Linedata Integrates AI and Prescriptive Analytics Into Its Solutions to Inform Clients’ Decisions

Linedata a global provider of asset management and credit technology, data and services, announced it has developed two artificial intelligence modules aimed at supporting clients in their decision-making and enhancing productivity in the follow-up of client cases. The new Digital Assistant and Sales Advisor modules, already used by Linedata’s clients from London to Toronto, are now available for the Linedata Ekip³⁶⁰ solution and can also be deployed on further Lending & Leasing solutions.

Khalid Dbich, Deputy CEO of SOFAC, a Moroccan company specializing in credit solutions, said: “Contrary to common belief, the financing offer with the best chance of success is not necessarily the one with the lowest monthly payment. It was important for us, at SOFAC, to master all the upstream information in order to provide the best advice, suggest the most suitable financing offers and, ultimately, remain competitive. Linedata’s Sales Advisor prescriptive analytics module provided a real answer to our needs. We immediately looked forward to participating in this promising project, which focuses on the concrete and tangible contributions of artificial intelligence to resolving business issues.”

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Digital Assistant, an AI-powered assistant to benefit from peer expertise

The artificial intelligence that makes up Linedata’s Digital Assistant suggests actions to a case manager, based on the choices previously made by other users on the same type of case. The assistant thus generates the equivalent of a business workflow without requiring any complex configuration.

Linedata’s Digital Assistant is particularly useful as:

• It avoids navigating across a number of submenus in order to select the appropriate option.
• It simplifies the takeover of an ongoing case by an employee who is not very familiar with it by immediately indicating its current status and the next actions to be taken.
• It acts as a virtual mentor to pass the essential know-how of more experienced colleagues to newcomers, who benefit from reliable suggestions for tasks to be performed.

Digital Assistant is based on a LSTM (Long Short Term Memory) recurrent neural network that takes into account the current screen and the sequence of actions that led to it in order to make the prediction. Digital Assistant exploits all the traceability data provided by the solution, makes them more reliable and enriches them with new concepts relating to accounting or financial processing.

Sales Advisor, to guide financing advisors

Linedata’s Sales Advisor module aims to transform the user experience of financing advisors by guiding them towards the offer to be put forward based on the probability of the transaction being validated.

In concrete terms, the tool performs analyses based on anonymized data about the buyer, the property to be financed or even the financing organization

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“In business intelligence, prescriptive analytics helps make decisions by identifying the best choices among the various options available and within known limits. We have chosen this approach and developed two modules to be integrated into our software offering. This will allow our clients to make more informed decisions while maintaining a high level of productivity and efficiency,” explained Alain Mattei, Head of Lending & Leasing at Linedata.

Linedata designed Sales Advisor to help its clients optimize their business processes around three main use cases:

• Improving the close rate of sales proposals by determining the most appropriate funding schedules
• Helping sell additional services (insurance, maintenance, etc.)
• Identifying loyal customers (future renewals) as early as possible in the setup process

To create the Sales Advisor module, Linedata’s experts deployed learning algorithms to calculate a relative probability of close between the different simulations offered to the client while taking into account the evolution of commercial policies over time. To achieve this, Linedata worked with a mixed team of data scientists and business experts who were able to collaborate on a fast-track implementation for SOFAC through a Datalab.

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