Goals101 is a transactional behaviour intelligence company . Based on their deep understanding of big data and using Artificial Intelligence, Goals101 has created ‘The Alpha Platform’, a scalable platform that sanitizes, interprets and analyses data to extract actionable insights. Using these insights, companies can develop hyper-targeted campaigns for cross sell and up sell of products and services in a way that is highly customized for each end user.
Visham Sikand, Managing Director & Co-founder, Goals101 is a Harvard Business School alumnus and has always been passionate about his work and has bootstrapped all his 3 businesses.
In a conversation with IncubateIND, Visham talks about the latest technology trends that are reshaping the future of fintech. Read On!
Tell us something about yourself and what does Goals101 do?
I am an alumnus of the Harvard Business School & Goals101 is my 3rd Start-up. In my previous role, I was the Chairman of Aetna Inc., in India, after they had acquired my last company Indian Health Organization. Aetna is a Fortune 49 company & the 2nd Biggest in the Health Space Globally.
Goals101 is a FinTech company, which helps its bank partners take a giant and critical leap towards ‘Intelligent Banking’. It simply means – banks need to add more context, relevance and speed in their interactions with their customers. Banks have great teams internally and are smart people, all they need is some tools which truly solve their fragmented set of information and implementation (on scale) challenge. Our Alpha Platform for Banks helps solve this. it’s helping our Bank Partners move towards becoming PADs: Personalized, Automated and Delightful Banks.
With our deep understanding of Big Data and Artificial Intelligence, our scalable platform (the ‘Alpha Platform’) sanitizes, interprets, analyses data in real time to extract actionable insights. Goals101 provides a managed service, a 360-degree approach, an automation platform, along with all the products and services required for communicating with the customer. Today various custom-used cases for banks are being solved by us such as Inactivity, Credit, New Sourcing, Spend Jumps, Transactions Jump, Deep Geaographies, Attirition etc.
In my personal time, I socialise very actively, play tennis and swim. I love trekking and traveling and make sure to take out the time for my hobbies. At Goals101, along with an amazing team, we strive to become the Global Leader in ‘Intelligent Banking’.
What are the latest trends that will shape the future of fintech?
Indian fintech sector was valued at approximately $33 billion in 2016 and is slated to reach $73 billion in 2020. It is a constantly growing sector with the ever-changing ecosystem of customer expectations and regulations. And with such digital transformations, the banking services have already seen a shift from the traditional brick-and-mortar model to a greater virtual presence. It’s the turning point, that has impacted the entire ecosystem of the banking industry by redefining the modes of interactions. There has been a growing emphasis on intelligent data analytics. AI and machine learning have become an imperative part of FINTECH success. Big data is bigger than ever. From websites to mobile apps, phone calls to chatbots, brands have come a long way to be make it the easier for the customer to communicate. The skepticism around Blockchain has dissolved and it is here to stay. Lending and credit have become the hottest sectors with peer-to-peer and unsecured lending taking center stage. We are living in a very fast paced world where the companies which are futuristic, technology savvy and agile, will be the real winners in the future.
How is Artificial Intelligence redefining the financial services landscape?
AI has already emerged as a powerful disruptor in the financial services industry. It can be used right from underwriting to customer services. The scope of AI is so wide that using the right solutions has become very critical. In the last couple of years, the banking industry has increasingly deployed and implemented AI technologies right from the front-end to the back-end processes. And most players have already hopped on to the AI bandwagon.
AI helps banks become more customer centric
Customer centricity and Hyper-personalization go hand in hand. Banks understand that everyone’s needs are unique and want to customize products and communicate accordingly. In the digital age, an average customer is bombarded with multiple stimuli leading to a reduced attention span. It is important for banks to give the customers a personalised experience creating a great experience for them.
Improved operations, efficient cost management and focus on profitability
With the technological upgradation, banks understand that they need to pace up to sustain and for this, they need to become smart. With the help of AI, banks are becoming more efficient in their operations and cost management. The dramatic rise of technologies like Robotic Process Automation (RPA) and Intelligent Process Automation (IPA) is further fuelling this.
Risk management and fraud detection: The AI assurance-
Financial service providers are inundated with big data, especially unstructured data. However, the approach to surveillance has been very people-centric, through audits and sampling. With the rise of AI-based systems, it is possible to analyse volumes of business data and find out how well the internal control systems are operating. Increasingly, financial organisations are adopting a machine learning-based approach to augment their algorithmic rules-based approach towards surveillance and risk management.
How is IoT impacting banks and financial services?
There is a tremendous potential in India for the emergence of new-generation banking driven by digital. One of the technology trends, that is driving the digital transformation is the IoT. It is the network of internet-connected sensors that can be embedded into physical devices. Data collected in these devices can be shared across the web with people, applications and other devices. This data further aids the banks in decision making by helping them gain insights into their customers’ spending patterns, ATM-usage and financing needs. Banks use IoT technologies to create more engaging and context-aware customer rewards, to generate more intelligent and personalized customer cross sell opportunities. The IoT is boosting not just the urban but also the rural banking sector in India in a big way.
Can blockchain and related technologies solve India’s huge lending gaps?
Blockchain technology is a decentralized digital ledger that maintains a growing list of transactions between participants. In addition to providing enhanced security and control over data, blockchain can help banks cut transaction times and reduce costs. Indian banks have already started to implement blockchain solutions for implementing KYC protocols and executing overseas transactions such as remittances. The blockchain solution is also expected to streamline KYC implementation procedure, as banks will be able to share information such as risk profiles for corporate customers and suspicious transactions. With Blockchain banks and lenders can enable a completely digital process of lending which will also speed up micro lending cutting time while increasing transparency.
How is the financial services industry winning with Big Data?
Big data is typically characterized by the 3Vs — volume, velocity and variety. Big data technology enables sourcing, aggregation and analysis of data. Financial industry is the powerhouse of extremely rich data, but data without organization and insights is nothing but chunks of organized information. Big data is creating many avenues that are redefining the way financial institutions can capitalize on their data.
A very important part of big data is Analytics, (includes behavioural analytics, predictive analytics and sentiment analytics), which enables organizations to gain more precise insights about their customers and who does not want that. Globally, the trend towards increasing use of analytics in banking is driven by a slowdown in economic growth and pressure on margins. Banks in India are facing similar issues, leading to increased adoption of analytics.
Many Indian banks are using analytics across a multitude of functions, including managing customer relationships, reducing credit losses and NPAs, countering fraud/money-laundering, managing risks mapping networks etc.The right use of big data can completely transform the long-term success of any company in the financial services domain.
Is Machine Learning ideal for payment fraud prevention?
Machine Learning and Artificial Intelligence are revolutionizing businesses, brands and even entire industries. They can drastically reduce labor costs, generate new and unexpected insights, discover new patterns and create predictive models from raw data. They also have the power to operationalize data analytics and enable real-time automated decision making that wasn’t previously possible. The more data the machine learning system reviews, the more accurate its predictions will be. There has been a lot of buzz in the payments industry about machine learning being a great tool to automate fraud prevention. This is when a computer is programmed to use data to recognize patterns and identify potentially fraudulent transactions in real time. It seems only natural for companies accepting digital payments to want to take advantage of this type of program to bolster fraud prevention efforts.