John Norris, COO
Capital Markets advisory businesses heavily rely on human interactions between buy-side and sell-side firms regarding research-related services. However, buy-side firms have invested very little in technology around their sell-side provider interaction value. Historically, clients used systems such as Microsoft Excel to capture information or relied on third party aggregators to provide sell-side CRM generated datasets making it difficult to do any meaningful analysis. Regulation changes in across Europe, coupled with continued cost pressures across the industry globally, has amplified the need for a more systematic approach one which does not merely offer a series of quantitative bar charts but can output recommendations on the value of suggested payment for sell-side relationships.
Many technology vendors have developed interaction capture systems – taking interaction extracts from sell-side providers, consolidating them to a single source – to facilitate buy-side voting for years. However, very few look at the data interpretation – once you have captured the data, what does it show? Little do they help with analytics to understand behavioural factors. This leads to the vital question of how much buy-side firms should pay sell-side providers and how accurate is this payment vs. the quality of the services provided.
Serving the market since 2016, Quintain Analytics (QA) provides extensive data analytics to enable buyside firms to understand the value of what they consume from the sell-side and ultimately determine how much it is worth. The company’s technology platform is based on award-winning behavioural analytics, which brings to life the true value of research related interactions translating them into how much a buy-side firm should be paying their sell-side providers.
QA helps buyside firms understand the true value of their sell-side providers instead of relying on highly subjective data sets that often distort the payment picture for advisory services. “We focus on interpretation to help clients understand their value recognition and the impact of behaviours across both buy and sell side,” says John Norris, COO, QA.
QA’s products are designed to cater to clients of all sizes and complexities, ranging from a handful of investment professionals to global multi-market asset managers. The company’s core DNA is data analytics and has designed its software and analytical engine to leverage a range of inputs from client-owned data, third-party aggregators, and its primary capture tool. The analytic outputs are displayed through a sophisticated yet user-centric design to facilitate easy interpretation of essential data. “We believe in data centricity around each type of investment professional, not a one size fits all view of data,” says Norris.
QA’s products and solutions aim to extract the relevant information from the industry big data to provide operational alpha for buy-side firms to help manage interaction related costs. “The power is in the data, and what QA has built (and is constantly evolving), is the ability to shine a light on the data that matters allowing it to feed into the decision-making process,” mentions Norris.
QA is also tackling one of the previously difficult to quantify but significant driver of provider value identifying the correlation between the use of research services and impact on portfolio positions. “The industry has long been searching for a way to identify providers who are accretive to idea generation as the current tools available have very small data factors to substantiate meaningful analysis. Overlaying portfolio position alpha accretion with other qualitative elements will give firms a very clear picture of true value,” says Norris.
QA believes in helping determine what is valuable to every client, producing relevant results, and aligning with their methodology. All of the company’s products are designed to use a diverse range of source data and showcase it in a way that is designed for the individual investment professional.