Overview
Calastone uses smart technology solutions and industry collaboration to enable global distribution, reduce operational risk and enhance client profitability.

There are a range of products across the investment lifecycle designed to meet both short-term market needs and long-term transaction requirements. Solutions encompass Transaction Services, Data Services and Connectivity/Infrastructure Services.

History
Calastone was established in March 2007 by three individuals, Philip Goffin, Kevin Lee and Ian Taylor who all have worked in the fund management industry. The founders saw that Fund Managers would typically use phone and fax systems to execute trades and transactions across borders. Associated with these transactions were a number of tasks, which would be manually completed, for example documenting and recording transactions. The founders recognized that an electronic transaction network that could handle and interpret instructions would improve efficiency for fund managers, distributors and transfer agents. In 2012, 90% of UK-based fund managers are connected through Calastone, and by 2014, the connection rate reached 99%. In 2016, Calastone has over 980 global customers in 28 countries and territories.

Customers
Calastone’s customers are mainly organizations that want to trade funds. These groups could be mutual fund providers, distributors and third party administrators / transfer agents within the funds industry. In particular, the fund providers include large companies like Schroders and JP Morgan Asset Management who would execute large numbers of international trades and transactions on daily basis.

Learn more about the Product Business Model

A dyadic transactional relationship where your good or service can be designed and delivered without prior interactions with the customer.

Engagement  — Value Creation Proposition
Calastone’s network is standardized and designed to be used at scale. So it is a bus-style value proposition. However, Calastone works with customers to tailor parts of the system to better meet overall fund industry needs.

The core value proposition to customers is access to a secure system, which will automate the processing of transactions, thus reducing administrative effort and costs. Users can also access trade data and fund price information, which can then be used for reporting.

A network effect exists here, as more organizations are connected to the network, the value of the network increases and the company attracts more organizations who want to trade with the already connected organizations.

Delivery — Value Chain
New customers are first put through a testing process to identify any connectivity issues before launching the system. Users are then given system training by Calastone and receive a username and password to access the portal. Customers do not need to acquire further technology or infrastructure to use the system.

Once customers of EMS are connected and when they want to place trade orders they can simply log into the Calastone portal to send an instruction using whatever message format they want, as Calastone supports more than 180 different language formats. Calastone’s system then translates order instructions into the ISO 20022 format, making it possible to automate transactions throughout the trading lifecycle. Users can then use the portal to track the status of transactions, for example to see when orders are received and confirmed.

Calastone’s Settlements product matches instructions and aggregates into a net position between counterparties, which both parties confirm in advance allowing for early morning settlement on a single payment. This approach solves two key issues; 1. matching of individual transactions per fund per distributor, and 2. timely payment on settlement date.

Monetisation — Value Capture
Calastone signs up customers to their network for free, there are no initial set-up fees, development or annual charges. Instead Calastone charges per transaction based on volumes traded. This could be from £1.50 – £2.70 per trade.

Digital Technology
Checkout claims to use machine-learning as the technology to monitor and control how merchants authorize, void or decline payments. So that checkout could find an optimal balance between fraud and approval rate. Card information is protected via tokenization technology.

Disclaimer — Written by Nushma Malik and revised by Tong Guan under the direction of Prof Charles Baden-Fuller, Cass Business School. This case is designed to illustrate a business model category. It leverages public sources and is written to further management understanding, and it is not meant to suggest individuals made either correct or incorrect decisions. The information contained here should not be used for investment advice and is simply indicates the individual’s understanding of the company’s business models as of February 2020. © 2020 This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.