CAF
RCI
Centre for Analytical Finance
- About
- Policy Advisory and Government Engagement
- Research
- Partnerships
- Publications
- RA Programme
- Projects
- Industry Outreach
- News
- People
- Connect
About CAF
The Centre for Analytical Finance (CAF) was established in the year 2004, with a mandate to produce high quality research, create research database, organise conferences and workshops, and train next generation of researchers in the area of finance. Through its Conferences, Workshops and Researcher’s Training programme, the Centre has created a forum for academicians, regulators and industry professionals, to discuss the latest issues and research. Centres association with the distinguished scholars of global repute and top industry practitioners makes it one of the premier research centres in South-east Asia.
- Undertake research projects that will aid and inform: Financial markets, Financial institutions, Financial instruments and Financial regulations
- Focus on issues in finance, including access to financial markets for small and micro entrepreneurs
- Disseminate research-based knowledge through conferences, workshops and lectures among all CAF constituencies: Academics, Practitioners, Regulators and policy-makers
- Create data-sets to help and benefit academicians as well as practitioners
- Consolidate our position as the premier research centre in the Asia-Pacific region
- Achieve global standing in the foreseeable future
Policy Advisory and Government Engagement
Our advisory work bridges rigorous research and real-time policymaking, enabling governments to design fiscally sound, socially impactful, and scalable interventions.
Our engagements span diagnostic assessments, policy design, fiscal analysis, and impact evaluation, supporting governments at the agenda-setting, budgeting, and implementation stages.
Pre-Budget Consultations: Analytical inputs on priorities, fiscal trade-offs, and reform options. Policy Diagnostics: Identification of structural bottlenecks using data-driven frameworks. Program Impact Evaluation: Policy impact assessment (including RCTs).
Our research portfolio spans national evaluations and state-level policy initiatives, including the Telangana Vision 2047, the establishment of the Street Vendor Incubation and Scaling Centre, the pan-India evaluation of PM SVANidhi, and work on algorithmic approaches to credit assessment for SHGs and micro-entrepreneurs undertaken in collaboration with microfinance institutions and SHG-linked credit systems.
Research
Our research focus includes real-time issues from financial markets, instruments, institutions, and regulations. We undertake projects which have policy implications, gather primary and secondary data, test our hypothesis by employing cutting-edge econometric techniques and come out with actionable recommendations. We form partnerships/associations and undertake collaborative research activities with finance think tanks and research centers of global standing.
Partnerships
The Centre for Analytical Finance (CAF) collaborates with governments, financial institutions, and development partners across India to advance data-driven research and policy solutions in finance. These partnerships focus on applying rigorous analytics, evidence-based evaluation, and innovation to strengthen financial systems, expand inclusion, and improve institutional decision-making.
Research Associate Programme
Training the next generation of researchers is an important CAF activity. Each year, CAF recruits two or three bright and motivated recent graduates in Finance, Statistics, Mathematics, Economics, Engineering, and Business as Researchers.
The center focuses on doing academic research with an industry application rigor. We design business tools using sophisticated models based on our ongoing research. These tools are actively used by lending institutions, credit bureaus and regulatory bodies whom we associate with as knowledge partners.
The tool uses state of the art machine learning algorithms to give a risk score associated with each new loan applicant. This tool uses information from the customer application, economic indicators local to the demographic factors and loan repayment partners of existing customers.
The tool has been designed based on the paper titled " Fintech for the Poor: Financial Intermediation Without Discrimination".
The tool uses state of art machine leaning algorithm to predict the stickiness of a customer to the banking correspondent network after a failed transaction. The tool helps the banking correspondent agents to take corrective measures to retain customers who are likely to drop out.
The tool has been designed based on the paper titled " Fintech for The Poor: Do Technological Failures Deter Financial Inclusion?".
The tool uses cluster models along with basic statistical predictors to identify volatility in banking correspondents’ transaction pattern. The tool helps the aggregator to monitor major deviation in agents’ transaction patterns.
The tool has been designed based on the paper titled " Fintech for The Poor: Do Technological Failures Deter Financial Inclusion?".
