Speaking to TechGraph, Ankit Sinha, Vice President (VP) of Cloud Practices and Consulting, Searce has said, “Artificial Intelligence and Data Science have a bright future because of the advanced automation they offer for various applications we use daily.”
Read the complete interview:
TechGraph: How is Searce utilizing its sectoral expertise and digitalization to provide data-centric research and analytics services for its clients?
Ankit Sinha: The Data and Analytics practice at Searce has many years of experience designing and implementing multi-terabyte, multi-user databases, and data warehouses supporting reporting and analytics platforms.
We use our sectoral expertise with the most appropriate methods and our Ips/Accelerators/Framework and Cloud Modernized digital tools to provide data-centric research and analytics services for our clients. For instance, integrating your business data is key to effectively performing retail data analytics.
Big Data & Advanced Analytics play a major role in the future of retailers by helping them to make smarter decisions, improve operations and increase sales. And thus, Searce has built a Customer Data Platform (CDP) for our retail customers which will help them to see faster business values.
Searce’s industrial experts understand the client’s data, analyze it and use advanced technology to create relevant business solutions. We have a dedicated team for every industry that creates unique solutions with our hyper-scale.
To quote another instance, Searce has pre-built AI/ML models to address all the pain points of our Fintech customers to accelerate their digital journey by improving their core business processes and creating customer-centric experiences. Searce collaborates with data experts from the client-side services teams in two ways.
Firstly, we work with their partners to leverage the enterprise and project-level data architectures they have defined to identify asset datasets and the associated asset data stores that can be used to perform data analysis where we discover new data assets through the course of our projects. To enhance the analytical services, we integrate the effective AI and ML algorithms with data management and data analysis
Secondly, we will work with their client-side services teams to support them in using asset-related data analysis to frame the business objectives, scope, and business cases that have been identified.
Furthermore, we will apply our innovative best practice framework for use case selection to support your client-side delivery partners to identify adjacent use cases and operational business opportunities that directly relate to safety, reliability, affordability, and growth across the sectors/industries. Considering the client’s business needs – Searce builds convincing customer data platforms and recommendation engines to accelerate the business.
TechGraph: How are AI and ML helping in the revolution of business assessment toward financial Inclusiveness?
Ankit Sinha: Many of the key processes and functions in FinTech businesses are supported by AI/ML. The use of advanced machine learning models for credit scoring has become an integral part of the underwriting processes for many fintech lenders.
This enhances application processing efficiency, enables faster processing of applications, and improves portfolio quality since powerful ML models predict delinquency risk quite accurately.
AI and machine learning have been extremely effective in helping fintech players in the MSME lending space, particularly those at the bottom of the pyramid who have limited or no access to formal credit from banks and other lenders.
To overcome the lack of credit history, fintech players are looking for devising innovative methods of creditworthiness evaluation. The Custom ML model built at Searce departs from the traditional data requirement constraints, allowing lenders to predict the probability of delinquency/default based on various kinds of alternative data quite accurately and evaluate and underwrite credit risk accordingly.
To build these AI and machine learning models, some fintech lenders lend to micro and small businesses using localized economic data, business image data (e.g., stock of goods, store space, store frontage, location, etc.), along with limited banking data, informal accounting data from mobile apps, etc. With AI/ML, fintech lenders are increasing financial inclusion to underserved segments of the MSME sector while maintaining a strong portfolio by making smart, quantitatively informed underwriting decisions.
TechGraph: How is Searce leveraging technology to enhance the customer experience?
Ankit Sinha: “What gets measured gets done,” goes the old saying. Over the years, executives looking to enhance their organizations’ competitiveness have devoted a great deal of attention to a wide variety of metrics that range from assessing the level of customer satisfaction, metrics for determining whether a company should continue a product, metrics for gauging how effectively a company serves its customers, and even metrics for assessing how “ideal” a customer’s experience is.
Our experience suggests three essential elements that can transform a middling approach to measuring the customer experience into one that can deliver impact and deliver value. As a first step, effective customer experience measurement pays attention to the journey level rather than analyzing just transactional touchpoints and overall satisfaction.
Secondly, it is vital to invest in hardwired technology that can capture customer feedback daily from multiple channels and integrate survey results, social media posts, and operational data into comprehensive, role-specific dashboards. Transparency can be created and decisions can be driven at all levels.
The final step to overcoming organizational inertia is cultivating a continuous-improvement mindset throughout the organization. Customer feedback should be integrated into the frontline worker’s responsibilities and used to improve the customer experience.
TechGraph: How do you see technologies namely AI, ML, and Data Science, with regard to their relevance across the analytics network? What does the future look like?
Ankit Sinha: A variety of business and consumer benefits flow from data science, machine learning, and artificial intelligence. In recent years, research and development efforts on automated processes and machine learning have been increasing with AI and data science automating much of production – thereby increasing efficiency.
Data science and AI will become increasingly popular in 2022. We can observe this trend by following the development of hyper-automation and advanced Natural Language Processing. Additionally, augmented analytics will leverage concepts such as the Internet of Things to reinforce and improve various technologies, such as advanced analytics, user interface, and cyber security.
The future of AI, machine learning, and data science will be further established by more machines, devices, services, smart cities, and homes that are powered by ML and AI. We will be focusing our efforts on developing more effective human-machine interaction, as well as developing true autonomous systems that can perform complex tasks for long periods without human assistance.
The future looks at encompassing these technologies across various industries. Artificial Intelligence and Data Science have a bright future because of the advanced automation they offer for various applications we use daily. With the rise of AI, IT companies, banking corporations, and other companies will benefit from increased productivity, speed, and resolutions.
To fully utilize this holy grail of modern technology which is Machine Learning, companies from all sorts of industries are jumping on the artificial intelligence bandwagon. Therefore, research can proceed more quickly, leading both to improvements for consumers and producers alike.
TechGraph: How is the response so far for your Consulting Services?
Ankit Sinha: In line with the industry trend, we have witnessed strong growth in the demand for our IT consulting services in the last couple of years. IT leaders are constantly looking for ways to reimagine their operating and business models using technology as the backbone. And with this shift.
Some of the key challenges that we are addressing for our customers today using our consulting services include:
a. Helping organizations observe improved productivity and employee collaboration – whether the teams continue to operate from an office, satellite offices, or remotely
b. Helping our clients design their IT systems to be able to manage the dynamic business environment
c. Deriving maximum value from the client’s data that operate in silos to help them on their journey to become a truly data-driven organization
d. Leveraging IT agility i.e. ability to design and deploy changes to the IT environment with low cost, return on investments, and minimal risk
e. Optimizing their cost spending on IT environments while still providing them with the ability to access the most innovative solutions & platforms.
