Liquidity has become a precious commodity in fixed-income markets since the global financial crisis. Post-crisis regulations have made broker-dealers reluctant to warehouse large risks on their books, which in turn has made it more difficult for insurers and other institutional investors to trade large blocks of bonds quickly and efficiently.
The best bond managers have always had to find the right investment strategy and the right specific trades to fulfill that strategy, but now they have a third job. No longer able to easily dip into the market pool for what they need, managers must develop or buy smart technology to rapidly aggregate any available drops of liquidity before they dry up.
The Problem with a Parched Market
Insurers are often in a position that requires them to invest large sums of money quickly. Before 2008, broker-dealers routinely accommodated such needs. But the post-crisis ban on proprietary trading along with stricter capital requirements have made banks and other market makers less willing to take the other side of a trade when no one else will. It simply isn’t worthwhile for them to hold bonds—particularly those that don’t trade frequently, such as credit, high-yield bonds and emerging-market debt—on their books until a buyer comes along.
With broker-dealers playing a diminished role in the markets, traders must monitor dozens of trading venues, looking for ways to execute large trades. In illiquid markets, however, opportunities are often fleeting, and monitoring so many information feeds makes it easy to miss them.
Cobbling together an order of sufficient size can also take a great deal of time, during which asset prices can easily move out from under an investor’s feet. Not to mention the fact that most investments that asset managers make on an insurer’s behalf will have a guarantee or liability match, and even just a few days’ delay with capital sitting on the sidelines can cause an unwelcome gap.
Technology Is Helping to Solve Illiquidity Challenges
New digital tools are helping asset managers and the insurers for whom they invest achieve better outcomes in an illiquid world, while also reshaping the investment process for the better.
Traders and portfolio managers now have more efficient ways to keep track of fragmented sources of liquidity and an overwhelming number of information feeds from multiple sources. Software that aggregates pockets of existing market data into a single user interface makes it easier for investment teams to see a big-picture, real-time view of availability and pricing at any given moment. That, in turn, ensures that they miss fewer opportunities to execute the trades that their clients need at the price they desire, even if liquidity is fleeting.
Investment teams are also speeding up and improving the investment process by digitizing, standardizing and centralizing their fundamental credit research. Fundamental research is qualitative in nature, which implies subjectivity. Scoring bonds on multiple factors using a standard, numerical scale and then aggregating those judgments into one overall score, however, puts objectivity back in the equation. It allows analysts, portfolio managers, traders and anyone on the investment team to instantly compare bonds in different industries and regions.
Without such a system, portfolio managers and analysts can spend hours or even days going back and forth about investment decisions. And when markets seize up unexpectedly—something they do increasingly often in the absence of large market makers—even minutes can be precious.
Smart Machines Make Investment Teams Faster and Smarter
Digitization is only the first step, however. Asset managers are building artificial intelligences (AIs) that are capable of reading and interpreting digital information about liquidity and fundamental research. For now, asset managers are using this software to automate tedious, mundane tasks, such as building trade orders. But the intelligent thing about AI is that with a steady diet of digital data, it can learn. Already, some fixed-income investment AIs can whittle the thousands of bonds in circulation down to a few that meet the specific parameters investment teams specify.
Speed is the first way insurers benefit from that. An insurer with $500 million to invest in a credit portfolio would need to purchase between 100 and 200 bonds. In a traditional investment process, this would entail hours—or even days—of discussions between portfolio managers and analysts about the best bonds to buy, and as many as 200 phone calls to check the availability of potential investments. Using digital tools that communicate with one another, that $500 million could all be invested in a single day—reducing the odds of a major price move.
In the future, AIs will learn to proactively monitor markets and suggest opportunities on their own. Since software doesn’t have to sleep, eat or answer email, the chances of missing a trade that suddenly becomes available drops dramatically, putting insurers at an advantage when illiquidity threatens their strategies. With the capacity to crunch enormous amounts of data in fractions of a second, smart machines may very well start to see opportunities and patterns that humans cannot.
Human decision-makers will always set strategy and make final investment decisions, but machines will unquestionably become a valuable complement to human investment teams sooner rather than later.
Beyond Liquidity
Above and beyond providing the kind of speed and efficiency that can serve as a buffer against illiquid markets, software that can analyze and learn gives insurers even more of an edge. Freed from exhaustively debating fundamental research, making phone calls to source bonds, or typing in trade orders by hand, asset managers can spend their time on activities that create far more value—activities only humans can do. Those include looking for unique data sources that the competition doesn’t have, interviewing management teams and government officials with insight into individual issues, testing more novel hypotheses and discussing strategy with clients.
The marriage of man and machine isn’t something insurers should fear—rather, it’s something they must ensure their asset managers are trying to achieve.