Banks process 50,000 new customer applications every week. Each application needs to be checked against government databases. Staff must verify Social Security numbers, addresses, and birthdates by hand. Most banks still do this work manually. The process takes days and costs millions.
American banks now spend 61 billion dollars each year on compliance, according to a 2024 study. The USA PATRIOT Act requires banks to verify every customer through Know Your Customer and Anti-Money Laundering checks. Banks spend more money each year, but still have backlogs, angry customers, and government fines.
New rules make things harder. Regulators updated requirements in 2024 and want faster responses. Banks now face tighter deadlines while handling more applications than before. The old manual system cannot keep up.
Staff spend hours checking customer information that arrives from different places. Online forms have missing details. Phone applications have typos. Branch paperwork gets filed incorrectly. Compliance teams work overtime reviewing each case. Customers wait weeks for account approval. Tired employees miss important warning signs.
Vijayalakshmi Alice Singavarapu faced these problems every day as a data engineer at a major bank. She managed the Customer Identification Program that processed about 13 million customer records each year. Every record needed to be checked against multiple databases to follow federal rules. The manual system was failing under the load.
She knew how to build systems that handle huge amounts of information. She saw that customer verification could work faster and better with automation. Instead of accepting slow manual reviews, she rebuilt the whole system.
Building Automated Verification Systems
She created her solution using Amazon EC2 servers that could handle thousands of customer records at once. Her system pulled customer data from many sources, fixed inconsistencies, and ran everything through checks that compared details against government and internal databases.
She set up AWS EC2 computers for batch processing jobs. The system could handle the bank's entire customer database while running checks that would take human staff weeks to finish. She wrote rule-based programs that found problems in customer information. The system caught mismatched Social Security numbers, wrong birthdates, bad addresses, and fake document numbers.
Her automated system put every customer record into three groups. Good accounts that passed all checks went straight to approval. Records with small problems went to a review list for staff attention. Bad records that failed checks got flagged right away for investigation.
She also built reports that showed compliance officers exactly what the system found. The reports listed data problems, success rates, and accounts that needed follow-up work. This gave business teams clear records for government audits and helped them spot patterns in application issues.
"The system we built changed everything about customer verification," Vijayalakshmi Alice Singavarapu says. "Compliance teams stopped spending all day checking routine cases and could work on complex situations that needed human judgment."
Her automation handled basic verification tasks that used to take up most of the compliance staff's time. Her system processed normal applications in minutes instead of days while flagging truly suspicious cases for immediate review.
Improving Accuracy While Cutting Costs
Her Customer Identification Program delivered results beyond just speed gains. Faster processing meant customers got account approvals in hours instead of weeks. The automated checks caught more problems than manual reviews, cutting fraud risk and rule violations.
She worked with compliance officers, fraud investigators, data teams, and security staff to make sure her system met both technical and regulatory needs. This teamwork created a new way to implement compliance technology that balanced automation with human oversight.
Her system solved banking's biggest compliance problem. It maintained regulatory standards while processing applications fast enough to satisfy customers. She proved that automation could improve compliance quality rather than hurt it. Automated systems gave more consistent verification than human reviewers while cutting processing time dramatically.
The work showed how data engineering skills could tackle complex regulatory problems while improving customer service and operational efficiency. The teamwork between technical and compliance staff became a model for other regulatory technology projects.
"When you process 13 million customer records, you need consistency," Vijayalakshmi Alice Singavarapu explains. "Automated systems don't make mistakes from being tired, don't miss important details, and treat every application the same way."
The success came from her technical approach combined with careful collaboration across different bank departments. Her system handled massive data volumes while maintaining the accuracy and documentation that regulators require.
Changing How Banks Handle Compliance
Her Customer Identification Program shows changes happening across financial services. Banks that still use manual compliance processes face growing pressure from regulators and customers who want faster service.
The methods she used are becoming standard tools for modern compliance work. Cloud-based batch processing, rule-based validation, and automated sorting now appear in compliance systems at banks nationwide. Her use of AWS EC2 computers showed how cloud technology could handle massive customer databases without breaking budgets.
The teamwork approach she took with compliance staff has become the standard for successful regulatory technology projects. Banks that make sure automated systems meet both technical performance goals and regulatory requirements get better compliance results while improving operational measures.
Her customer verification methods now spread to other compliance areas, including transaction monitoring and regulatory reporting. Banks that adopt these automated approaches gain advantages through faster processing, lower costs, and stronger regulatory compliance.
Industry data shows compliance costs increased for 98% of financial institutions in 2023, making automation solutions like hers more valuable. Banks that embrace data engineering approaches to compliance challenges turn regulatory requirements into competitive advantages that improve both regulatory outcomes and customer satisfaction.
Projects like Vijayalakshmi represent a shift in how banks handle compliance work. Smart institutions use technical expertise to transform compliance from an expensive burden into a competitive edge.