AI for Enterprise Banking
AI/ML automation
AI for Enterprise Banking
AI/ML automation
AI for Enterprise Banking
AI/ML automation
Goal & Purpose
Enterprise banking requires AI and legacy seamless integration. Data must be classified and structured, flow through the correct internal processes, and integrate with both legacy and 3rd party partners, all within a secure on-premise environment.
Verification
Process Automation
On-Premise
Integrated AI
KYC: Advanced Data Extraction
Interplay® can extract structured data from smartphone photos of IDs, including driver's licenses, passports, etc. This allows a quick verification and Know Your Customer (KYC) for anyone looking to verify account owners, buyers, or sellers.
Interplay is trained to recognize a myriad of document sources, data fields, and known structured data models. It is currently deployed in Asian financial institutions to verify transactions.
Neural Patterns for Mortgages
By building an NLP word cloud based on the terms and text of mortgage applications, we can model trends, find “hotspots”, and uncover relationships between terms for faster processing and smarter overall market analysis.
Legacy System Integration
Financial institutions have an enormous investment into existing legacy systems that have functioned for years or even decades without major disruption. CTOs are faced with the challenge of protecting this investment while also incorporating new technologies.
Interplay can connect modern AI engines to legacy systems that may not have APIs available: text scraping, RPA, ANSI feeds, etc. can all work inside an integrated low-code application flow.
System Flow
On-Premise Deployment
Enterprise banking demands on-premise servers for security and speed.
Interplay runs on data-center hardware and edge servers wherever remote or bandwidth-constrained locations require AI and applications for the organization.
AI Structured Data Document Verification
Interplay handles document extraction for Asian Banks across multiple languages and character sets. The AI is trained on trade finance documents and import records. This produced AI models with millions of pre-trained data points.
This AI improves trade finance and other banking document verifications and routing. Verification includes original document copy classifications as well as seal and chop extractions. Automation minimizes manual human hand-holding for advanced job tasks, bringing efficiency and accuracy.
AI Dynamic Contract Analysis
Contracts held by clients can be scanned and instantly sorted by the recognized entities and topics covered. The text of the contracts and documents can build the NLP recognition engine for custom AI training, which builds a stronger proprietary knowledge base. All these documents then start into an automated workflow as determined by internal managers.
Credit Risk Patterns via Neural Modeling
Credit risk analysis is one of the strongest cases for neural modeling to recognize patterns. With ever-changing market conditions, ambiguously defined customer groups, and varied asset profiles, traditional risk profiling is rife with misclassifications.
When neural network models are applied to customer and asset data sets, patterns are found, trends are recognized, often in unconventional and unexpected ways.
Financial Data Extraction
Banks often deal with unorganized and unstructured data from contracts, receipts, and 3rd party printed financial statements, or from unstructured data feeds.
Interplay’s dynamic data extraction ML can recognize financial data, structure it, and port it directly to existing legacy systems for further processing, while also providing analytics and further training to the AI/ML.
Workflow Automation: Legacy←→SaaS
Bringing data to existing legacy platforms can be leveraged further when connected to the ever-expanding universe of SaaS providers and point solutions via 3rd party APIs.
Interplay provides a drag-drop environment to build out workflows that shuttle data seamlessly from legacy in-house systems to 3rd party SaaS providers for CRM, customer profile lookup, background checks, etc., and get completed data right back.
AI/ML Management for Loan Queues
Loan queue automation can leverage AI/ML to bring more accurate scoring information much more quickly to loan officers:
- Missing profile information can be estimated based on recognized patterns and then merged and confirmed with 3rd party information
- Documents are routed automatically through the workflow to eliminate the wait on human sorting
- Queries to external sources can be automated for faster responses and without human typing errors
- Synthetic data can protect consumer identities
AI for Smart Customer Chatbots
Customer assistant chatbots can be powered by a specific vocabulary built by computer modeling of all existing auction texts with Natural Language Processing (NLP).
Hundreds of “intents” are recognized by the AI-chatbot. Roughly half of all enquiries are handled by the AI – immediately – the rest are passed on to human agents. This same vocabulary drives search, quizzes, and trend interactions.
Biometric Verification
Biometric palm scanners can be integrated into retail banking locations for further verification of customers. Together with smart ID scanning, the biometric scan provides extra security. Scanners can be placed at ATM entrances, loan desks, or anywhere an extra layer of security will benefit both the bank and the safety of the customers.
AI/ML Classification for 3rd Party Data
Data from third parties, whether at the customer-level interacting with apps, or at the business-level with different (and sometimes competing) actors all sharing data at different levels, the inbound potential is unstructured, duplicate, and unclear.
Iterate leverages AI/ML to automatically classify 3rd party data, structure the data based on patterns, and route the data according to internal rules.
Synthetic Data for Customer Privacy
Customer data privacy is paramount to the enterprise. Simultaneously, B2B data connections, AI risk models, and analytics also benefit from large sets of customer data.
Synthetic data can satisfy the data volume needs for the enterprise while also shielding customer privacy.
Fully Secure Architecture
Interplay’s data protection, encryption and privacy compliance all combine to provide the enterprise-level security required by financial firms. The entire application platform can be hoested within the bank's own on-premise data center, with full security at every level in the architecture.
Bank Lobby Threat Awareness
Resulting from our work with schools and retail environments, Interplay has a full threat awareness suite included that can identify guns, rifles, knives, and can also determine if assailants are wearing balaclavas.
This threat awareness leverages existing video feeds from security cameras, and requires no special equipment.