Linedata is delighted to announce the completion of a technology project around Machine Learning within Linedata Optima, our fund services BPM platform. This is a further step in our ongoing mission to deliver measurable efficiencies to our clients. The new models our teams have developed present our clients with suggestions to further tune their workflows and operating models.
The two driving forces behind this update are:
- The cut down on the time taken to get exceptions to the most qualified user for resolution. The model examines the historical assignment and resolution patterns within the database and suggests automatic assignment rules, with a defined level of confidence, to managers.
- The teams were conscious of avoiding the display of false or premature exceptions to users. The model examines the data and notes scenarios where exceptions are initially raised but are automatically closed later in the day as data changes in the underlying application. To cut down on this ‘noise’ and focus users’ attention on exceptions that genuinely need further analysis, suggestions are made to managers, again with a confidence level, on when the processes that generate the exception should start.