Actico ML helps enterprises.

Actico helping businesses make smarter decisions via ML

Platform combines expert knowledge and data knowledge at every level to create an optimum decision

Singapore-based Actico Pte Ltd has been helping businesses globally to make smarter day-to-day decisions that drive higher levels of growth and attain a competitive advantage. The company provides best-in-class software and tools used across multiple industries, enhancing day-to-day decision-making and end-to-end automation.

Ajit Shah, MD APAC, Actico, tells us more in a face-to-face discussion.

Actico ML helps enterprises.DQINDIA Online | dqindia

Actico ML helps enterprises.

Dataquest: Please tell us about Actico.

Ajit Shah: We are a German company. We were originally part of Bosch, and became Actico, an independent company, 3 years back. We are focused on financial services. We are a platform for intelligent decision automation.

The areas we focus on are risk management, compliance, fraud, and automation of business processes. The plan is to move on to the other industries, especially, telecom and healthcare. Some of our major customers globally are UBS, Bank Santander, Royal Bank of Canada, CIMB, MayBank, ING, etc.

In India, Bajaj Finance is our major customer. Others are DMI Finance, Delhi, HDFC, and SBI Life Insurance.

Dataquest: Elaborate on the ACTICO ML software platform.

Ajit Shah: ML or AI, we call it as the augmented intelligence. We have an integrated platform where you can introduce machine learning, business logic, and automate the business process to do a digital decision. It is a pure technology platform.

We believe that financial institutions will bring all their business expertise and data, and configure the platform as per their needs. The platform can be used by business users and define their business policies.

The first version was built almost 18 years ago, and the work on ML has been built over the last two years. The independent company was launched 3-1/2 years ago and all the development work happens in Immenstaad, Germany.

The differentiating point is: we bring all the ML output back into the business rules on a real-time basis. Customers have used the platform for different use cases, including lending, customer experience, fraud, etc. In the areas of risk management and credit decisions, the combination of business rules and machine learning has demonstrated a 20-25% improvement.

In the case of compliance, or fraud, or KYC AML, we have seen that due to the ML platform, the improvement has been at least 30-40%.

The expert knowledge and the data knowledge can be combined at every level to create an optimum decision. The entire process can be automated 100 percent.

Dataquest: How can it generate ML models and combine them with business rules?

Ajit Shah: The orchestration of feature engineering, data management, training and retraining of models, etc., are all executed through the business rules. The output of the ML can be directly called from the business rules.

The platform also has the capability to ingest data from other sources like bureau data, third-part industry data, etc.

Dataquest: How can it assist trained machine learning models in production systems?

Ajit Shah: The initial training has to be driven by defining the data and building the models. Once the initial models are defined, the retraining of the models on an ongoing basis gets fully automated.

Dataquest: Besides financial institutions, who are your other targets across India?

Ajit Shah: We are looking at telecom and healthcare. Enterprises are also moving toward digitization. Retail is yet another industry we are looking at.

Dataquest: Have you signed customers for Actico ML in India?

Ajit Shah: As a ML company, we have signed up DMI Finance in Delhi. DMI Finance is a lending company, who’s aim is to be a 100% digital lender. They initially automated their decisioning process using the Actico platform, with the aim that all decisions should be executed in less than 30 seconds. This was implemented in April 2018.

Subsequently, in March 2019, they decided to augment the capabilities by implementing ML to execute behavioral scores, fraud scores, etc., so that they can further improve on their credit decisions.

Dataquest: Finally, what are your future plans, especially for the other industries?

Ajit Shah: There are a lot of opportunities in the financial industry, owing to the growth in the amount of lending. With mobile, people also want real-time decisioning. RBI has also come up with P2P lending and small finance banks. These provide us with a great opportunity in future.

We also work with new edge fintech companies who are offering some innovative customer offerings. They can use our platform for building their own solutions.

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