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Why Buy-Side Needs to Step Up to the Potential of Technology Innovation
By Ranjit Tinaikar, MD, Advisory & Investment Management, Thomson Reuters
The pendulum has clearly been swinging in favor of the buy-side (made of fund manufacturing and distribution professionals in Asset / Wealth Management firms) away from the sell-side (made of primary and secondary markets professionals in Investment Banks) since the financial crisis of 2008. As profit pools and talent shifts to thebuy-side, will it take the lead in capital markets by adopting technology innovations? Managing retirement funds and investment plans is indeed an onerous responsibility that, if done right, can make a significant difference to individuals, institutions and the overall economy. It is therefore, not surprising, that the buy-side may adopt a conservative view on innovations such as hosting portfolios on data cloud services, using social media to inform investment decisions, or joining open communities.
"A Hedge Fund following retail stocks got market signals ahead of consumer sentiment reports by tracking satellite pictures of traffic density in retail malls"However, as the pace and level of complexity in managing assets has been speeding up with new regulations, increasing difficulty in beating investor benchmarks, and increasing margin pressures—the imperative for the buy-side to take a more proactive view to adopting technology innovations is becoming ever more pressing. There are at least four themes around which the buy-side can take a more proactive approach to adopting technology innovations. Search for Alpha: ETFs are fast eating into the market share of Mutual Funds as actively managed funds find it increasingly difficult to justify their expense structures based on performance against benchmarks. The search for “alpha” is intensifying for all. As a result, fund managers will increasingly need insights beyond raw data to make their investment decisions. These insights may be derived through access to unique content sets or analytics. For example, text mining analytics that scan SEC Filings, News and Research, when combined with the power of traditional financial models can significantly improve ability to predict credit performance of a company.