ING Makes AI Bond-Trading Tool Independent
ING is separating Katana and new funding will expand the artificial intelligence tool which was developed by the Dutch bank to helps investors make quicker decisions on which bonds to buy and sell.
The Dutch bank originally developed Katana to help its traders provide liquidity and respond more quickly to requests for quotes from clients. In 2018 ING launched Katana Lens for the buyside after developing the offering with PGGM, one of the largest pension fund managers in the Netherlands. ING said other asset managers have also been using the tool and providing feedback and market validation.
Santiago Braje, former head of credit trading at ING and chief executive of Katana, told Markets Media: “Katana will be independent of ING’s trading activity which will avoid conflicts of interest and we will be able to access data across the whole market.”
Katana Lens systematically scans a universe of investable bonds chosen by the fund manager and identifies possible opportunities based on the current yield or spread against historical behaviour for similar underlying risks over the past six to 12 months. Clients can see profitable opportunities they might have otherwise missed, make decisions more quickly and trade smaller tickets more frequently.
Katana Labs ltd has incorporated in the UK as part of the spin off with ING Ventures investing a further £1.5m ($1.9m) alongside other investors, as part of a £3m funding round.
— ING (@ING_news) January 7, 2020
Katana presents trading ideas but is not linked to execution.
“Our roadmap includes linking to execution so the so buy side has an integrated solution, and adding liquidity intelligence features,” said Braje.
He continued that the new funding will also be used to expand the firm’s team and its bond coverage. Katana currently focuses on emerging markets, global credit and European investment grade bonds.
Braje added: “In a year’s time we aim to have expanded product coverage, liquidity intelligence and and linked to execution. We should also be ready to start expanding globally.”
Fixed income automation
Meaningful automation is coming to fixed income according to the Top 10 Market Structure Trends for 2020 from Greenwich Associates.
— Greenwich Associates (@GreenwichAssoc) January 6, 2020
The consultancy said absolute volume traded through electronic channels across request-for-quote, order book and streaming increased by over $2bn (€1.8bn) a day in US corporate bond markets last year and investors began widely adopting automated trading tools.
“Furthermore, electronification of processes on the trading desk other than the execution itself—salespeople deciding whom to call, more efficient capital allocation, etc.— will happen more quickly and have a greater impact on the market’s functioning going forward,” added Greenwich.
Katana is one of the 25 different innovation initiatives currently in one of the ING Labs in Amsterdam, London and Singapore. It is the latest start-up originated by ING that enters the scale-up phase, following other projects such as Yolt, a mobile app to help people keep track of their finances, and Cobase, which allows multinationals access their accounts across banks and financial institutions.
Annerie Vreugdenhil, chief innovation officer at ING Wholesale Banking, said in a statement that Katana has grown from an internal innovation project to a serious value proposition for bond investors.
“We attracted major clients who see the added value of this super smart AI-tool,” she added. “I’m proud that with our support Katana grew out to a fully-grown fintech that is ready for an independent future. A future that I’m sure will be very successful.”
The bank can access data science, artificial intelligence and machine learning for new products.
AiPEX with Watson simulates a team of analysts and traders to identify potential investments.
Machine learning models systematically scan newly arriving, anonymized data to identify anomalies.
The Cobalt programme launched in 2018 to help fintechs collaborate with the asset manager.
Users with different skill levels will be able to undertake machine learning and advanced analytics.