Shanmuka Siva Varma Chekuri automated Everest Reinsurance’s global systems, cutting manual work by 70% and embedding compliance to mitigate cyber-risk.
Published: February 5, 2026 11:12 AM IST
Working for Everest Reinsurance across North America, Europe and Asia-Pacific, Shanmuka Siva Varma Chekuri reduced manual reconciliation by 70% and achieved same-day payment cycles, proving embedded compliance matters more than fixing regulatory violations after detection as ransomware claims multiply faster than infrastructure adapts.
The cyber insurance market is expected to reach $32 billion by 2030, doubling from its current value of $16.3 billion, as ransomware attacks, supply-chain breaches, and data exfiltration incidents continue to multiply across various industries. Yet, a Munich Re’s 2025 report warns that premium growth conceals a structural vulnerability: reinsurance data infrastructure wasn’t built for the speed and complexity modern cyber claims demand. When claims and payment information arrive in different formats from multiple vendors across jurisdictions, reconciliation becomes manual, error-prone, and slow. One missing record can delay millions in settlements. One corrupted file can trigger weeks of human verification. One audit failure can destroy the reputational trust that took decades to build. For reinsurers operating as the financial backbone behind insurance companies, data fragmentation isn’t an operational inconvenience—it’s a systemic risk threatening the industry’s ability to absorb the surge in cyber claims ahead.
Shanmuka Siva Varma Chekuri spent years solving precisely this problem as a Senior Data Engineer currently working with Everest Reinsurance, building systems connecting claims and ERP infrastructure across North America, Europe, the UK, Singapore, and Australia. His work demonstrated a principle that most reinsurers discover only after expensive failures: that compliance can’t be treated as an afterthought auditing exercise separate from live data systems, and that automated validation, preventing regulatory violations by design, matters more than fixing them after detection. To address this challenge, he used Azure Lakehouse architecture with proprietary frameworks for multi-file validation and concurrency-safe processing. These solutions reduced AP processing time by 65%, decreased manual work by 70%, and eliminated 90% of reconciliation errors. Additionally, they deliver same-day invoice-to-payment cycles and full audit trails. This approach challenges an assumption that faster processing means sacrificing control when compliance should be actually embedded into the data architecture from the start.
Today, data fragmentation is the most immediate threat facing the reinsurance industry. Claims and payment information often come in various formats from different vendors, thus leading to more manual checks and the consolidation of information that further increases the cost of error. “Here, one missing record may delay millions of payouts or lead to an audit failure,” Shanmuka notes.
So, Shanmuka solved this problem through the restructuring of a data ingestion process, using his own frameworks to confront his most difficult task—fully automating the global Accounts Payable (AP) system at Everest Reinsurance, which covers North America, Europe, the United Kingdom, Singapore, and Australia. Now, his proprietary Multi-File Control Validation Framework validates file integrity and consistency automatically. His Concurrency-Safe Delta MERGE Pattern avoids overwriting conflicts when thousands of jobs run concurrently. As a result, AP processing time was cut by 65%. Also, manual work shrank by 70%. Equally, errors during reconciliation came down by 90%. Together, they help achieve same-day invoice-to-payment cycles. Thus, his frameworks have become in-house reference points for financial and insurance clients.
Another factor that is just as dangerous to the stability of the industry is the compliance gap that makes nonsense of automation. Compliance is a practice that is treated as an afterthought by many insurers, including those in our country, who consider it as an independent audit exercise that has nothing to do with their live data systems, thereby exposing them to more risks.
Shanmuka’s philosophy turns this logic on its head using his Audit-Lineage Methodology. Now, each record handled by his systems has a full history of transformations, timestamps, and approvals, thus making it easy to trace transactions between source and ledger. This design, which became the pillar of his work in regulated insurance settings, cut the time spent in preparing audits by over 50%, from several weeks to just one day. “The most convenient method of satisfying regulation is to ensure that no one can contravene it by accident,” he adds.
The last part of the problem is scale. For a reinsurer to operate in our country, the United States, the United Kingdom, and the larger Asia-Pacific region, it has to deal with diverse tax regulations, data rules, and payment systems. Without a common system of regulations, every territory applies its own fixes, thereby slowing things down and creating confusion. To solve this problem, Shanmuka expanded the same data systems—the automation tools for claims and payment processing he originally created with AI at Everest Reinsurance—into a model that works across different territories. The model employs uniform checks, records, and safety procedures across the board, while being mindful of the laws of every relevant jurisdiction. A claim in Mumbai, for example, which must follow the data regulation in our country, goes through the same secure and traceable procedure as a claim in New York. This ensures that everything is checked, easily tracked, and in accordance with applicable regulations. “You can’t build international trust on local logic,” he concludes. “The system should understand every border without failing at any of them.”
Currently, cyber threats are growing very fast globally and in our country in particular. Yet, Munich Re predicts that cyber insurance premiums will double by 2030 as ransomware and supply-chain attacks are expected to continue to rise. Systems like the one created by Shanmuka, which incorporate strong data verification into reinsurance processes, do not simply speed things up, but rather guarantee the integrity of data and make our insurance industry stronger at both national and international levels as digital threats continue to grow.
Also Read:
Topics
Disclaimer : This story is auto aggregated by a computer programme and has not been created or edited by DOWNTHENEWS. Publisher: india.com
