Machine Learning And Intelligent Process Automation; Interview with Bikram Singh, Co-Founder and CEO of EZOPS – TechBullion
Share
Share
Share
With Artificial Intelligence, EZOPS can maximize data confidence, integrity, and control. This machine learning and intelligent process automation platform is one innovation to look out for, the CEO Bikram Singh shares more insights into the platform with us in this interview with TechBullion.
I am Bikram Singh and I am the CEO and Co-Founder of EZOPS.
I have built and managed operational services and technology solutions for banks, hedge funds, asset managers, fund administrators, and custodians.
From my experience in the financial industry, I know firsthand the pain points that plague data management teams. As a result, it has become my mission to develop an end to end platform that addresses the challenges teams face across the entire lifecycle of data. Through EZOPS, I am able to obtain my goal of providing financial institutions with a solution that drives operational efficiency and delivers quality data.
Prior to founding EZOPS, I had over 20 years of experience managing financial services operations and technology while working at McKinsey & Company, Lehman Brothers, Lava Trading, Goldman Sachs, and Citi.
EZOPS is AI-enabled software that harnesses the power of machine learning and intelligent process automation to revolutionize data control and drive transformative efficiency gains at some of the worlds largest financial services institutions.
Through my years of experience in financial services, I, along with Co-Founders Sarva Srinivasan and Dutt Chintalapati, realized that we could develop and implement automated workflows to solve for many of the challenges our clients faced every day. We combined our industry experience with our knowledge of machine learning and automation to develop EZOP in an effort to eliminate the longstanding redundancies and inefficiencies that have plagued the industry for decades to help transform how data is controlled at large financial institutions today.
EZOPS is the leader in cutting-edge innovation for the financial services sector, including: Global Banks, Regional Banks, Custodians, Asset Service Providers, Asset Management, Operations Outsourcers, Fintech, Corporate Treasury.
Our solutions help our clients transform their business operations and cover crucial areas such as Operations, Finance, Governance, Regulations, Compliance, and Audit to enhance quality & control for post-trade operations.
EZOPS offers comprehensive functionality that businesses of large scale and complexity need in order to manage the four pillars of operational data control reconciliation, research, remediation, and reporting all powered by Machine Learning and smart workflow management.
EZOPS intelligently automates repeatable actions, checks for errors, and offers insights that users might miss on their own. The goal is to streamline parts of the process that software can do better.
EZOPS platform combines machine-learning with smart workflow management functionality for comprehensive end-to-end automation.
It integrates siloed data and processes across the enterprise for cohesive exception management processing EZOPS ARO improves transparency and communication via alerts, notifications, messages, and emails.
It Facilitates source system remediation to OMS, PMS, accounting systems & sources for reference data, corporate actions & market data.
Since the financial crisis the landscape across the institutional financial sector has changed. This has further accelerated with the global pandemic and the drive for digital transformation.
The business of financial intermediation is entering the post-internet era and the next decade will see business models on the institutional side being disrupted as large financial institutions start taking a hard look at the collection of businesses they have and the associated fit with their respective business model and strategy.
As digitalization, shedding, restructuring, realignment takes place, it will present an opportunity for a variety of players. Many of whom will likely be unregulated, technologically savvier, and much more nimble than the institutions of the past.
Transactional volumes have increased during the pandemic in conjunction with an increased focus on regulatory reporting and compliance. At the same time markets and companies have become more fragmented.
This has led to an increased operational and technical infrastructures that were primarily built to support pre-crisis business complexity, volumes and regulatory reporting are proving to be costly to maintain and yielding less than desired business value.
EZOPS can be easily integrated into a clients current operating systems via cloud or on-premise installations. Clients are up and running in a matter of days depending on the complexity of their ecosystem & tech stack. Amazon Web Services (AWS) users can access EZOPS ARO capabilities via the Amazon Marketplace in a matter of hours. EZOPS multiple partner and channel integrations allow clients to switch on new capabilities seamlessly and in a frictionless manner.
Yes, we have a strategic partner ecosystem consisting of technology providers, consulting organizations, and financial software firms. Our partners compliment our software solution and support our clients globally. Solutions partners include: BNY Mellon, Riskfocus, Orchestrade, and Access Fintech. Technology partners include: Snowflake, Oracle, and AWS.
Website: https://www.ezops.com
LinkedIn: https://www.linkedin.com/company/ezopsinc/about/
Twitter: @ezopsinc
Facebook: @ezopsinc
- Meta speeds up its hiring process for machine-learning engineers as it cuts thousands of 'low performers' - Business Insider - February 11th, 2025 [February 11th, 2025]
- AI vs. Machine Learning: The Key Differences and Why They Matter - Lifewire - February 11th, 2025 [February 11th, 2025]
- Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression - Nature.com - February 11th, 2025 [February 11th, 2025]
- Climate change and machine learning the good, bad, and unknown - MIT Sloan News - February 11th, 2025 [February 11th, 2025]
- Theory, Analysis, and Best Practices for Sigmoid Self-Attention - Apple Machine Learning Research - February 11th, 2025 [February 11th, 2025]
- Yielding insights: Machine learning driven imputations to fill in agricultural data gaps in surveys - World Bank - February 11th, 2025 [February 11th, 2025]
- SKUtrak Promote tool taps machine learning powered analysis to shake up way brands run promotions - Retail Technology Innovation Hub - February 11th, 2025 [February 11th, 2025]
- Machine learning approaches for resilient modulus modeling of cement-stabilized magnetite and hematite iron ore tailings - Nature.com - February 11th, 2025 [February 11th, 2025]
- The Alignment Problem: Machine Learning and Human Values - Harvard Gazette - February 11th, 2025 [February 11th, 2025]
- Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data - Nature.com - February 11th, 2025 [February 11th, 2025]
- Analyzing the influence of manufactured sand and fly ash on concrete strength through experimental and machine learning methods - Nature.com - February 11th, 2025 [February 11th, 2025]
- Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008 -... - February 11th, 2025 [February 11th, 2025]
- Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation - Nature.com - February 11th, 2025 [February 11th, 2025]
- Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the... - February 11th, 2025 [February 11th, 2025]
- Unlock the Secrets of AI: How Mohit Pandey Makes Machine Learning Fun! - Mi Valle - February 11th, 2025 [February 11th, 2025]
- Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer -... - February 5th, 2025 [February 5th, 2025]
- Machine learning for predicting severe dengue in Puerto Rico - Infectious Diseases of Poverty - BioMed Central - February 5th, 2025 [February 5th, 2025]
- Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact - Nature.com - February 5th, 2025 [February 5th, 2025]
- AI and machine learning: revolutionising drug discovery and transforming patient care - Roche - February 5th, 2025 [February 5th, 2025]
- Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults... - February 5th, 2025 [February 5th, 2025]
- Identification of therapeutic targets for Alzheimers Disease Treatment using bioinformatics and machine learning - Nature.com - February 5th, 2025 [February 5th, 2025]
- A novel aggregated coefficient ranking based feature selection strategy for enhancing the diagnosis of breast cancer classification using machine... - February 5th, 2025 [February 5th, 2025]
- Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine... - February 5th, 2025 [February 5th, 2025]
- How machine learning and AI can be harnessed for mission-based lending - ImpactAlpha - January 27th, 2025 [January 27th, 2025]
- Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms -... - January 27th, 2025 [January 27th, 2025]
- Using robotics to introduce AI and machine learning concepts into the elementary classroom - George Mason University - January 27th, 2025 [January 27th, 2025]
- Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea - Nature.com - January 27th, 2025 [January 27th, 2025]
- Why Most Machine Learning Projects Fail to Reach Production and How to Beat the Odds - InfoQ.com - January 27th, 2025 [January 27th, 2025]
- Exploring the intersection of AI and climate physics: Machine learning's role in advancing climate science - Phys.org - January 27th, 2025 [January 27th, 2025]
- 5 Questions with Jonah Berger: Using Artificial Intelligence and Machine Learning in Litigation - Cornerstone Research - January 27th, 2025 [January 27th, 2025]
- Modernizing Patient Support: Harnessing Advanced Automation, Artificial Intelligence and Machine Learning to Improve Efficiency and Performance of... - January 27th, 2025 [January 27th, 2025]
- Param Popat Leads the Way in Transforming Machine Learning Systems - Tech Times - January 27th, 2025 [January 27th, 2025]
- Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods - Nature.com - January 27th, 2025 [January 27th, 2025]
- Machine learning is bringing back an infamous pseudoscience used to fuel racism - ZME Science - January 27th, 2025 [January 27th, 2025]
- How AI and Machine Learning are Redefining Customer Experience Management - Customer Think - January 27th, 2025 [January 27th, 2025]
- Machine Learning Data Catalog Software Market Strategic Insights and Key Innovations: Leading Companies and... - WhaTech - January 27th, 2025 [January 27th, 2025]
- How AI and Machine Learning Will Influence Fintech Frontend Development in 2025 - Benzinga - January 27th, 2025 [January 27th, 2025]
- The Nvidia AI interview: Inside DLSS 4 and machine learning with Bryan Catanzaro - Eurogamer - January 22nd, 2025 [January 22nd, 2025]
- The wide use of machine learning VFX techniques on Here - befores & afters - January 22nd, 2025 [January 22nd, 2025]
- .NET Core: Pioneering the Future of AI and Machine Learning - TechBullion - January 22nd, 2025 [January 22nd, 2025]
- Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU... - January 22nd, 2025 [January 22nd, 2025]
- A comparative study on different machine learning approaches with periodic items for the forecasting of GPS satellites clock bias - Nature.com - January 22nd, 2025 [January 22nd, 2025]
- Machine learning based prediction models for the prognosis of COVID-19 patients with DKA - Nature.com - January 22nd, 2025 [January 22nd, 2025]
- A scoping review of robustness concepts for machine learning in healthcare - Nature.com - January 22nd, 2025 [January 22nd, 2025]
- How AI and machine learning led to mind blowing progress in understanding animal communication - WHYY - January 22nd, 2025 [January 22nd, 2025]
- 3 Predictions For Predictive AI In 2025 - The Machine Learning Times - January 22nd, 2025 [January 22nd, 2025]
- AI and Machine Learning - WEF report offers practical steps for inclusive AI adoption - SmartCitiesWorld - January 22nd, 2025 [January 22nd, 2025]
- Learnings from a Machine Learning Engineer Part 3: The Evaluation | by David Martin | Jan, 2025 - Towards Data Science - January 22nd, 2025 [January 22nd, 2025]
- Google AI Research Introduces Titans: A New Machine Learning Architecture with Attention and a Meta in-Context Memory that Learns How to Memorize at... - January 22nd, 2025 [January 22nd, 2025]
- Improving BrainMachine Interfaces with Machine Learning ... - eeNews Europe - January 22nd, 2025 [January 22nd, 2025]
- Powered by machine learning, a new blood test can enable early detection of multiple cancers - Medical Xpress - January 15th, 2025 [January 15th, 2025]
- Mapping the Edges of Mass Spectral Prediction: Evaluation of Machine Learning EIMS Prediction for Xeno Amino Acids - Astrobiology News - January 15th, 2025 [January 15th, 2025]
- Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus -... - January 15th, 2025 [January 15th, 2025]
- Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools - Nature.com - January 15th, 2025 [January 15th, 2025]
- "From 'Food Rules' to Food Reality: Machine Learning Unveils the Ultra-Processed Truth in Our Grocery Carts" - American Council on Science... - January 15th, 2025 [January 15th, 2025]
- AI and Machine Learning in Business Market is Predicted to Reach $190.5 Billion at a CAGR of 32% by 2032 - EIN News - January 15th, 2025 [January 15th, 2025]
- QT Imaging Holdings Introduces Machine Learning-Enabled Image Interpolation Algorithm to Substantially Reduce Scan Time - Business Wire - January 15th, 2025 [January 15th, 2025]
- Global Tiny Machine Learning (TinyML) Market to Reach USD 3.4 Billion by 2030 - Key Drivers and Opportunities | Valuates Reports - PR Newswire UK - January 15th, 2025 [January 15th, 2025]
- Machine learning in mental health getting better all the time - Nature.com - January 15th, 2025 [January 15th, 2025]
- Signature-based intrusion detection using machine learning and deep learning approaches empowered with fuzzy clustering - Nature.com - January 15th, 2025 [January 15th, 2025]
- Machine learning and multi-omics in precision medicine for ME/CFS - Journal of Translational Medicine - January 15th, 2025 [January 15th, 2025]
- Exploring the influence of age on the causes of death in advanced nasopharyngeal carcinoma patients undergoing chemoradiotherapy using machine... - January 15th, 2025 [January 15th, 2025]
- 3D Shape Tokenization - Apple Machine Learning Research - January 9th, 2025 [January 9th, 2025]
- Machine Learning Used To Create Scalable Solution for Single-Cell Analysis - Technology Networks - January 9th, 2025 [January 9th, 2025]
- Robotics: machine learning paves the way for intuitive robots - Hello Future - January 9th, 2025 [January 9th, 2025]
- Machine learning-based estimation of crude oil-nitrogen interfacial tension - Nature.com - January 9th, 2025 [January 9th, 2025]
- Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients - Nature.com - January 9th, 2025 [January 9th, 2025]
- Staying ahead of the automation, AI and machine learning curve - Creamer Media's Engineering News - January 9th, 2025 [January 9th, 2025]
- Machine Learning and Quantum Computing Predict Which Antibiotic To Prescribe for UTIs - Consult QD - January 9th, 2025 [January 9th, 2025]
- Machine Learning, Innovation, And The Future Of AI: A Conversation With Manoj Bhoyar - International Business Times UK - January 9th, 2025 [January 9th, 2025]
- AMD's FSR 4 will use machine learning but requires an RDNA 4 GPU, promises 'a dramatic improvement in terms of performance and quality' - PC Gamer - January 9th, 2025 [January 9th, 2025]
- Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images -... - January 9th, 2025 [January 9th, 2025]
- Understanding the Fundamentals of AI and Machine Learning - Nairobi Wire - January 9th, 2025 [January 9th, 2025]
- Machine learning can help blood tests have a separate normal for each patient - The Hindu - January 1st, 2025 [January 1st, 2025]
- Artificial Intelligence and Machine Learning Programs Introduced this Spring - The Flash Today - January 1st, 2025 [January 1st, 2025]
- Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of... - January 1st, 2025 [January 1st, 2025]
- Open source machine learning systems are highly vulnerable to security threats - TechRadar - December 22nd, 2024 [December 22nd, 2024]
- After the PS5 Pro's less dramatic changes, PlayStation architect Mark Cerny says the next-gen will focus more on CPUs, memory, and machine-learning -... - December 22nd, 2024 [December 22nd, 2024]
- Accelerating LLM Inference on NVIDIA GPUs with ReDrafter - Apple Machine Learning Research - December 22nd, 2024 [December 22nd, 2024]
- Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis - BMC... - December 22nd, 2024 [December 22nd, 2024]