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Forestpin Co-Founder and Director Dilanke Hettiaratchi (left) and Co-Founder and Managing Director Ransith Fernando
Each year, the APAC CIO Outlook Magazine publishes a list of top Big Data Analytics companies originating from the Asia Pacific Region. The 2018 list published in November includes the following companies given in alphabetical order, CADS (Malaysia), DATAVLT (Singapore), Forestpin (Sri Lanka), GRIDSUM (China), HYPERS (China), OneAD (Taiwan),% (China), Tech Valley (China), Vpon (Taiwan), WINNER Technology (China).
The APAC CIO Outlook is a magazine published from the technology hub of Silicon Valley, USA, with sales offices in Hong Kong and editorial presence in all major APAC countries. The APAC CIO Outlook Magazine aims to provide a platform for CIOs, CTOs, and other senior level IT buyers and decision makers, along with CXOs of solution providers, to share their experiences, wisdom and advice with the enterprise IT community of APAC countries. They also identify and profile emerging companies providing cutting edge solutions to enterprises in APAC.
“We are delighted to be recognised in this prestigious list of Big Data Analytics software, which include very large companies from the region. I believe it’s due to the uniqueness of the value proposition of our solution,” said Forestpin co-founder and director Dilanke Hettiaratchi. “We need to thank all of the progressive companies in Sri Lanka that were early adopters of Forestpin Analytics and Risk Alerts, and who have supported us along the way. Some of these companies already had the best of breed analytic solutions, yet saw the potential of timely visibility of risk, which has helped them towards mitigation of financial loss,” says Forestpin co-founder and managing director Ransith Fernando.
Forestpin is a Sri Lankan company that helps companies reduce operational risk in transactions, by giving analytics and alerts on suspicious transactions.
Forestpin’s Risk Engine works as a part of the enterprise system in the background, where data is extracted on a predefined basis, and a series of anomaly detection computations are run, resulting in a risk score on each and every transaction. The engine also computes a dynamic threshold based on the alerts sent in the last 30 days, and the number of alerts a user can consume per day on average, where the transactions above the threshold are alerted either in digest form or individual alerts. The engine’s dynamic workflow with authorisation levels permits users to comment or change statuses based on their roles. The updated statuses are used by the learning mechanism to identify the risk factor to the business. If an alert is marked as not useful, then the Risk Engine will stop highlighting that type of risk over time. If an alert is marked as keep alerting, human error, process improvement, or found manipulation, then the learning mechanism increases priority for the type of alerts. Interaction on the alerts is also captured for our enterprise customers on Forestpin analytics to ensure businesses are attending and investigating their alerts.
With Forestpin’s sophisticated tools, customers have changed about 0.7% of transaction values based on alerts, which is a significant value for an enterprise. The results can be calculated by using the alerted and changed statuses making the ROI very clear and measurable.
As a self-service forensic data analytics tool, Forestpin Analytics allows clients to very quickly analyse their data with simple visualisations of complex mathematical and statistical tests. The user can simply upload data or access a server connection, configure the default dashboard as required and Forestpin’s tool provides the desired outcome. The company provides highly flexible dashboards to users where data can be easily fed through copy and paste or uploading data. In addition, the platform offers a field for verifying the data and generates a default dashboard to kick-start the analysis. The dashboard is completely configurable where a user can move analyses, decide on what he/she wants to see, make some analyses larger, add or remove analyses based on our predefined list of analyses and have multiple dashboards. Once the user is happy with the dashboard, the entire configuration can be saved. This allows reusing the dashboard on a future date with more data or for sharing the dashboard with another user. For the enterprise customers, data automatically flows into the server, and a default dashboard is given, which once again is completely editable by the end user, and all configuration is local to the user and can be saved. Once the data is fed, the data analytics tool provides many tests such as time series, correlation, relative time factor, first two digit tests, duplicates, composition, quadrant and stratification which highlight areas of risk or opportunity. In addition, clients can also benefit from BI tests such as the group, ageing, distribution, and box view. These provide for summarised information with data mining capability.
Forestpin was an early adopter of machine learning. Towards the end of 2016, it incorporated a learning mechanism to its core product and tested it out with some of its customers. By 2017, it was implemented across all of the customers.
The company is constantly investing on research on machine learning and algorithms to improve its product. It is also planning to offer services on bespoke machine learning in the future.