Increasing the Possibilities of AI Platforms with Active.Ai

Asia Blockchain Review
August 3, 2019

Asia Blockchain Review recently spoke to Ravishankar, Shankar Narayanan, and Parikshit Paspulati, Co-Founders of Active.Ai, an award-winning fintech startup that is building a conversational AI platform from Singapore for the rest of the world. The founders talked about understanding unstructured data to help financial services design intelligent conversations, developing AI enterprise platforms, the possibilities for AI solutions, and how AI is already changing the world. 

Asia Blockchain Review:  What was the inspiration and rationality behind the founding of Active.Ai?

Co-Founders of Active.Ai: During one of his overseas trips, Ravishankar (Co-Founder and CEO) lost his wallet, forcing him to block all his cards and report the loss. A phone call to the bank and its lengthy IVR (Interactive Voice Response) process compounded his stress. Looking back, what crossed his mind at the time was that there must be a much simpler, faster way to resolve this predicament. 

Instead of going through the arduous step-by-step instructions, from profile verification to confirming the card cancellations, he thought it would be easier, through chat messaging, to let the bank know what he went through. The bank would take care of the rest with minimum fuss, the same way a bank’s relationship manager understands a customer’s intentions and provides the best solution. 

So the idea of having an AI-powered Virtual Assistant for messaging was inspired by that unfortunate event. Simply type/say, “I lost my wallet,” and the bot would understand the possible meaning, intent, and potential outcome behind such a statement. The bot then calls out the cards to be blocked with a single touch. This is one of the many disruptive but interesting possibilities, where the power of conversational AI helps reimagine the overall banking experience.

 

ABR: How do you enhance the AI enterprise platform with Natural Language Processing (NLP), Natural Language Understanding (NLU), and Machine Intelligence? How widespread is the use of these technologies?

Active.Ai: We are taking the conversational experience to a deeper level of customer engagement that goes beyond the transactional, moving conversations from reactive to proactive and predictive. Our virtual assistants are not just bot-based conversations, but a bot and human agent/relationship manager-based collaboration. 

Our expertise in the financial services industry and attention to accuracy rates particularly when dealing with a multiple-language, multiple-dialect environment, omnichannel presence, and customer insight based on machine learning leads to a customer experience that is way beyond what an application or portal can provide. We believe that when customers communicate in a natural, conversational way, they reveal more about their preferences, opinions, feelings, and inclinations. Our AI engine understands that and acts based on that machine comprehension. There are six major benefits of employing conversational AI:

Rich User Experience Crafts intelligent micro-conversation by incorporating personality and a unique voice for each brand. The AI produces curated natural dialogues that are multi-lingual from the brand’s base datasets using human trainers and training algorithms. Constantly learning, the AI will not just have a far deeper understanding of a brand’s customers, but the ability to personalize the experience.

Cost Savings Provides prebuilt datasets with complete industry standards for functional flows of services in retail and corporate banking, brokerage, and insurance. Through machine learning, our conversational virtual assistants’ highly predictive nature resolves customer service issues before they arise, thereby significantly reducing customer abandonment rates and helping to streamline tasks naturally.

Boost Productivity Through our AI’s cognitive automation, unstructured information from customer interactions can easily be analyzed, processed, and restructured into useful, consumable data by the brands. Our AI helps boost productivity and allows brands to stay focused on business goals.

Service Accuracy State-of-the-art Machine Learning capabilities adept at automatically learning and improving from origin datasets, with the incorporation of NLP and NLU, easily handle context driven conversations. With the understanding of users’ behaviors and goals through our AI technology, brands can respond appropriately with detailed accuracy.

Ease of Knowledge Transfer The AI engine platform is equipped with NLP, NLU and Machine Learning. Our product’s AI is used to learn and understand human intent and respond intelligently. Our out-of-box solution with pre-built models is easily configurable and highly customizable, making the training and knowledge transfer process simple and easy to adopt by everyone.

Applicability Flexible “AI Switch” approach enables smooth collaboration across channels to accomplish tasks, learning from interactions to help suggest and complete new tasks. Through comprehensive and flexible APIs (application program interfaces), we can connect TRINITI through MORFEUS (Active.Ai’s middleware product with API that helps with integration into various banking platforms) to all middleware systems of financial institutions (FIs) and help seamlessly plug into various channels.

 

ABR: What are some of the key challenges in implementing AI solutions for various industries? How have you tackled these issues?

Active.Ai: In the BFSI (Banking & Financial Services Industry), we see attempts to streamline processes such as customer engagement that, in the past, have been labor intensive. We see that brands try to resolve thousands of their customers’ simple queries or FAQs with minimal to no need for human interaction. The responses are in real-time across their channels of engagement, through web, mobile messaging platforms, and voice-based devices. By anticipating customers’ needs from context, preferences, and prior queries and responses and delivering proactive alerts, relevant offers, or transactional content, the AI Virtual Assistant becomes smarter over time and performs almost flawlessly in any scenario.

On automation and knowledge transfer, the AI platform offers huge time and cost savings if it is pre-programmed with industry and domain knowledge, and BFSI firms only have to train it once. The AI emulates human actions to automate and perform repetitive, high-volume, and time-consuming business tasks. They can further refine the responses and actions, making adjustments according to their customers’ handling protocols and business objectives. A good AI platform is equipped with NLP, NLU and Machine Learning, is used to learn and understand human intent, and responds intelligently, thereby making training and knowledge transfer process simple and easy to adopt by internal personnel.

Leveraging AI technology to improve the quality of services is how BFSIs have decided to tackle the competitive marketplace. With strict quality control, delivery and speed to market that includes intuitive user experience mean that they will drive faster customers’ adoption with accurate data and insights into what they want in real-time.

While legacy banking systems have been able to make transaction processing more efficient over time, there are still serious obstacles hindering meaningful CX (customer experience) improvements. To be future-ready, BFSIs look towards not just updating their legacy systems, but also transform their back-office tech to deliver the customer experience people expect. One way they are looking to achieve this is through AI. 

ABR: Is the TRINITI solution designed specifically for the banking and financial sector? Can you tell us more about the development of this solution?

Active.Ai: Active.Ai’s award-winning TRINITI.Ai is a Conversational AI platform with a powerful combination of cutting-edge AI algorithms and data models. It focused on BFSIs with secure, on-demand, and scalable infrastructure on the cloud powered by Amazon Web Services (AWS). Business users and developers can rapidly configure and build intelligent conversational systems/services.

This enterprise AI platform for the BFSI runs on the cloud to provide customers with a reliable, agile, and scalable experience. Running on AWS’s fault-tolerant, high-performance infrastructure, TRINITI enables customers, such as banks, insurance companies, and financial institutions, to support voice-based transactions on the cloud. Leveraging AWS’s GPU infrastructure with Amazon Elastic Compute Cloud (Amazon  EC2), it performs advanced workloads like machine learning and quickly scales capacity during peak times, such as when testing new applications, and delivers conversational financial services. This assists banks, securities, insurance, and payment companies in redefining their digital strategy. With NLP, NLU and Machine Learning, the platform enables natural dialogues using messaging, voice, and IoT devices. It has the AI capabilities for natural language comprehension and conversation, which can go from transactional to predictive and collaborative by seamlessly bringing in a human agent into the conversation.  

This product innovation helps our clients in customer engagement, queries/call center inquiry-based services, transaction services, predictive engagement, and commerce. While using AI to lower operational costs for engagement and increase adoption is appealing to banks in terms of return on investment (ROI), it also provides the best experience in Lead Generation/Origination.

Active.Ai’s goal is to bank a billion and grow the conversational volume of its clients and partners. This innovation helps BFSIs at the frontend to secure customers, mimic bank employees, deepen digital interactions beyond the transactional, and engage customers across channels. Within the organization, AI on the backend aids employees, automates processes, and preempts problems.

TRINITI.Ai is an award-winning innovative product based on the idea that having a conversation is the natural way to interact. Team Active.Ai helps create that capability and potential. Unlike the conventional web or app experience that’s linear and one dimensional, a typical conversational journey can be unstructured at all times. 

Through the BFSIs’ engagement channels, a voice or text entry, whether the instruction or query is simple or complex, connects both systems through APIs. It deciphers the content, and through natural language processing and understanding, helps to make sense of the instruction or request (intent). It pulls out the relevant data (entity) until all the required BFSIs’ parameters are complete, which its API can consume properly. The whole effort is managed through a dialog approach. Finally, the end user of the BFSIs will get a conversational response through their channel of choice, e.g. messenger, bank or social platform, voice, and IoT with Alexa or Google Home. 

To make the product great, Team Active.Ai took great pains to incorporate additional services building the best practice CX journey and providing professional services to seamlessly integrate backend and overall implementations for FIs. The administration user panel allows a user to not only create CI screens, design a customizable CX journey, and enable backend system integration, it also trains and retrains the AI engine and review users’ and customers’ transactions and AI reporting. Further product enhancement includes productizing FIs’ verticals with prebuilt, out-of-the-box journey and training data. The specialized verticals covered are Banking, Insurance and Capital Markets.

ABR: Can you tell us more about the features offered with MORFEUS? How does it enhance a client’s service platforms?

Active.Ai: We deliver conversational banking services for our customers with our AI engine called Triniti and conversational middleware called Morfeus. Triniti is built to craft intelligent micro conversations fine-tuned specifically for banking and finance and pre-trained relevant ontology built with preprocessor, NLP, NLU, NLG (Natural Language Generation) and Machine Comprehension. Morfeus acts as an orchestration layer that hooks to frontend channels including messaging, voice, social and IoT, with an advanced integration interface to complex backend APIs of the banks and financial systems. We have added business applications for financial services that are highly scalable as well as customizable, prebuilt models specifically for banking, insurance, and capital market functionalities that are built with multiple language support in mind.

 

ABR: How quickly are businesses in Southeast Asia adopting AI solutions? In what aspects?

Active.Ai: In SEA, we are beginning to see AI adoption is still in its infancy but on the rise, given the market sentiments on AI and that businesses are just beginning to understand its application. Though AI applications are less well understood and genuinely knowledgeable AI talents are few and far in between, conversations are universally natural. People use messaging and voice chat as an integral way to communicate with one another, and that may be a huge factor in pushing adoption forward. We see a wide range of applications, especially in the BFSI verticals in India, where they launch their AI solutions and try to stay ahead in the technology adoption curve. We see that the global trend is moving in that direction as well.

In BFSIs, we are beginning to see apparent adoption of AI into their strategies, trying to bring conversational experiences to a deeper level of customer engagement that goes beyond the transactional. We are seeing a movement of conversations from reactive to proactive and predictive. Virtual Assistants are not just a bot-based conversation, but a bot and human agents/relationship manager-based collaboration. All this will transform the way we live, think, and interact.

In certain parts of Asia, Singapore and India particularly, we see a quicker maturity in AI application and faster adoption in BFSI services, especially in Tier 1 banks and capital markets. This is because unstructured information from customer interactions can easily be analyzed, processed, and restructured into useful consumable data by them. And AI’s cognitive automation will help in customer engagement, answer general queries/call-centre enquiries, transaction services, predictive engagement, and commerce. The AI helps manage customer engagement with the best experience in lead generation/origination, with increased adoption rates and lower overall operational costs, allowing banks to achieve the best ROI. At Active.Ai, we believe that conversational AI is on the rise and helps boost productivity, allowing brands to streamline operations, save money and time, and stay focused on business goals.

 

ABR: Can you tell us about your vision for Active.Ai? 

Active.Ai: Active.Ai’s vision is to become the AI Software-as-a-Solution (SaaS) platform for financial services, helping to redefine their digital strategy for the future, bringing in enhanced automation, and enriching intelligent customer engagement through Conversational AI.

 

ABR: How is AI changing the way businesses interact with customers? How widespread will the use of AI become in the near future?

Active.Ai: Businesses, particularly BFSIs, have significantly evolved over the years from technology experimentation to adoption. The next phase of digital business will be powered by AI-enabled services that will drive interactions and form deeper engagement between businesses and their customers.


Follow Asia Blockchain Review on:

About the author
Asia Blockchain Review

Gateway to Blockchain in Asia

Asia Blockchain Review is the largest initiative for media and community building in Asia for blockchain technology. We aim to connect all blockchain enthusiasts on a regional scale and facilitate the technological foundation of blockchain through a range of group discussions, technical workshops, conferences, and consulting programs.

Related Article
GSMA Hong Kong Expresses Positive Outlook for Blockchain
Paul Ulrich, Senior Policy Manager of APAC, GSMA Hong Kong, revealed that developing countries acros...

August 22, 2019

India’s Reliance Jio Unveils Its Massive Blockchain Network
Reliance Jio will install across India one of the largest blockchain networks in the world “with ten...

August 22, 2019

Mosendo, the Final Piece of the Cryptocurrency Payments Puzzle
We kick off the interview series with Clayton Roche, the Head of DeFi with Mosendo and the community...

August 21, 2019

Escalating Protests in Hong Kong Reinforce Bitcoin’s Safe Haven Status
Demand for Bitcoin is surging as more people look to reliable safe haven currencies in the face of e...

August 21, 2019

We provide information about Asia Blockchain Review latest activities as well as global blockchain news and research. Subscribe to our Newsletter now or Contact us