ALIS is a private AI system that learns from your bank's past lending files and policies. It helps your underwriters, collections and risk teams make faster decisions — and shows the reasoning behind every one.
ALIS is not a new system to learn. It connects to the software you already use, and gives your credit team one place to ask questions, review files and catch risks early.
Underwriters, collections and ops staff ask questions in plain English. ALIS reads the file, pulls bureau and bank data, and drafts a recommendation with clear reasoning.
It studies the thousands of lending decisions your team has already made. Admins can review what it learned, correct mistakes and approve new patterns.
Ready-made links to your LOS, LMS, bureaus (CIBIL, Experian, CRIF, Equifax), Account Aggregator, KYC systems and your own databases.
Type a borrower's name, employer or business and ALIS pulls news, sector signals, litigation, MCA filings and local economy context — so a loan in a monsoon-linked district is read differently from one in a salaried pincode.
Manage policies, tune the model, and keep a complete audit trail. Every decision — and every override — is logged, timestamped and exportable for RBI inspections.
ALIS runs inside your own cloud or data centre as a single-tenant system. No data is copied outside, nothing is shared between banks, and every bank gets its own private ALIS instance — trained only on its files and its policies.
ALIS plugs into your LOS, LMS, bureaus, Account Aggregator and internal databases through secure, read-only connectors. Your core systems stay exactly as they are today — there's no migration, no rip-and-replace, and no disruption to your underwriting or collections workflow.
We ingest your historical loan files, sanction memos, decisions and outcomes, along with every version of your policy manual. ALIS studies how your credit committee has actually decided — what you approve, what you decline, what you exception — so it reasons the way your team reasons, not the way a generic model does.
Your underwriters, collections officers and risk analysts get a working assistant from day one. They can ask questions in plain English — "Does this file fit our Tier-2 LAP policy?" — and ALIS comes back with a clear recommendation, a confidence level, and the three closest past files it reasoned from.
Every answer ALIS gives is traceable. It names the policy clause it applied, lists the past files it compared against, shows the bureau and cash-flow data it relied on, and logs who reviewed or overrode it. When an RBI inspector asks "why did you approve this loan?", your team has a one-click answer.
A bureau score tells you how someone has paid in the past. It doesn't tell you if their employer just laid off 2,000 people, or their sector is under stress, or their local economy is slowing.
Type a borrower's name, employer or business into ALIS and it pulls together a real-time research brief — news, sector signals, litigation, MCA filings, local economy context, and public background — all cited, all traceable.
Headcount up 1.2% this quarter. No major layoffs in last 12 months. Attrition has normalised to 12.3%.
Discretionary spending weak in BFSI clients. Fresher hiring slower than 5-year trend. Salary growth muted at 6–8%.
Median tenure in similar roles: 3.2 yrs. Salary in range for Bengaluru, band 5. 94% of past cohort files performed.
No director roles. No pending cases. No PEP/sanctions match. No adverse news in last 24 months.
Here's what your underwriter sees when they open a loan application. The recommendation always comes with the reason behind it — so you can trust it, or override it.
| FILE | CITY | SIM. | OUTCOME |
|---|---|---|---|
| LAP-38112 | Nashik | 0.94 | Performing 9/9 |
| LAP-37044 | Aurangabad | 0.91 | Performing 14/14 |
| LAP-39221 | Pune | 0.89 | Performing 6/6 |
| LAP-36910 | Kolhapur | 0.87 | 1× 30 DPD |
| LAP-38545 | Nagpur | 0.86 | Performing 11/11 |
File fits LAP §4.2.1 (Tier-2, salaried + SE co-app). DSCR 1.42× clears 1.30× threshold. CIBIL 784 clears 720 minimum. 131 of 142 similar past files are performing; closest match LAP-38112 currently performing 9/9.
Soft watch: 62% of co-applicant income is contractual. Suggested condition: verify contract tenure ≥ 24 months at sanction.
| 09:14:02 | File created in LOS by RM a.subramanian |
| 09:14:58 | KYC verified · PAN + Aadhaar + Digilocker |
| 09:16:40 | Bureau pull · CIBIL 784 · Experian 772 |
| 09:22:11 | AA consent granted · HDFC SB · 18 months |
| 09:38:04 | Policy engine ran · §4.2.1 · 7/8 checks cleared, 1 soft watch |
| 09:41:17 | ALIS recommendation generated · APPROVE · conf 87% |
| 09:41:18" | Similar past files matched: 142 · top-5 shown |
No rip-and-replace. ALIS connects to your existing tools on day one.
TurboLOS, Newgen and in-house systems also supported.
CIBIL, Experian, CRIF and Equifax — direct integration.
Consent-based bank statement and salary data.
Masked Aadhaar and name-DOB reconciliation across sources.
Plus your internal data warehouses and lakes.
Document, employer and negative-database checks.
Ozonetel, Exotel and leading field-agent platforms.
Your existing identity provider, with MFA.
Every action is logged. Every decision is traceable. Your data never leaves India — and never leaves your own cloud.
Key Fact Statements, consent flows and cooling-off periods wired into every relevant screen.
Consent management, purpose limitation, and customer data access and erasure workflows.
Single-tenant deployment in AWS Mumbai, Azure India, or your on-premise. No data leaves the country.
Every decision, override and policy change is logged. Export RBI-ready reports in a few clicks.
We'll set up a private walkthrough for your team. Bring a few sample (redacted) past files, and we'll show you ALIS reasoning through them — in a secure sandbox.