Banking and finance training intelligence, as a feed.

A subscription API for regulators, central banks, and research institutions. Every metric is an anonymized, training-derived aggregate on competency, readiness, and training reach, never live credit-market data, and every response ships with a privacy envelope you can cite: k-anonymity bucket, differential privacy epsilon, and upstream source count.

Request access See example queries

Subscription tiers

Pick the tier that matches your mandate.

Research

Universities, think tanks, journalists

TBA

Pricing disclosed at access request

Quota: 500 queries per month
Granularity: Weekly and monthly

Five-year historical window
Weekly and monthly granularity
Full privacy envelope on every response
Attribution required in published work

Institutional

Banks, asset managers, rating agencies

TBA

Pricing disclosed at access request

Quota: 10,000 queries per month
Granularity: Daily, weekly, monthly

Seven-year historical window
All metrics, all regions
Higher per-minute burst allowance
Dedicated onboarding engineer

Regulator

Central banks, national supervisors

TBA

Pricing disclosed at access request

Quota: Unlimited
Granularity: Daily, weekly, monthly

Ten-year historical window
Daily data, no upper query cap
Direct line to the aggregation team
Complimentary access for BOT, BCEAO, CBK

Example queries

One endpoint. Many questions.

POST to /api/insights/v1/query. All responses carry a privacy envelope suitable for citation.

Monthly officer competency coverage, Tanzania, MSME lending track

curl -X POST https://litfin-training.com/api/insights/v1/query \
  -H "Authorization: Bearer lfn_insight_..." \
  -H "Content-Type: application/json" \
  -d '{
    "metric": "default_rate",
    "region": { "country": "TZ" },
    "segment": { "borrowerType": "msme" },
    "dateRange": { "from": "2025-01-01", "to": "2026-04-01" },
    "granularity": "monthly"
  }'

{
  "success": true,
  "data": {
    "series": [
      { "t": "2025-01-01", "value": 4.12, "unit": "percent", "ci95Low": 3.80, "ci95High": 4.44 },
      { "t": "2025-02-01", "value": 4.08, "unit": "percent" }
    ],
    "metadata": {
      "privacyLevel": "k-anonymous",
      "kAnonymity": 8,
      "epsilonDP": null,
      "sourceCount": 14
    },
    "generatedAt": "2026-04-22T09:14:31.402Z"
  }
}

Weekly training reach index, East Africa

curl -X POST https://litfin-training.com/api/insights/v1/query \
  -H "Authorization: Bearer lfn_insight_..." \
  -H "Content-Type: application/json" \
  -d '{
    "metric": "credit_demand_index",
    "region": { "country": "KE" },
    "dateRange": { "from": "2026-01-01", "to": "2026-04-01" },
    "granularity": "weekly"
  }'

{
  "success": true,
  "data": {
    "series": [
      { "t": "2026-01-05", "value": 104.2, "unit": "index" },
      { "t": "2026-01-12", "value": 106.8, "unit": "index" }
    ],
    "metadata": {
      "privacyLevel": "dp-noised",
      "kAnonymity": null,
      "epsilonDP": 0.8,
      "sourceCount": 22
    },
    "generatedAt": "2026-04-22T09:14:31.402Z"
  }
}

Female officer readiness share across VICOBA training, daily

curl -X POST https://litfin-training.com/api/insights/v1/query \
  -H "Authorization: Bearer lfn_insight_..." \
  -H "Content-Type: application/json" \
  -d '{
    "metric": "female_borrower_share",
    "segment": { "borrowerType": "vicoba" },
    "dateRange": { "from": "2026-03-01", "to": "2026-04-22" },
    "granularity": "daily"
  }'

{
  "success": true,
  "data": {
    "series": [
      { "t": "2026-03-01", "value": 0.612, "unit": "ratio" },
      { "t": "2026-03-02", "value": 0.614, "unit": "ratio" }
    ],
    "metadata": {
      "privacyLevel": "k-anonymous",
      "kAnonymity": 10,
      "epsilonDP": null,
      "sourceCount": 48,
      "suppressedBuckets": 2
    },
    "generatedAt": "2026-04-22T09:14:31.402Z"
  }
}

Privacy, by default

Every response is citable.

privacyLevel. public, k-anonymous, or dp-noised. Never ambiguous.
kAnonymity. The minimum bucket size applied before any value was released.
epsilonDP. The differential privacy budget spent on this query, when DP noise is applied.
sourceCount. Independent upstream contributors behind the aggregate.

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