Key Job Responsibilities:
• Be able to train AI models (eg: Google Doc AI), doesn't need coding experience (D) 
• Have exposure to document checking process (E) 

• Be able to review logs and identify transactions/root cause that prevents STP (E) 

• Translate data to &gt; actionable insights eg: Enhancement CRs for tech to work on, Client exception report for educating clients (thru RMs), Procedural changes etc. (E) 

• Perform first level testing for the requirements proposed (E) 

• Be able to create process maps and user stories (E) 

• Exceptional presentation skills (data visualisation / PowerPoint) (E) 

• Experience with Tableau, Looker Studio would be added advantage, but someone with an experience of using other tools can easily learn these tools. (E) E - Essential; D- Highly Desirable

• STP Failure Analysis: Review transaction and document data to identify patterns and root causes of STP failures, including mismatches in documents or tech defects 

• Cross-Functional Collaboration: Partner with Ops and Tech teams to design and implement mitigation strategies for STP gaps, including systemic enhancements and automation of client exception handling. 

• Process Mapping &amp; Efficiency Studies: Conduct time &amp; motion studies to identify bottlenecks and inefficiencies. Experience with tools like Celonis or other process mining platforms is highly desirable. 

• STP Metrics &amp; Benchmarking: Track and report STP performance against benchmarks. Drive improvements from current STP rates (e.g., 23% for mandatory docs) toward target states (e.g., 90–100%). 

• User Acceptance Testing (UAT): Lead and execute UAT cycles for Smart Doc enhancements, validating STP impact and ensuring readiness for production deployment by testing against high volume contributing client docs.
 
• Stakeholder Communication: Prepare and deliver timely stakeholder packs summarizing STP improvement initiatives, outcomes, and next steps. 

• Operational Interlocks: Align STP efficiency gains with Ops to ensure measurable FTE savings and process rationalization. 

• Data Quality &amp; Pre-Validation: Support initiatives like Channel pre-validation and client education to improve input quality and reduce manual interventions. 

• Raw data to actionable insight: Be able to review data, draw down insights that translate to actionable task for (a) Clients, (b) Tech and (c) Ops, all aimed at eliminating rework and improving efficiencies.

Business Analyst in Bengaluru (UID-10198)

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