Managing retirement and investment funds 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.
However, as the pace and level of complexity in managing assets have been accelerating 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.
Disruption and digital innovation
The asset management value chain is ripe for disruption due to a confluence of two drivers: The industry is consolidating into fewer at-scale players as active long-only funds lose share to exchange traded funds.
Regulatory changes around capital adequacy (Basel III), investor protection and transparency (MiFID II), Know Your Customer (KYC) and anti-money laundering (AML) requirements are adding significant costs to asset managers in terms of risk management, self-funding research, liquidity management and KYC compliance, at a time when margins are compressing.
The world of technology and data is opening up new possibilities that could help asset managers adapt to this changing environment: “New world” signals (Internet of Things, social media and Internet) can help outperform traditional sources; AI and machine learning can automate investment management activities like research and portfolio construction; and open cloud-services can transform the cost structure of asset managers.
Asset managers can leverage the power of data, analytics and technology to adapt to changing investor, regulatory and competitive dynamics in at least four ways:
- Improve fund performance by harnessing the power of “new world” signals
- Improve productivity of investment management professionals through automation
- Improve compliance with KYC requirements and reduce counterparty risks
- Manage liquidity effectively by insourcing execution management services
Improve fund performance by harnessing the power of “new world” signals: While we expect the onslaught of ETFs to continue, we believe that there will always be room for good active managers.
It comes as no surprise, therefore, that some of the largest asset managers and hedge funds (HFs) are increasing their investments in data, analytics and associated technology by 10%-20% – despite margin pressures.
These insights may be derived through access to unique content sets or analytics.
A database that not only provides details on a particular corporation but also its suppliers and distributors could significantly enhance an analyst’s ability to estimate earnings.
In one case, a hedge fund following retail stocks got market signals ahead of consumer sentiment reports by tracking satellite pictures of traffic density in retail malls!
Similarly, text-mining analytics that scan SEC filings, news, social media and research when combined with the power of traditional financial models can significantly improve ability to predict credit default of a company. The potential for adopting big data and analytics on the buy-side is immense.
Improve productivity of investment management professionals through automation: Our research suggests that 40% of a research analyst’s time is spent on assembling and organizing data – much of which can be easily automated. As margins compress, the productivity of the most critical resource on the buy-side – the investment professional – becomes even more critical.
The investment professional’s workflow is still chained to desktop solutions from the 1980s. A lot could be gained from adopting digital innovations from the consumer world: Google® on Natural Language Search, IBM on Machine Learning, Apple on Mobility and Facebook on Social Media.
A portfolio manager at a large asset manager commented that he was unable to test the full range of his ideas because it was so hard to access the data, perform the analysis and view the output.
What if all of this could be done in 30 seconds? What if you didn’t even have to remember the command to execute this – what if you could use Natural Language?
The application of search engines and interactive navigation to data analysis is immense. It could significantly improve productivity of research analysts in near-term and portfolio management in the mid- to long-term.
Watch Eikon video — Singularity
Improve compliance with KYC requirements and reduce counterparty risks: As the costs of compliance increase, industry utilities to harness the power data, analytics and technology have started emerging. Asset managers as well as banks will need to tap into the power.
The buy-side must adhere to strict regulations with compliance burdens befitting large regulated financial institutions particularly in the area of KYC due diligence.
These obligations extend to investors (retail and institutional), to trading counterparties (the dealers) as well as to beneficiaries as in the case of a pension fund.
The identification and verification of these individuals, entities and their related parties is a substantial undertaking for a buy-side firm that typically entails significant manual research effected by way of staffing up a dedicated team.
However, the opportunity to streamline this activity, leverage industry best practice and share cost efficiencies enabled by the fact that many of the counterparties of firm A are also customers or counterparties of firm B, is real and significant.
A number of firms including Thomson Reuters have set up managed services or utility models to provide such an end-to-end KYC due diligence and counterparty assessment service. Some are proven to enable 30%-50% run-rate cost savings with the added benefit of improved compliance and a near real-time view of a counterparty’s KYC, something previously unimaginable.
Manage liquidity effectively by insourcing liquidity management services
Traditionally, the buy-side relied on sell-side trading algorithms and execution management systems (EMS) to access liquidity.
As the sell-side is playing a lesser role on market making, buy-side firms will increasingly need to become adept at managing the liquidity constraints.
Therefore, we will see an increased use of trading algorithm development and EMS by the buy-side.
The sell-side has led many of the technology innovations in capital markets ranging from trading algorithms, industry connectivity solutions and low latency platforms. The time may just be right for buy-side technology to step up.