ING is continuing to improve decision-making in bond trading.
Co-created with Dutch pension fund PGGM, Katana Lens is a web-based application that uses predictive analytics to help bond investors make faster and sharper decisions within minutes.
“What used to take forever, now only takes five minutes and a cup of coffee,” said Santiago Braje, global head of Credit Trading, who announced Katana Lens today at the Artificial Intelligence Summit.
Science over assumptions
Investors have millions of trading ideas to choose from. To narrow down their options, they often resort to making assumptions – a time-consuming activity that can lead to missed opportunities.
Based on a web application, Katana Lens uses an algorithm that learns from the history of hundreds of thousands of trades and identifies the most promising ones. By going through all the pairs of bonds and taking each ‘buy’ and ‘sell’ combination as a possible investment, it simplifies the selection process for investors, who are presented with a prediction or suggested decision.
Katana Lens follows up on last year’s launch of Katana, which was created to help traders decide what price to quote when buying and selling bonds for their clients based on historic and real-time data. While Katana is a tool to improve pricing as well as the speed of the traders’ response on the sell-side (banks) within the bond market, Katana Lens was developed for the buy-side (investors).
“When we realised the impact Katana could have, we decided to also help our clients in investment management make better decisions,” said Androniki Menelaou, data science lead at the Wholesale Banking Advanced Analytics team, who also covered Katana Lens in a keynote at the AI summit.
Katana is the result of intensive research and development by ING’s Financial Markets Global Credit Trading team in London and the Wholesale Banking Advanced Analytics team. The first results of testing Katana with the emerging markets (EM) desk in London show faster pricing decisions for 90% of trades; reduction in trading cost by 25%; and traders are able to offer clients the best price four times more frequently.