Governments legislate reforms in order to increase transparency in financial operations and deal with fraud issues. In recent years, new regulations have been enacted that bind financial institutions to exert greater analysis and control over their activities, both in the United States and in Europe (main financial centers worldwide).
- Dodd-Frank – consumer protection and financial reform endorsed by President Barack Obama on July, 11th 2010. The objectives of the reform are the following:
- Reinforcing investor protection: liability, consistency and transparency.
- Systemic risk: strong supervision and regulation of financial firms.
- Global supervision of financial markets: securitization, derivatives and credit rating agencies.
- Increase of international regulatory standards and improvement of international cooperation.
- Emir – the Bylaw 648/2012 of the European Parliament and of the Council on OTC Derivatives, Central Counterparties (CCPs) and records of transactions entered into force on August, 16th 2012.
- MiFID II – In October 2011, the European Commission presented this Directive to review the financial instruments in the markets in order to make financial markets more transparent and efficient and to increase investor protection.
These new regulations compel investment banks to have greater control over the transactions they perform and have a record of all the communications involved in the negotiations.
The volume of communications generated is quite large; a bank with a volume of 1,000 traders might generate 40,000,000 communications (phone calls, emails…) a year.
It is necessary to have a solution that allows analyzing the content of all communications (both audio and text) in order to be able to perform:
- Transactions Analysis.
- Transactions Reconstruction.
- Proactive prevention of fraud and risk control
New product description
The product provides the user with a solution for the analysis of their trading environment. It will allow the user to carry out an internal control of bad and good business practices. And it also gives the user the capacity to respond the regulators requests.
This is achieved by providing them with the adequate tool to analyze the communications generated in a trading desk environment (phone calls, emails, chats, text message…) and to link to the transactions (hereinafter referred to as trades) that the aforementioned desk executes. The product will also solve the following use cases:
- Linking trades to communications: linking two environments currently separated; the transactions executed and the communications exchanged to carry out those transactions. This automatic linking (Automatic Trade Reconstruction, ATR) has not been achieved by any other company in the market. To offer this solution the following is needed:
- Implement algorithms that allow crossing the information obtained from the communications with the transactions, offering an automatic match with probabilities. These algorithms are highly complex and the more operations they analyze the more they are “trained”.
- Interface for managing the obtained information.
- Communications search: it allows to search communications through their content and their associated information (date, participants…). To do this, the challenge will be:
- Voice recognition engine that provides the system with sufficient levels of precision to successfully analyze the contents of the calls.
- Text analysis engine that allows the system to successfully analyze the contents of text documents (emails, chats, text messages).
- Classifications engines that allows the system to structure the information of communications. At this point and using the information detected by the analysis engines, the classifications engines based on logical rules and engines based on automatic classification (machine learning) will be implemented.
- Information and communications storage system that derives from the performed analysis combining: speed and capacity to store large volumes of data. Considering the nature of such a system (large volumes and combination of structured and unstructured information), the data should be stored in a Big Data environment.
- Interface that allows the user to combine power and simplicity in order to perform the searches.
- Proactive monitoring, automatic alarm creation and creation/management of open cases.
- “Behavior” analysis by applying complex behavioral algorithms in a trading desk environment, creating alerts that allow the internal control units of the financial institution to prevent risks and fraud.
- A system that allows the user to create, escalate, maintain, close and manage cases.
- Interface for the analysis of the obtained data.