Customers of the investment management firm have expressed a desire to preserve and increase the value of their assets, but prefer to entrust the task of investing to a professional contractor rather than managing it themselves. The company handles a variety of assets, such as currency, real estate, business shares, precious metals, stocks, and securities.
The management company operates on an agency network principle. Key business processes involve managing document flow and obtaining signatures and approvals from three parties: managers of RusCapital, agents of the management company, and end clients. It is essential to constantly monitor transactions made by authorized agents of the client and to track various indicators related to deals and client relations, including
- The amount of the agent’s commission received;
- Future income of the agent from the attracted client;
- The specific partner or region that the client is attached to;
- Investment dynamics of each asset;
- Current form and condition of each asset;
- Indicators of expected client profit for the quarter and year;
- The fact of profit accrual for each asset;
- Statistics of clients and their dividends across different funds;
- Terms and conditions of contracts with customers;
- And other metrics.
Interaction and document flow between agents, RusCapital employees, and end clients was conducted through traditional offline processes involving manual work by secretaries. All documents were filled out manually using Excel spreadsheets, paper documents, and handwritten signatures for each approval.
Fund clients had no means to monitor their assets and related transactions in real time, and each action with their assets had to go through a manager’s approval. All metrics were calculated manually by the company’s employees without any automation. Reports were also generated using manual methods. Human factors played a significant role in the company’s system-critical business processes.
The company aimed to rectify the complete lack of automation by implementing a popular CRM system. However, the CRM system was not customized and was only superficially configured. It did not fully cover the company’s business processes, nor did it help to increase the speed and efficiency of RusCapital’s operations.
Standardization of service levels when working with RusCapital clients was absent. Process speed varied significantly due to the dependence on the work of specific employees and the extensive geography of partners located in different locations around the world. A centralized remote working tool was also absent.
In addition, the management company required the implementation of a predictive model to help calculate expected compensation for future deals. Such a system based on mathematical models and Big Data algorithms would provide an effective solution to streamline the company’s operations and help to achieve its business goals.