Financial Services industry has been at the forefront of using innovative technologies. During 2000s, banks and insurers rolled out ‘anytime anywhere’ transaction capabilities – thanks to centralized Core Banking Systems and e-channel solutions. In the new wave of digitization, the players are now leveraging technologies like Intelligent Automation along with Artificial Intelligence and GIS.
Even after computerization, transactions like account opening, loan application processing, NEFT / RTGS recon, payment gateway recon, regulatory filing and customer servicing were people intensive. The banks are now rapidly deploying RPA, OCR and AI technologies to make these processes truly automatic. Intelligent automation is able to read account opening and loan applications, validate fields and enter them in Core Banking System. Intelligent OCRs are able to download financial statements of loan applicants, analyze them and present smart summary to loan assessing officers. RPAs are able to handle customer queries using Natural Language Processing techniques and AI is helping banks in fraud detection, customer servicing and investment advisory.
Insurers too are leveraging RPA and AI for policy issuance, risk based pricing, claims fraud detection, regulatory reporting, customer servicing and improving renewal rates. GIS tools are helping insurers in improving risk-based underwriting, disaster support and reinsurance strategy.
Companies can save the effort and improve compliance to regulatory reporting by using RPA tools. To begin with, RPA tools can assist in collating data from many structured sources (e.g. IT systems, Excel sheets), semi-structured sources (e.g. PDF, images) as well as online sources (e.g. websites). Once these are converted into digital and structured data, RPA can help carry out data computations to arrive at ratios, benchmarks or percentages as required by the regulator. RPA can further arrange the data in pre-defined formats with covering notes and even email out to the regulator after due checks by the regulatory team of the company. This can help you save costs, never miss submission deadlines and reduce errors when complying with regulatory reporting requirements.
We can help you map the data sources and deploy RPA tools for regulatory reporting by leveraging our knowledge of financial services regulations and skills of deploying RPA tools.
Lastly, insurer can keep updating GIS maps with history of claims and hence build its own intelligence of risk-prone geographies by the type of insurance.
GIS is a technological tool for comprehending geography and making intelligent decisions. It gives any organization the ability to go beyond standard data analysis with tools to integrate, visualize and analyze the data using geography. Market potential assessment, customer analytics and site selection are ways businesses can combine geographical analysis for better business intelligence.
GIS can help in answering several questions such as:
- Location – What market opportunities exist at a particular location (district, locality, PIN code)?
- Trends – What are the buying and behavior partners at different geographies?
- Models – What spatial patterns exist?
- Modeling – What would happen if?
Customer analysis can be done using GIS which adds Postal address or longitude and latitude stamps to business data and visualizing the data on a map. For example, while setting up a children clothing store, we could map the population of people with children in targeted age group throughout the target geographical area like states or districts. The data once put into a GIS can generate maps wherein the highest concentration of families with children are depicted using specific color patterns. The final map so generated will highlight the ideal areas for opening new stores. Similarly, banks can visualize customer data on a map with different color schemes based on parameters like credit worthiness, income levels, no. of bank accounts customers have, average bank balances and expenditure patterns. This helps identify cross-sell opportunities, opening of ATM or Branches and run intelligent campaigns.
GIS allows businesses to convert bytes of data in legacy system databases and Excel sheets to be presented in a more visual and understandable form, thus enabling business managers to get better insights and take more informed decisions.
A large Mutual Fund in India
The leading Mutual fund in India receives numerous emails every day from customers. Handling these emails required huge manual effort even though most of these queries were repetitive in nature. We helped the Mutual Fund deploy intelligent automation involving RPA and NLP to interpret incoming emails and respond to themRead More
A large broking company
A leading Broking company offering online trading platform wished to identify newly registered customers who had higher propensity to start transacting. We helped the company develop Machine Learning based model to predict propensity to transact for members who downloaded their mobile appRead More