Mosaic Smart Data is using machine learning and artificial intelligence to spot potential opportunities in capital markets as well as providing real-time data analytics on trades.

The firm is launching MSX360, which uses machine learning to provide personalized recommendations on what is happening in the markets and what action traders should take to seize the opportunity.

Matthew Hodgson, chief executive and founder of Mosaic Smart Data, told Markets Media:“Mosaic Smart Data is like a refinery that takes raw coal and produces jet fuel through normalizing and harmonizing data.”

Hodgson launched the fintech after his experience in previous roles at Deutsche Bank and Solomon Brothers, where he found it impossible to get a consolidated view of data on all trades with one client across all products. MSX, Mosaic’s platform, can generate these analytics in real time in fixed income, currencies and commodities.

The new service, MSX360, uses the same data but provides recommendations on future action.

“MSX360 allows firms to move from defending their share to becoming offensive through optimizing their use of resources,” added Hodgson.

Early adopters of MSX360 have improved outgoing sales call volumes, call times and volumes seen by more than 20% according to the firm. “Every bank knows what an increase of 1% of revenue means to their bottom line,” said Hodgson.

He explained that MSX360 allows clients to see patterns of client behaviour which could be seasonal, monthly or weekly. This allows a bank to predict the best time of day for a trade and the most suitable instrument to use. The model learns from individual users’ activity and interests over time to constantly improve recommendations.

“For example, MSX360 can provide alerts for the rollover of an FX swap so firms can call a client in advance,” he added. “The aim is to surprise and delight clients.”

Clients can add their own intellectual property on top of MSX360 or use Mosaic’s models. Hodgson compared MSX360 to Netflix, which streams film and TV series and make recommendations based on your viewing habits.

“Today, the idea of walking into a video shop and trawling through shelves feels completely antiquated,” he added. “We’re used to a service like Netflix doing the legwork for us and suggesting options we will want to watch from a database of thousands.”

Mosaic Smart Data has launched the first real-time guided analytics for capital market performance, MSX360®.

MSX360® uses machine learning and AI to answer all the essential questions traders need answered. pic.twitter.com/ZbvJxjoV6k

— Mosaic Smart Data (@MosaicSmartData) February 2, 2021

The pandemic and the shift to remote working has led to an acceleration of digital transformation across financial services.

“The buy side was more reluctant to spend on digital transformation but have now seen that it is essential,” said Hodgson. “The industry is realising the value of monetising large bodies of data including across exchanges, vendors and CCPs.”

Technology trends

One of the technology trends that Nasdaq highlighted in its latest annual report is edge cloud which reduces reliance on centralized processing.

Brad Peterson, chief technology & information officer snd Lars Ottersgård, head of market technology, said in the report: “In the financial services industry, edge cloud can support workflows designed to evolve customer engagement models and provide deeper insights from data, as well as enable hybrid cloud strategies.”

The 2021 @NasdaqTech Trends Report highlights technologies and recent innovations industry-wide. The combination of cloud, federated learning, and homomorphic encryption can securely reduce barriers to sharing and analyzing data.

Read more: https://t.co/SF3XEq0rxX pic.twitter.com/meHyL4FaBb

— Nasdaq (@Nasdaq) January 31, 2021

They continued that marketplaces and financial firms can create a special purpose or customized cloud that is aimed at addressing the needs of certain workflows.

“Investment managers can use low-latency edge computing to make predictions with machine learning models trained in the public cloud using alternative datasets such as satellite imagery showing crop yields, oil reserves and retail parking lot usage,” said the report. “This allows them to gain insight into the macro economy, as well as specific sectors and companies. New, emerging marketplaces could leverage edge cloud to run their matching engines as well. The list goes on.”

Other important trends are the acceleration adoption of the software-as-a-service model (SaaS) and the combination of cloud, federated learning and homomorphic encryption.

“With federated learning, organizations can share insights without actually sharing data,” said the report. “Moreover, homomorphic encryption is emerging as a technology that can allow organizations to share data, retain complete control over who can access or perform analysis on that data, and own auditability of that process.”