The finance industry is going through a period of profound change and disruption.
Technology provides the means for firms to re-imagine the way in which they operate and interact with their customers, suppliers, and employees. One particularly significant area of development is the utilization of artificial intelligence (AI) and machine learning (ML).
The pace of AI application is clearly accelerating as companies begin to leverage it to increase efficiency and innovation to gain a competitive advantage in the marketplace.
Financial services organisations have a long history of working with data, for example using analytics to extract insights for creating better, more profitable business models, investment strategies and improving the customer experience.
The challenge lies in organising and managing this data, verifying its accuracy and capitalising on the opportunities it provides.
AI can enable regulatory compliance, improve business performance, drive cost-savings and efficiencies, rapidly analyse and spot trends, create new value propositions and promote quicker decision making. This creates a cycle of innovation across a wide range of business functions and a re imagined customer experience.
AI relies on quality data being input, as well as the interpretation of that data. Firms are not quite ready to let the machines do everything and skilled human intervention is still required.
AI will be key in how the financial industry operates and delivers services, and for it to compete and thrive. According to consulting firm Accenture, the contribution of AI and augmented technologies to the bottom line for financial services companies around the world is estimated at $140 billion in productivity gains and cost savings by 2025.
Algorithmic trading has long been a primary user of it, but there are several other areas within the finance sphere where AI is rapidly beeing adopted .
Transforming the deal process
For deal professionals, AI is not just an exciting source of new transaction flow. It can now be applied to every part of the deal process, from tracking and sourcing deals through to due diligence, execution, portfolio-, and risk-management and post-deal integration.
AI-powered deal-flow search engines can help executives improve the effectiveness and efficiency of the deal process. They automate tasks, smooth workflows, and scrutinize company data and information- completing processes that would take months of an analyst’s time in minutes. Deal-flow platforms can visually chart and track balance sheets, profit and loss, creditors, debtors, debt, shareholders, connections, contacts and introductions. This enables deal makers to identify and assess targets, inform decision making and accelerate execution.
AI-powered deal-flow search engines deliver actionable insights and trends even as underlying conditions change and develop.
Our journey in AI
A visit to Google HQ in Denmark where they presented their take on AI in the project AlphaGO from deepmind.com – relying heavily on AI, lets us to believe it was time to revisit AI.
In SoftCapital we first started to work with AI in 2001, just investigating a new technology and whether we could benefit from this in our software. At that time we were doing systems for market making of derivatives, and here speed was and is of the absolute essence. So we decided that AI was this was not for us due to calculation and speed considerations, but technology and lesson learned.
In 2016 SoftCapital has evolved to be more portfolio and Risk-management oriented. In the periode computer calculations has incrreased exponentially and we decided to give AI another try in portfolio management and transaction fee management.
Now we are ready to release “Optimizer” in late 2020 in where we utilize AI in 2 major areas.
Currently a stringent due diligence process is taking place to verify the results we are getting.
In the next blog we will be getting into details with the areas we have implemented AI,