CXOToday has engaged in an exclusive interview with Mr. Sanjay Kukreja, Global Head – Technology eClerx Services Limited
- Can you provide an overview of the services eClerx offers?
eClerx is a leader in innovative business process management, change management, data-driven insights, and advanced analytics powered by subject matter experts and intelligent automation. Clients benefit from our operational and domain expertise which when clubbed with smart automation helps to make process transitions and delivery a value additive process for our clients.
On the automation front, eClerx embeds all the work that it delivers with intelligent automation. These include either tactical automations like RPA or end-to-end applications that ensure that all activities in any process can be automated. Apart from embedding automation in our operations delivery, the technology team provides end-to-end consulting, implementation and solution support across a range of applications and technologies.
Our technology consulting and implementation services include:
- Generative AI
- AI & Machine Learning
- RPA lifecycle services
- Custom software development & support
- Software testing & quality assurance
- IT infrastructure services
- Data services
- Technology staff augmentation
- Cloud practice
- Third-party software implementation & support
- Software products for managed services
- Design studio
And more.
We understand that the current approach to building and managing technology is not enough for today’s business landscape. The rapid pace of change has made it difficult—if not impossible to achieve meaningful results with traditional methods. That’s where we come in!
We empower organizations like yours with trusted consulting services that support innovation across all levels within your organization.
- What industries and sectors do you specialize in serving?
At our company, we have extensive experience working with a variety of industries and sectors. Some of the areas we specialize in serving include Cable & Telecom, Financial Services, Retail, Travel & Leisure, and Hi-Tech.
- What is your approach to training and developing your technology teams to ensure they have the skills and knowledge to implement and manage technology solutions effectively?
Our approach includes a variety of training and development strategies:
Ongoing Training and Development: eClerx provides ongoing training and development programs to our technology teams to keep them up-to-date with the latest technologies and industry trends. The training encompasses both technical abilities and interpersonal skills development, including project management, communication, and leadership proficiencies.
Mentoring and Coaching: eClerx assigns experienced mentors or coaches to new team members to help them develop their skills and knowledge. This involves providing guidance on specific projects, as well as feedback and support for career development.
Collaboration and Knowledge Sharing: eClerx encourages collaboration and knowledge sharing among team members through regular meetings, workshops, and forums. This helps to foster a culture of continuous learning and improvement, as well as create opportunities for team members to learn from each other’s experiences.
Performance Management: eClerx uses performance management processes to assess the skills and knowledge of our technology teams and identify areas for improvement. This involves setting performance goals, conducting regular performance reviews, and providing feedback and support for improvement.
Overall, eClerx’s approach to training and developing our technology teams is focused on providing ongoing learning opportunities, fostering a culture of collaboration and knowledge sharing, and using performance management processes to support career development and skill building.
- Can you provide examples of successful technology implementations in the BPO industry that you have been a part of?
Example #1: We deployed our Compliance Manager application for client on-boarding and refresh. The application helped manage regional inconsistencies in information harvesting and reporting for KYC due diligence using advanced automation. The tool sources and updates KYC data using RPA and AI.
Example #2: We utilized our product, Roboworx, to automate 80 percent of one of the world’s largest cable & telecom company’s manual processes. As a result, Roboworx filled the employee shortage gap of 10 full-time employees, saving $65,000 per month.
Example #3: We utilized our data engineering toolkit to manage end-to-end data cycles for one of the largest Hi-Tech manufacturer in the world. The toolkit help ingest, clean, enrich and visualize data across multiple data sources, which helped provide real-time decision-making capabilities to our client.
- What is your experience with AI and Machine Learning technologies at eClerx?
The AI/ML technologies that have been implemented by eClerx focus on solving our client problems around text mining, image processing, speech and video processing as well as executing use cases around predictive analytics. Since most of the work that eClerx delivers is around data, AI/ML solutions blend very well with our services. The text analytics use cases include text mining, natural language processing and intelligent document digitization. With the advent of Generative AI, eClerx is focused on solving use cases around content generation, summarization and semantic search. Our image processing tools use deep learning to solve use cases around image classification, adjustment and tagging. Our speech to text conversion tools are an integral part of our Customer Experience offering where these models run both on private and public datasets for training.
- What emerging AI and Machine Learning trends are you most excited about and why?
We are excited about the trends we’re seeing in two areas: cable & telecom and financial services industries. Within the cable & telecom industry, the rise of streaming services has made it more important for cable companies to provide personalized content for their customers. AI and ML make it easier for these companies to cater to their audience. This can help keep customers happy while also making finding new customers easier.
AI and ML can help cable companies provide better customer service by automatically detecting customers’ needs based on behavior patterns or context clues, such as location-based information gathered from connected devices like smartphones or smart TVs. Think: “What should I watch while I’m at home?”
They can also help find new customers by using predictive analytics techniques that identify potential leads based on similar characteristics found among current customers. Think: “People who watch The Walking Dead tend not to watch Game of Thrones.
AI and ML give cable companies the ability to predict when customers may be dissatisfied. Using machine-learning algorithms, companies can identify patterns in customer interactions and react before they happen. This could mean preemptively reaching out to those who are likely to cancel their subscriptions if not given better service options or sending targeted ads or coupons based on what you know about them (maybe they have kids who like sports but haven’t signed up for cable yet).
In addition, AI platforms can find ways to ensure customers stay happy once they’re already subscribers—and not just by predicting when someone might leave and offering deals accordingly. By analyzing each customer’s data profile and behavior patterns over time, you’ll be able to offer personalized recommendations based on their unique interests as well as targeted ads across different devices. For example: “Hey John! We noticed you’ve been watching lots of cooking shows lately; here’s one from Amazon Video Prime.
In the second industry – financial services, fraud detection is the most common application of AI in the financial markets industry. Machine learning models have been used for a long time in the credit card transaction monitoring to flag abnormal behavior, which could be fraudulent. Many people have personally experienced receiving calls when they’re making a transaction when they’re overseas. These have existed for quite some time. Now, more recently, banks have started using machine learning in anti-money laundering control initiatives.
A lot of these initiatives use NLP to screen news and adverse media articles. NLP is used for matching names and identifying hits, and machine learning models are also used for anomaly detection on transaction patterns to be able to flag fraud. At eClerx, we have used NLP to analyze news articles. And this has been applied in various contexts.
One of them is in the anti-money laundering space where we are doing KYC review of clients and we are looking for adverse media about the clients. And the same techniques can be applied for various other functions within the bank, whether it’s it is for monitoring any expected change in the creditworthiness of clients to set up early warning systems based on news articles of target customers that the bank may be tracking.
So, in all these, the common principle is that if you do a search, you would get hundreds to thousands of articles about the entities that you’re searching. Machine learning and NLP is being used to determine if that article is relevant to the search that you’re making.
For example, when we are doing this for adverse media screening for KYC, we try to find out if the article is relevant to the entity that is being researched upon or is it just a coincidence that the entity’s name is mentioned in some context on the article. So, finding out the relevance of the article to the context is made using machine learning. We also try to extract certain data points from the article to see if the target entity has been alleged to commit a crime or if there is a conviction, because that is a big difference in terms of materiality of the news.
We try to determine whether the article has spoken about a conviction of the entity by a court or authorities and also when was this judgment made, so that if it is in a period that is far back in the history, then it may not be material in the current context. All those factors are extracted through natural language processing and machine-learning capabilities applied on the news articles. This typically is used to reduce the noise in the search that we get, even where banks use paid sources like Factiva or wall check.
There is a high degree of false positive that positives that come through in the search, and these techniques are used to reduce those false positives so that the review effort is spent on the articles which have a high probability of being a true hit. This can be constructed in such a way that it can be used for AI/ML or it can be used for tracking important target customers to see if there are any events that that helped in pitching new products or solutions to the client, as well as an early warning system to detect any credit deterioration based on news articles that you can get in the public domain.
In all this, AI and ML has enabled scouring through far more data sources than humanly possible to identify fraud.
- What sets your company apart from other Business Process Outsourcing providers in the industry?
What sets eClerx apart from its competitors is our ability to provide customized and value-driven solutions tailored to our clients’ specific business needs. We understand that the current approach to building and managing technology is not enough for today’s business landscape, and the rapid pace of change has made it difficult—if not impossible to achieve meaningful results with traditional methods.
As a result, our team of experts is always up-to-date with the latest technological advancements, helping our clients leverage these technologies to stay ahead of the curve.
Furthermore, our global presence, with offices and teams located in Australia, Canada, Germany, India, Italy, Netherlands, Philippines, Singapore, Thailand, the UK, and the USA, enable us to deliver seamless and high-quality services to our clients, regardless of their location.
