decisions, however it has been rare to have analytics touching the lives of the end customers and helping them take their daily life decisions. With just about every device which we carry and work with; from a cooking range to smart electricity meters capturing user data, analytics as a service will increasingly change our lives without the end consumer ever knowing that he is actually taking an analytically driven decision.

Take the case of the "Smartest Tennis Racket in the Planet"

Babolat is one of the leading tennis racket manufacturer in the world and has just released the Babolat Play Pure Tennis Racket - The world’s first data capturing tennis racket (and btw the same is legally approved by the ITF). From Andy Murray to Nadal, swearing by the power of the racket, it wont be long before this becomes the de-facto standard of the future. 

This smart tennis racket is revolutionizing the tennis world with just the addition of a few small additions  (a small accelerometer and gyro-meter fitted at the edge of the handle, and some more paraphernalia to transmit the data) which can record every stroke and volley done by you in the game. The data is sent to a cloud, where a whole bunch of advanced analytics (from the best analytics company in the world :) runs on it, and the end user can download the analytical insight on his performance on his iphone or android device, as to which strokes were the best, a cluster analysis on what type of shots he placed and the outliers, which shots were the weak ones, after what time did he start losing steam etc. The next version of the rackets may even talk back to him saying “'Hey, you have a weak backhand, and 75 percent of the shots you hit were backhands in the last 10 mins– why do you think you're losing?" Dont believe me as yet,  well, check out this link

Imagine the possibilities of embedding analytics into our daily life technologies:

• Imagine a health band as a patient engagement strategy or to revolutionize the way we handle disease management for patients with CVD risk, that can accurately measure your health indicators and give you back near real time trend or forecast on your health risks (Imagine the possibilities for the UAE, which ranks among the highest in cardio vascular disease risk population)

• Imagine your office chair telling you that its time to go and take a walk in the park or that you have not exercised enough today and have been just sitting around blogging or surfing the internet

Anything that moves and does not, seem to be capturing data and sending it to a cloud. Imagine how much smarter the world is headed to be into the future with analytics deployed on the cloud working on this data. It is definitely the age of analytics and specifically big data analytics, but the difference today is that in today’s world it would not just be corporations and governments using analytics for decision making, it would be end users seamlessly embedding analytics into their daily lives to take the most basic of decisions. As Tom Davenport says in his latest book “Enterprise Analytics”, this is not the age of “software as a service (SaaS), it is the age of “decisions as a service (DaaS)” enabled through software's like SAS.

Welcome to the world of analytics with preaching health bands, gossiping office chairs, talking tennis rackets and more...

Have a good week,

Because the Future is now...

What caught my attention the other day was how large corporations and key govt organizations in the region were not truly unlocking value from their data. If large corporate giants in this region were to unlock their data with powerful predictive analytics, they would probably have  insight into the pulse of a nation, better than possibly anything that the nation’s leadership has ever been used to. Aha! You obviously do not trust me, because that makes no sense (I see that smirk on your face, but I request your patience). Here is one example which I have been chewing on for a while...

Believe it or not :NBAD can predict the financial Health of UAE better than the Central Bank!

Emirates NBD and National Bank of Abu Dhabi are the largest issuer of cards in the UAE. They have such large market shares in the UAE, that their transaction data captured in the core banking system is probably the best way to track the macro economic indicators of this country than any govt department. Imagine if  we were to track the buying pattern of consumers and the usage of cards, and map it against the GDP of the country over time, with some additional variables dropped into the analysis. Predictive analytics could help and identify correlations between consumer spending and GDP and even predict the GDP into the future. After all, GDP or Gross Domestic Product is the nothing but the market value of all officially recognized final goods and services sold within a country in a year.

The advantage of the consumer cards spending data coming from the banking heavy weights in the country is a good enough sample size to be able to predict with relative accuracy the GDP Trend. Consumer spending data (as transactions) is available with the banks all the time. Mining this data for the purpose over time mapped to GDP is not rocket science, but the potential of the insight could be startling. For Starters 1) if Central bank of UAE were to get access to this data, they could track even on a daily basis the consumer spending sentiment and forecast into the future 2) Both these banks have investment arms, imagine the investment bets these banks could make in the stock market on stocks whose prices have a positive correlation with the GDP. 

UAE’s Fiscal policy think tanks may want to sit up and take note that “if you torture the data long enough, it will confess”

My USD 0.02 to end this note : Banks and governments have this rare opportunity to reinvent themselves with data analytics. Ignore the jargons IT companies throw at you like Hadoop, big data and cloud and focus on the goldmine of data you already have access to and mine them with a few smart analysts and some power tools like SAS.

Have a good weekend,

Conquering the next frontier in Investment Data Analytics/ mining

All of us in the portfolio/fund management technology world keep wondering, what’s the next technological wave which will sweep and change the tech landscape. The prime reason for this keen interest is because, there is very little innovation and change which happens in the fundamental operations of these businesses. A Fund is a Fund since the birth of the concept and a portfolio is a portfolio, and there are only so many ways in which it can be looked and analyzed, and we've got multiple systems which do it in today's times.

In the early 2000s, everyone wanted an STP front to back office operation, after a few years they wanted to move from thick client architecture to thin client architecture and by 2009-10 the buzz word was outsourced middle and back office operations (a mix of man and machine technology); so the question everyone seems to be asking is what more can technology deliver to us?

I was reading this fascinating article on “Big data” on the WSJ. It spoke about how a handful of cutting edge companies were helping firms comb through terabytes and pentabytes of data with intelligent algos to aggregate and identify hidden pockets of brilliance. I strongly believe this could potentially be a trend if harnessed properly by Fund/ portfolio management firms also.

Specific to the Middle East, and when the topic of discussion is large AUM asset managers, most of the back office operations systems have now been in place for a good decade+ in several organizations. Every year, several thousand transactions go into the back office database from the transaction side. From the CRM side, wealth management pumps into the database another few thousand disjointed demographic information points. Then there’s of historical prices, exchange rates, research notes etc which go into the system from a multitude of sources and reside unused except for the occasional historical unrealized gain loss report which is requested by the CEO or COO.

Here are a few thoughts which I could figure out from the limited reading that I did over the holiday season on self learning and programmable Algorithms.

There are several types of algos which are used by data analytics firms, and some of them could also find use in the asset management industry. There are “Anomaly detection algos” (in simple terms, a string which could be used by companies to identify “Is this investment transaction in pattern, or out of pattern; does it match typical portfolio manager/ trader behaviour, or not?”) and then there are Classification algos (Is this out-of-pattern activity fraudulent, or not?). The potentials are endless. From a no-brainer idea of trying to avoid an "Adobili scandal" , to analyzing your past data to help understand why loss making deals were done in the past , and maybe even learn from the mistakes and avoid such mistakes in the present and future. Now imagine if you could insert such a string into your pre/ post-trade analyses and they could be used by your middle office to comb through fewer transactions thereby reducing your workforce in the middle office compliance function.

Then there are “Clustering algorithms”, these could be used by asset management firms to better understand client behaviour from all the disjointed demographic information stored in the databases. Eg: What other people is this fund investor of yours most like? If you were to mix a Clustering algo with a recommendation algos (k+nearest neighbor algo) you could arrive at even better intelligent decisions like, What fund or ETF would this customer be most likely to accept!

I strongly believe this is the next big leap which all large cap asset/ fund managers would want to make. The technology systems are already out there. They are being cleverly used by firms in the retail FMCG industry,  credit card fraud management industry, automotive industry etc. It is only a matter of intelligently adapting these technologies to suit into our industry.

The fundamental building blocks to reaching this state start with having a strong back office and single book of records. Having multiple back office systems is not a major impediment (as long as you have the money to spend in integration), however a single book of records ensures that these systems can be easily slipped into place when the time is right. 

Ladies and gentlemen, This is our next frontier in the buy side space ...to borrow a phrase from Star Trek "to explore strange new worlds of (unstructured Data), to seek out new (alpha)and new (client needs), to boldly go where no man has gone before"