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NYC-based Finance Firm Automating Recruitment with Resume Parsing API
User Details
- A prominent finance MNC headquartered in New York, specializing in financial services and consulting.
- With over 8 global offices and 4500+ employees working actively, they offer their clients innovative financial solutions such as banking support services, funds management, and investor engagement worldwide.
Problem Statement
Well, the company is quite dynamic in nature when it comes to hiring people. They want to ensure they get the best candidates on board for their finance solutions. In the process, the client faced significant challenges in their recruitment, which blocked their ability to hire the right talent swiftly and effectively. These challenges included:
High Volume of Applications
The client’s offices received thousands of resumes for each job opening, overwhelming their HR team and leading to delays in screening and shortlisting ideal candidates.
Inconsistent Resume Formats
Applicants submitted resumes in various formats(IMG, PDFs, DOCs, Online Portfolios, etc), making it difficult for recruiters to compare and evaluate candidates efficiently.
Time-Consuming Manual Screening
The HR team spent an excessive amount of time manually reviewing resumes and matching them to job descriptions, resulting in slow turnaround times and missed opportunities.
Difficulty in Matching Skills to Job Requirements
Identifying candidates with the right skills and experience was challenging due to the lack of an automated system to match resumes to job descriptions accurately.
High Recruitment Costs
The inefficiencies in the recruitment process led to increased costs in terms of time, resources, and missed business opportunities.
Looping In “HireLakeAI”
One of the company’s HR managers took a free product demo for HireLakeAI and discovered a significant boost in resume processing and sorting speed. Based on this success, the company integrated HireLake API/business solutions, which include enhanced features like AI-backed resume parsing and JD(Job Description) matching.
AI-Based JD Matching
With HireLakeAI’s advanced AI algorithms, the time to match each resume went from 15 minutes to under 60 seconds. The platform automatically screened and shortlisted candidates based on the specific criteria outlined in the job descriptions.
AI Resume Parsing
HireLakeAI’s resume parsing feature accurately extracted relevant information from various resume formats in seconds. This ensured consistency and completeness for further processing. With not just “keyword-based parsing”, HireLakeAI scanned the entire resume to extract valuable insights for a complete understanding of each candidate.
Seamless Integration
Embedded HireLakeAI’s API with Workday, facilitating real-time data flow between the HRMS and hiring platforms like Monster and Naukri. This integration scrapped the manual data entry part, reduced errors, and ensured up-to-date candidate information across all platforms.
User Impact
The time taken to screen and shortlist candidates reduced from an average of 10 days to just 2.5 days, leading to faster hiring cycles.
The client saved approximately $25,000 annually by reducing the need for additional recruitment resources and minimizing time-to-hire.
The accuracy of JD matching led to a 39% increase in the quality of shortlisted candidates, ensuring that new hires were better suited to their roles.
The improved candidate experience and quicker response times resulted in a 30% increase in offer acceptance rates, reducing the risk of losing top talent to competitors in the marketplace.
The client could now handle a 50% increase in job openings without additional strain on their HR departments, supporting their future and expansion plans.
HireLakeAI’s AI-powered resume parsing and JD matching API gave our client a serious hiring upgrade. By automating the process and finding the perfect candidates for each vacancy, it helped them save time, and additional costs, and improve the quality of their new hires. This solution not only fixed their hiring setbacks but also set them up for scalable success in finance.
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