Financial Services
Reduce Operational Cost, Minimize Risk & Enhance Customer Experience
with A Powerful AI/Data Analytics Based Financial Solution.
Harness AI for
Financial Service
Operations
In the fast-paced world of today, financial organizations need to make the best choices in the shortest time. Historical data on which we’ve always relied is becoming more irrelevant, as situations change in the blink of an eye. AI& Data Analytics equips FSOs with real-time insights to make decisions on the fly, understand their customers better, and present them with tailored value propositions.
Deploying sophisticated solutions in financial services also requires industry-specific nuances and regulatory compliance. FSOs need to strike a balance between consumer insights and customer privacy, automating tasks without losing the human touch, and ensuring compliances are met without impacting the customer experience.
Data Woes In The BFSI Industry: Challenges
The BFSI industry faces numerous challenges in managing and leveraging data effectively. The volume and complexity of data, increasing regulations, and the need for real-time insights pose significant obstacles. By leveraging data analytics, BFSI companies can gain insights into customer behavior, reduce fraud, improve risk management, and enhance operational efficiency.
Managing And Processing Large Volumes Of Data
BFSI companies have to deal with large amounts of data generated from various sources such as transactions, customer interactions, and market trends.This data needs to be processed, analyzed, and stored securely for future use.
Ensuring Data Accuracy And Consistency
Inaccurate or inconsistent data can lead to wrong decisions, regulatory compliance issues, and financial losses. BFSI companies need to ensure that their data is accurate and consistent across all sustems and platforms.
Legacy Systems And Data Silos
Many BFSI companies have legacy systems that are not compatible with modern technologies, making it difficult to integrate data from different sources. Data silos can also lead to redundant data, duplication of efforts, and inconsistent information.
Trigger Growth With An End-to-End Solution
Credit Risk Scoring
By using multiple data points to analyze customer behavior, income-tax history, financial history, and other transactions, AI/Data Analytics empowers lenders to determine the risk score for each customer, and accurately predict who is most likely to repay a loan.
Customer Acquisition for eVendors
By analyzing the behavioural data and digital footprints on the lender's digital property, AI can predict the customer's purchase intent. Lenders can identify consumers who are most likely to buy a product, those who would need some persuasion, and those who are disinterested in the products.
Debt Collection
AI-powered tools can optimize debt collection by boosting decision-making when it comes to debt collection. It can detect patterns in historical data of solvent and insolvent borrowers, provide valuable inputs to decision-makers, and make it easier to spot at-risk accounts so debt collectors are proactive rather than reactive.
Churn Management
Sift through vast volumes of data and organize information based on who is most likely to churn. AI/Data Analytics helps you uncover specific profile attributes like age, gender, income, number of products, and the campaign from which someone came. By spotting these indicators, AI can identify customers’ intent on leaving, analyze the whys and hows, and proactively develop a strategy to combat churn.
Operational Excellence
With increased digitalization across the sector, especially among neobanks and fintechs, traditional financial institutions too will need to leverage the latest tools and technologies to drive digitally-enhanced process improvement initiatives and automation processes including claims approval, fraud detection, documents digitization, and underwriting.
Customer Analytics
As more customer interactions occur via digital channels, insurers can leverage dynamic consumer information to design solutions that better match clients and get ideas to market more quickly. AI and data analytics also provide scalable personalization in distribution, underwriting, claims, and services, allowing individuals to enjoy personalized experiences
Personalized Recommendations
Data analytics allows businesses to provide customized solutions to clients on a large scale. Companies are harnessing data insights to provide customer value in various ways, including data-driven portfolios, AI-based recommendation systems, merchant offers based on financial history, life cycle stage, and contextual information.
Cross-Selling
Personal financiers can detect user behaviour patterns, anticipate income and expenses, and provide customized suggestions using statistics and modeling. By analyzing buyer behaviour at the account level, banks can customize their offerings to a particular demographic and boost a campaign's ROI.
Customer Experience
n terms of customer experience, AI and machine learning can assist personal financiers and retail bankers to predict client demands and deepen connections by customizing their approaches, fine-tuning ads for optimal efficacy, recognizing attrition risks and targeting customer categories that offer the highest acquisition potential.
Harness AI & Financial Service Operations
Our Success Stories
Creating a Credit Risk Scoring Model For Micro Small Consumer Loans Using AI
See how we assisted a top fintech in the East Africa and Columbia region assess the credit risk of microloans while servicing a population with limited credit risk.
Our Winning Moves
- Classified consumers into four categories based on their risk characteristics
- Studied transaction patterns over time (previous two weeks, four weeks, etc.), consistency and volatility in transactions, percentage and index increase in transactions, prior loan repayment behavior, etc.
- Conducted out of time validation for three months of data.
- Built a normalized scoring framework by fixing the factor and offset for four models.
Outcome
15%
Improvement in loan approvals over 6 months
10%
Reduction in default rates
60-70%
Lift of trained models
Predictive Churn Management for A Life Insurance Company
Learn how Valiance assisted a pan-India private life insurer with a multi-channel distribution strategy improve its retention and persistency ratio, while reducing the cost of customer acquisition.
The Key Challenge
The client’s persistency metrics (13th, 25th, 37th ) were below the industry average.
Our Winning Moves
- Employed a quantitative approach and adopted scientific measures to understand the cause behind poor persistency.
- Devised optimal renewal strategies for agent follow-ups, email reminders, SMS alerts and telephonic follow-ups.
Outcome
20%
Increase in policy persistency in 1st year
3M
USD
Increase in revenue
Cross-selling Personal Loans While Reducing Risks
Discover how Valiance helped a leading financial services company in India with over 20,000 employees across 1400 locations improve its personal loan campaigns. The company is focused on lending, asset management, wealth management and insurance.
The Key Challenges
- The traditional customer segment approaching the client for a personal loan has been those who are unable to secure similar loans from a bank. Since personal loans are unsecured, the risk of lending to a new applicant is high. However, high interest rates make this product attractive from an ROI standpoint.
- The client wanted to leverage the already existing customer base with previous payment track record as they were less risky.
- Customers campaigns across existing customer base provided limited scope and conversions.
Our Winning Moves
We helped the client expand personal loan penetration across the existing customer base. We also used a combination of intelligent methods to proactively handpick customers who were more likely to respond to personal loan offers.
Outcome
10%
Increase in conversion rates compared to those from previous campaigns.
20%
Higher ticket size iin the portfolio of new cross sell campaigns
