Columnists

Big data use next big thing for stock marts

data

Research by McKinsey & Co has found out that companies that make smart use of their big data also enjoy higher revenues. FILE PHOTO | NMG

Football transfer season is here and one Belgian Striker is the talk of the town. Romelu Lukaku is set to make a switch to Manchester United from Everton for a potentially world record $115 million – snubbing my favourite club (Chelsea) in the process. What a terrible mistake!

Anyway, the whole circus reminded me of an old movie, “MoneyBall”, in which an underfunded B-rate team goes on to win the 2002 baseball championship by beating a well-funded team with the “best fans and the best stadium”. In fact, the team wins 19 consecutive games, tying for the longest winning streak in American League history.

Their secret: assembling undervalued talent using players’ data. Arguably, thanks to Oakland A’s, big data is now a buzzword in sports and business. Sadly big data, or extremely large data sets, has yet to firmly find its way in our capital markets. But here’s how we can catalyse this revolution.  

For stock brokers, the shift to mobile and Internet-based trading is a superb door-opener but more can be done. Information—cash deposits and balances, trade executions, investor holding patterns, pending bids and so on—collated from these platforms, presents a big data opportunity.

Not only can this treasure provide deep client insight, but can be harnessed to achieve several goals. These may include finding ways to differentiate themselves, improving client sales and retention, detecting fraud, tailoring targeted-client advice and reducing client attrition. A push for this evolution could see brokers improve operations, increase margins and better serve its customers. And evidence supports this; a survey by McKinsey & Co has found out that companies that make smart use of their big data also enjoy higher revenues.

For research analysts, a crash course in big data may now be necessary. Besides company filings and price-to-earnings ratios, researchers may now need to learn how to interpret big data in order to corroborate information from their usual sources. Furthermore, with the new broker platforms accumulating data, it’s certain that in the future, brokers will only hire analysts with some data analytical skills to solve their big data puzzles.

For this, a skill set on the usage of data sets and quantitative techniques may soon become an added advantage for new hires. Other groups that need to jump on this trend include investment managers, investment banks, advisors and the exchange.

That said, challenges abound. A lot of big data is useless and even the good stuff needs to be laboriously cleaned of erroneous information. Its true huge data does not mean quality data. Therefore, industry players will have to filter out these useless information otherwise they will end up making wrong decisions. Perhaps as a remedy, they may need to focus not on how much data they accumulate but on how they can slice and dice the same.

In all, big data revolution is inevitable. Through it, much vitality could be injected into Kenya’s capital markets to help accelerate its growth.

Mr Mwanyasi is MD, Canaan Capital Limited